🌱 Youth Electives Ages 8–15"Students who believe they have ideas worth expressing, and the ability to express them, become lifelong readers and writers."Youth Course Development Standards
🧠 How AI Works
✏️ Make & Create
🛡️ Truth & Safety
🛠️ AI Toolbox
🎓 AI in School
💻 Code with AI
📗 Young Adult Electives High School – Undergraduate
🎨 Art & Creativity
🛠️ AI Tools & Apps
🌐 Society & Domain
🚀 Applied Foundations
💡 Business Essentials
🔒 Cybersecurity
💼 Professional Electives Career & Graduate Level
📋 Strategy & Org
📡 AI Models & Research
🔭 AI Frontier
⚙️ Development
🔒 Cybersecurity
🎓
90 Courses Available
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Core Course 1 of 18
AI Governance
Understand how AI is regulated, who makes the rules, and why it matters. Explore international policy frameworks, corporate accountability, and what responsible AI deployment looks like in practice.
Live8 Modules
Course modules
M1
Defining AI Governance
What it is, what it isn't, and why the question matters more than the answer
M2
The World's First AI Law
How Europe decided to regulate AI — and what that means for everyone
M3
The US Approach
Voluntary frameworks, principles-based guidance, and the theory behind American AI policy
M4
China's AI Governance Framework
State-centric regulation, targeted rules, and a different theory of what AI governance means
M5
Corporate AI Governance Structures
How organizations govern AI internally — and the gap between policy and practice
M6
How AI Auditing Works
Technical audits, process audits, and outcome audits — and why each alone is insufficient
M7
What Corporate AI Policies Contain
The anatomy of a corporate AI policy — and why structure matters for reading critically
M8
Policy Drafting Fundamentals
How to write AI governance policy that creates real obligations — not just intentions
Explore how AI shapes jobs, laws, communities, and culture. Examine real-world case studies on bias, fairness, and the future of human-AI collaboration.
Live8 Modules
Course modules
M1
AI Is Already Everywhere
Mapping the systems shaping your day before you notice them
M2
What AI Actually Does to Jobs
Task automation, labor market power, and what the evidence says
M3
Disinformation at Scale
How AI changes the production, spread, and detection of false information
M4
Facial Recognition and Biometric Surveillance
How AI identifies people at scale — and what that changes about being in public
M5
The Digital Divide and AI Access
Who gets AI's benefits — and who gets left out
M6
The Digital Divide and AI Access
Who gets the benefits of AI — and who gets left behind
M7
The Energy Cost of AI
What training and running AI actually costs the planet — and why the numbers are contested
M8
Forecasting AI — What We Know and Don't Know
How to think about AI's future without falling for hype or dismissal
Dive deep into generative AI for writing, art, music, and storytelling. Learn to collaborate with AI as a creative partner while protecting your original voice.
Live8 Modules
Course modules
M1
How Generative AI Works
The models behind text, image, audio, and video generation
M2
AI & Writing
Using AI for drafting, editing, and storytelling — and its limits
M3
AI & Visual Art
Tools, techniques, and the authorship question
M4
AI & Music
From composition to production — how AI is changing music
M5
The Consent & Copyright Problem
Training data, style theft, and the legal gray zone
M6
Protecting Your Creative Voice
How to use AI without losing what makes your work yours
M7
AI as a Creative Partner
Workflow design for human-AI creative collaboration
M8
The Future of Creative Work
Economic and cultural implications of generative AI
A capstone exploration of where AI is headed — technically, socially, and philosophically — and how to think about it clearly.
Live6 Modules
📱
Core Courses · Course 19
AI in Social Media
Understand how AI shapes your social media experience through content filtering and targeted advertising. Learn about algorithmic content moderation and social influence.
4 Modules
🔍
Core Courses · Course 20
AI and Misinformation
Learn to recognize, evaluate, and counter AI-generated misinformation. Covers detection methods, information verification techniques, and the infrastructure that amplifies false narratives.
4 Modules
Course modules
M1
Every New Medium Rewrites What We Believe
How new information technologies have always disrupted what counts as truth
M2
Reverse Image Search and Visual Verification
Practical tools and techniques for verifying images and video online
M3
Firehosing and Flooding the Zone
The deliberate strategy of overwhelming audiences with contradictory claims
Compare the leading AI models — their strengths, limitations, design philosophies, and real-world performance. Learn to choose the right model for the right job.
Live8 Modules
Course modules
M1
The Model Landscape
Who built what, and why the differences between models actually matter
M2
How GPT-4o Works
OpenAI's architecture, training approach, and what makes it distinctive
M3
Understanding Claude
Anthropic's constitutional AI, safety focus, and where Claude excels
M4
Gemini and Google's Approach
Multimodal-first design and how Google's AI strategy differs
M5
Benchmark Reality Check
What benchmarks measure, what they miss, and how to read them critically
M6
Cost, Speed, and Context
Practical tradeoffs — tokens, latency, pricing, and context window limits
M7
Choosing the Right Model
A framework for model selection across use cases and constraints
M8
The Frontier Is Moving
How to track model releases and evaluate new models as they launch
Explore AI systems that see, hear, and generate across text, images, audio, and video. Understand how multimodal capabilities are reshaping what AI can do.
Coming Soon8 Modules
Course modules
M1
What Multimodal Means
Why combining modalities is harder than it sounds — and why it matters
M2
Vision-Language Models
How models like GPT-4V and Gemini understand and describe images
M3
Image Generation Deep Dive
Diffusion models, latent space, and how images are generated from text
M4
Audio and Speech AI
Transcription, voice synthesis, and real-time audio understanding
M5
Video Understanding
How AI processes and generates video — current capabilities and limits
M6
Cross-Modal Reasoning
Tasks that require connecting information across different input types
M7
Building Multimodal Applications
Practical patterns for integrating multimodal models into products
M8
What's Coming in Multimodal AI
The next capabilities — and the hard problems still unsolved
Learn to run open-source and quantized models on your own hardware. From setup to inference, understand the practical reality of local AI — privacy, cost, and control.
Live8 Modules
Course modules
M1
Why Run Models Locally
Privacy, cost, latency, and the cases where local beats cloud
M2
The Open-Source Model Ecosystem
Llama, Mistral, Phi, and the landscape of locally-runnable models
M3
Hardware Requirements
What GPU, RAM, and storage you actually need for different model sizes
M4
Quantization Explained
How 4-bit and 8-bit quantization shrinks models without killing quality
M5
Setting Up Ollama
The fastest path from zero to running a local model
M6
LM Studio and llama.cpp
Alternative runtimes and when each makes sense
M7
Prompt Formatting for Local Models
Why chat templates matter and how to get consistent outputs
M8
Building Applications on Local Models
API compatibility, speed tuning, and practical production patterns
Demystify the technology behind ChatGPT, Claude, and Gemini. Understand transformers, training, and why these systems behave the way they do — without needing a PhD.
Live8 Modules
Course modules
M1
The Transformer Architecture
Attention mechanisms, tokens, and what's actually happening inside an LLM
M2
Pre-Training at Scale
How models learn from the internet — and what that means for their behavior
M3
Tokens, Context, and Memory
Why LLMs don't 'remember' and what context windows actually do
M4
Temperature and Sampling
How randomness is controlled to produce different output behaviors
M5
Emergent Capabilities
Why large models can do things small models can't — and the debate around why
M6
Fine-Tuning vs. Prompting
When you need to train and when a good prompt is enough
M7
Hallucination and Confabulation
Why models make things up and what can be done about it
M8
The Limits of Scale
What bigger models can't fix — and where the field is going
Go deep on diffusion models, LoRA, and the technology behind Midjourney, DALL·E, and Stable Diffusion. Learn to generate, control, and understand AI imagery.
Live8 Modules
Course modules
M1
How Diffusion Models Work
Noise, denoising, and the math behind image generation
M2
Text-to-Image Pipelines
How a prompt becomes an image — step by step
M3
The Role of CLIP and Vision Encoders
How models understand what text means visually
M4
Stable Diffusion Architecture
UNet, VAE, and the components that make open-source generation possible
M5
LoRA and Model Customization
How to train lightweight adapters for consistent styles and subjects
M6
ControlNet and Guided Generation
Depth maps, poses, edges — controlling generation with structure
M7
Prompt Engineering for Images
What actually works — syntax, weights, negative prompts, and style tokens
M8
Evaluating and Selecting Generated Images
How to assess quality, consistency, and fitness for use
Learn to read, run, and design AI evaluations. Understand what benchmarks actually measure, how to evaluate models for your specific use case, and where standard evals fall short.
Live8 Modules
Course modules
M1
Why Benchmarks Exist
The history and purpose of AI evaluation — from ImageNet to MMLU
M2
Reading Benchmark Scores
What leaderboards show, what they hide, and how to read them honestly
M3
Common Benchmarks Explained
MMLU, HumanEval, HellaSwag — what each tests and why it matters
M4
Benchmark Contamination
How training on test data distorts scores — and how to detect it
M5
Task-Specific Evaluation
Designing evals for your actual use case, not the general case
M6
Human Evaluation Methods
When to use humans and how to do it without introducing bias
M7
Building an Eval Pipeline
Automating evaluation across model versions and prompt changes
M8
The Limits of Evaluation
What no benchmark measures — and what that means for trust
Understand what AI alignment means, why it's hard, and why the field's best researchers consider it one of the most important problems in technology.
Live8 Modules
💬
AI Models · Course 9
Conversational AI and Chatbots
Understand how AI systems communicate with humans through text and speech. Learn principles for designing effective conversational interfaces and evaluate chatbot capabilities and limitations.
4 Modules
Course modules
M1
Machines That Speak Have Been Arriving for a Very Long Time
The history of human-machine conversation from ELIZA to ChatGPT
M2
Personality, Tone, and Voice
How AI systems develop distinct communication styles and why it matters
M3
From Spoken Word to Machine Understanding
Speech recognition, natural language processing, and intent detection
M4
Conversation Flow and Turn-Taking
How well-designed chatbots manage context, state, and dialogue structure
Explore the rapidly evolving world of real-time AI — voice interfaces, speech recognition, synthesis, and the systems powering always-on AI assistants.
Live8 Modules
Course modules
M1
The State of Voice AI
From Siri to GPT-4o voice — how the technology evolved
M2
Automatic Speech Recognition
How transcription works and why accuracy varies by speaker and context
M3
Text-to-Speech Synthesis
Neural TTS, voice cloning, and what makes voices sound natural
M4
Real-Time Conversation Models
How low-latency voice models handle interruption and turn-taking
M5
Voice Interfaces in Products
Design principles for conversational UX — what works and what doesn't
M6
Speaker Identification and Diarization
Who said what — identifying speakers in multi-party audio
M7
Emotional and Prosodic AI
How models are learning to interpret and express tone and emotion
M8
Where Voice AI Is Headed
Multimodal conversation, always-on assistants, and the ambient computing future
Understand the chip competition powering the AI era — GPUs, TPUs, custom silicon, and why hardware has become the defining constraint in AI development.
Live8 Modules
Course modules
M1
Why Hardware Determines AI Capability
The link between compute, model size, and what AI can do
M2
NVIDIA's Dominance
How CUDA lock-in and GPU architecture made NVIDIA the AI hardware king
M3
Google's TPU Strategy
Custom silicon, distributed training, and why Google built its own chips
M4
The New Entrants
AMD, Intel, Cerebras, Groq — challengers and what they're trying to do differently
M5
The Memory Bandwidth Bottleneck
Why moving data is often harder than computing it
M6
Inference vs. Training Hardware
Different workloads demand different silicon — what that means in practice
M7
The Export Control Dimension
How US chip restrictions are shaping the global AI race
M8
What Comes After GPUs
Neuromorphic chips, optical computing, and long-run hardware possibilities
Explore how AI systems use generated data to train themselves — and what that means for capability growth, quality control, and the future of AI development.
Live8 Modules
Course modules
M1
What Synthetic Data Is
Generated vs. real data — definitions, use cases, and tradeoffs
M2
Why Real Data Is Running Out
Token scarcity, copyright, and the limits of internet-scale training
M3
How Models Generate Training Data
Self-play, distillation, and prompting models to produce their own examples
M4
Quality Control for Synthetic Data
Filtering, verification, and avoiding model collapse
M5
Constitutional AI and Self-Critique
How Anthropic uses AI feedback to improve AI behavior
M6
Model Distillation
Training smaller models on larger model outputs — efficiency gains and limits
M7
The Recursive Improvement Question
Can AI improve itself indefinitely — and what are the risks?
M8
Where Synthetic Data Is Going
Current research frontiers and what the next generation of training looks like
Understand why context length matters, how it's grown from 2K to 1M+ tokens, and what expanding context windows make possible — and what problems they create.
Live8 Modules
Course modules
M1
What a Context Window Is
Tokens, attention, and why longer context is technically hard
M2
The History of Context Expansion
From GPT-3's 4K to Gemini's 1M — how context grew and why
M3
Attention Complexity
Why quadratic attention makes long contexts expensive to compute
M4
Efficient Attention Methods
Sliding window, sparse attention, and the architectures solving long context
M5
What You Can Do With Long Context
Full codebases, books, legal documents — real use cases unlocked
M6
Lost in the Middle
Why models don't use long context equally — attention distribution problems
M7
RAG vs. Long Context
When to retrieve and when to just put it all in the prompt
M8
Where Context Length Is Going
Theoretical limits, practical limits, and what the next generation enables
A living course tracking the AI frontier — emerging capabilities, upcoming model releases, and how to read the signals that matter in a fast-moving field.
Live8 Modules
🤖
AI Progress · Course 10
Autonomous AI Systems
Explore AI systems that operate independently in the physical world. Understand the technology behind self-driving cars, drones, and robots, including perception systems and decision-making algorithms.
4 Modules
Course modules
M1
Machines That Drive Themselves Are Already Driving
The current state of autonomous vehicles on public roads
M2
How Autonomous Drones Navigate
Sensor fusion, path planning, and obstacle avoidance in the air
M3
Failure Modes in Autonomous Systems
Why edge cases are so dangerous and how engineers try to address them
M4
Why Human Oversight Exists
The case for keeping humans in the loop and the design challenges it creates
The frontier of AI in games — fully generative worlds, AI companions, and what the next decade of game design looks like. Part three of three.
Coming Soon8 Modules
Course modules
M1
Fully Generative Game Worlds
What it means to generate everything — story, space, characters, and rules
M2
AI Companions and Relationship Systems
Long-term, memory-driven AI characters and what they demand
M3
Real-Time Neural Rendering
How AI is changing how game worlds look and perform
M4
The Economic Impact on Game Studios
Job changes, cost structures, and what AI means for indie vs. AAA
M5
Multiplayer and Competitive AI
Bots that play fairly, anti-cheat systems, and matchmaking AI
M6
AI-Generated Games at Runtime
The vision of games that write themselves as you play
M7
Player Rights and AI Content
Who owns AI-generated in-game content — emerging legal questions
M8
Designing for an AI-Native Future
Principles for game designers working with and against AI systems
In Development
🎬
Art · Course 4 of 14
AI Video Production
Learn how AI is transforming video creation — from script to screen. Explore generative video, AI editing tools, and the workflows reshaping filmmaking.
Coming Soon8 Modules
Course modules
M1
The AI Video Landscape
Text-to-video, image-to-video, and the tools reshaping production
M2
How Video Generation Models Work
Diffusion, temporal consistency, and the hard problem of motion
M3
Sora, Runway, and Kling
Comparing the leading generative video tools — capabilities and limits
M4
AI-Assisted Scriptwriting
Using LLMs for story development, dialogue, and script drafting
M5
AI in Editing and Post-Production
Automated cuts, upscaling, color grading, and VFX with AI
M6
Voice and Audio for AI Video
Synthesis, dubbing, sound design — the audio side of AI production
M7
Legal and Ethical Dimensions
Copyright, likeness rights, synthetic actors, and disclosure requirements
M8
Building an AI Video Workflow
Practical integration — what to use, when to use it, what to avoid
In Development
🏛️
Art · Course 6 of 14
AI and Architecture
Explore how AI is reshaping architectural design — from generative floor plans to parametric facades, structural optimization, and AI-assisted urban planning.
Live8 Modules
Course modules
M1
AI in the Design Process
Where AI fits in architectural workflow — ideation, documentation, analysis
M2
Generative Design Tools
Parametric AI tools architects are actually using — Midjourney, Stable Diffusion, Rhino AI
M3
Floor Plan and Space Generation
AI systems that generate functional layouts from programmatic constraints
M4
Structural Optimization
How AI finds efficient structural forms that humans wouldn't design
M5
Environmental Simulation
AI-driven energy modeling, daylight analysis, and climate-responsive design
M6
Urban Planning and City-Scale AI
Traffic modeling, zoning optimization, and AI in urban policy
M7
Computational Heritage and Preservation
Using AI to document, analyze, and restore historic buildings
M8
The Future of the Architect
How the profession is changing — and what AI can't replace in design
Dive into AI-powered music creation — from generative melody and harmony to full production. Learn the tools, the techniques, and the questions about creativity and authorship.
Coming Soon8 Modules
Course modules
M1
How AI Composes Music
The models and methods behind AI-generated melody, harmony, and rhythm
M2
Generative Music Tools
Suno, Udio, MusicGen — comparing the leading AI music platforms
M3
Prompt Engineering for Music
Describing what you want — genre, mood, instrumentation, and structure
M4
AI in Music Production
MIDI generation, stem separation, mastering assistance, and sample creation
M5
Training on Human Music
Copyright, consent, and the ethics of training on existing works
M6
Collaboration Between Human and AI
Workflows where AI augments rather than replaces the composer
M7
Generative Music for Games and Film
Adaptive soundtracks, procedural audio, and real-time composition
M8
Authorship and Ownership
Who owns AI music — current law, industry practice, and open questions
In Development
🖌️
Art · Course 8 of 14
AI for Graphic Design
Learn to use AI in professional graphic design workflows — logo generation, layout, typography, brand systems, and the tools reshaping visual communication.
Live8 Modules
Course modules
M1
AI's Place in the Design Workflow
Where AI helps, where it hurts, and what designers actually use it for
M2
Generative Image Tools for Designers
Firefly, Midjourney, DALL·E — comparing outputs for design use cases
M3
Logo and Brand Identity Generation
AI in brand exploration — speed, iteration, and the limits of generation
M4
Layout and Composition Assistance
AI tools for page layout, spacing, and visual hierarchy
M5
Typography and AI
Font recommendation, variable fonts, and AI-generated letterforms
M6
Brand Consistency with AI
Training models on brand assets and maintaining visual identity
M7
Presentation and Infographic Design
AI-powered slide design, data visualization, and document creation
M8
The Changing Design Profession
What AI changes about the designer's role — and what it doesn't
Explore how writers can work with AI without losing what makes their writing theirs. Covers voice preservation, AI-assisted drafting, editing, and the ethics of AI authorship.
Live8 Modules
Course modules
M1
What Voice Means in Writing
Defining the thing AI threatens to flatten — and how to protect it
M2
AI as Drafting Partner
Using LLMs for first drafts, brainstorming, and overcoming blocks
M3
Preserving Voice When Using AI
Prompting techniques that pull AI toward your style, not away from it
M4
AI-Assisted Editing
Grammar, clarity, flow — where AI editing helps and where it damages writing
M5
Research and Fact-Finding with AI
Using AI for research without inheriting its hallucinations
M6
Genre-Specific AI Writing
Fiction, nonfiction, poetry, journalism — how AI tools differ by form
M7
Disclosure and Authorship Ethics
When and how to disclose AI use — industry norms and personal ethics
M8
Developing Your AI-Augmented Practice
Building a writing workflow that uses AI without depending on it
Explore how AI is transforming photography — from intelligent cameras to AI editing, image upscaling, generative fill, and the ethics of synthetic photography.
Live8 Modules
Course modules
M1
AI in the Camera
Computational photography — how your phone already uses AI before you edit
M2
AI Photo Editing Tools
Lightroom AI, Luminar, Photoshop generative fill — what they actually do
M3
Image Upscaling and Restoration
Super-resolution, noise reduction, and restoring damaged photographs
M4
Generative Fill and Inpainting
Adding, removing, and replacing content in photographs with AI
M5
AI-Powered Photo Selection
Culling thousands of images — AI tools for editing down a shoot
M6
Style Transfer for Photography
Applying aesthetic styles to photographs — techniques and limits
M7
The Ethics of AI Photography
Disclosure, manipulation, deepfakes, and photojournalism standards
M8
The Future of the Photographer
What AI changes about the craft — and where human vision still leads
Discover how AI is entering theater, dance, and live performance — as a creative collaborator, a generative tool, and a disruptive force in the performing arts.
Live8 Modules
Course modules
M1
AI on Stage
Current uses of AI in theater and performance — and the debates they spark
M2
Generative Text for Theatre
LLMs in playwriting, dialogue generation, and dramaturgical research
M3
AI in Choreography
Motion capture, movement analysis, and AI-assisted dance creation
M4
Synthetic Actors and Digital Doubles
De-aging, resurrection, and virtual performers — where the industry stands
M5
Immersive and Interactive Performance
AI-driven audience interaction and responsive performance environments
M6
AI for Music and Sound in Live Performance
Real-time composition, adaptive scoring, and live AI instruments
M7
Accessibility and AI in Performance
Sign language interpretation, audio description, and real-time captioning
M8
The Human Question in Performing Arts
What live performance means when performers and writers can be simulated
Learn how investors evaluate AI companies, what makes an AI pitch compelling, and how to navigate the specific dynamics of raising for an AI-driven business.
Live8 Modules
Course modules
M1
The AI Investment Landscape
Where money is flowing, who's funding what, and why the AI bubble is different
M2
What Investors Look for in AI Companies
Defensibility, data moats, team, and the product-market fit question
M3
Crafting the AI Pitch Narrative
How to explain what your AI does without losing the room
M4
Technical Due Diligence Preparation
The questions sophisticated investors ask — and how to answer them
M5
Valuation in AI Businesses
Revenue multiples, ARR, and how investors value AI-native companies
M6
Competitive Differentiation
How to answer 'why won't OpenAI just do this?' convincingly
M7
Term Sheet Dynamics for AI Deals
IP ownership, data rights, and AI-specific terms to negotiate
M8
From Pitch to Close
Managing the fundraising process — timelines, updates, and decision-making
A strategic and operational guide to building a business where AI is central — not bolted on. Covers architecture, culture, competitive advantage, and execution.
Live8 Modules
Course modules
M1
What AI-First Actually Means
The difference between using AI tools and building AI into your business model
M2
Identifying AI-Native Opportunities
Finding problems where AI creates structural advantage, not just efficiency
M3
Data Strategy and Moats
Building proprietary data assets that compound your AI advantage
M4
The AI-First Tech Stack
Infrastructure decisions — models, infrastructure, and build vs. buy tradeoffs
M5
Team and Culture for AI-First Orgs
Hiring, roles, and the cultural norms that make AI-first work
M6
Speed as a Strategic Asset
How AI-first businesses move faster — and how incumbents respond
M7
Ethical and Governance Foundations
Building responsibility into the architecture before you need it
M8
Scaling an AI-First Business
What breaks at scale — and how to build systems that hold
Learn how AI is transforming financial analysis, forecasting, and operational management — and how finance and ops leaders can use these tools effectively.
Coming Soon8 Modules
Course modules
M1
AI in Financial Analysis
Automating reports, identifying patterns, and AI-assisted financial modeling
M2
Forecasting and Scenario Planning
AI tools for revenue forecasting, demand planning, and risk modeling
M3
Accounts Payable and Receivable Automation
Document processing, matching, and exception handling with AI
M4
AI in Supply Chain and Logistics
Demand sensing, inventory optimization, and routing intelligence
M5
Expense Management and Fraud Detection
AI systems for identifying anomalies and controlling spend
M6
AI in HR Operations
Recruiting, workforce planning, and employee experience with AI
M7
Operational Dashboards and AI Reporting
Building executive-level AI-powered reporting systems
M8
Risk and Compliance in AI Finance Systems
Audit trails, explainability, and regulatory considerations
Explore how AI is transforming customer support — from chatbots to intelligent routing, agent assistance, and the future of human-AI service teams.
Coming Soon8 Modules
Course modules
M1
The State of AI Customer Service
What's deployed, what customers think, and where the bar is today
M2
Chatbot Architecture and Design
Intent recognition, dialog management, and building bots that don't frustrate
M3
LLM-Powered Support Agents
Moving beyond scripted bots to generative AI in customer-facing roles
M4
Agent Assist Tools
Real-time AI assistance for human agents — how it improves speed and quality
M5
Intelligent Ticket Routing
Classification, prioritization, and AI-driven support workflow
M6
Voice AI in Customer Service
IVR evolution, voice bots, and real-time transcription for support
M7
Measuring AI Customer Service Performance
CSAT, resolution rate, and the metrics that matter for AI-powered support
M8
The Human-AI Support Team Model
Designing the blend — when to hand off, escalate, and intervene
In Development
🏢
Business · Course 11 of 9
AI for Small Business Managers
A hands-on course for managers running teams of 5–50. Learn to introduce AI into daily operations, make smarter decisions with data, and lead your team through adoption — without needing a technical background.
Live8 Modules
💼
Business · Course 12
AI's Impact on Jobs
Examine how AI automation affects different industries and job roles. Learn strategies for adapting to technological change and developing AI-resilient skills.
Live4 Modules
⚡
Business · Course 13
AI, Work, and Your Career
This course moves beyond fear and hype to give workers, students, and managers a realistic picture of how automation affects careers, industries, and daily work.
Live8 Modules
Course modules
M1
Every Generation Believes Its Machine Is Different
Historical context for understanding the current automation wave
M2
White-Collar Work Under Pressure
How knowledge work is changing as AI handles cognitive tasks
M3
Why Will AI Take My Job Is the Wrong Question
The right framework for thinking about automation and your career
M4
The Human Skills That AI Cannot Replicate
Judgment, relationship, and creative skills that remain irreplaceable
M5
The Augmentation Paradigm
Using AI to extend your capabilities rather than be replaced by it
M6
Trade Adjustment Assistance and Its Limits
What policy support exists and where the gaps are
M7
Mapping Your AI-Resilience Profile
A practical framework for assessing your own career exposure and options
M8
Unions in the Age of Algorithms
How labor organizing is adapting to algorithmic management and automation
Survey the landscape of AI agent use cases — understand when agents add value, what architectures they use, and how to evaluate whether agency is the right solution.
Live8 Modules
Course modules
M1
What Is an AI Agent
Agents vs. tools vs. assistants — precise definitions and why they matter
M2
The Agent Loop
Perception, reasoning, action, observation — the core cycle of agent operation
M3
Survey of Agent Use Cases
Research, coding, customer service, data analysis — mapping the landscape
M4
When Agency Adds Value
The decision framework for whether an agent is actually the right solution
M5
Agent Architectures Overview
ReAct, Plan-and-Execute, and other patterns — a comparative map
M6
Multi-Agent Systems Introduction
Orchestrators, sub-agents, and the cases that require multiple agents
M7
Evaluating Agent Performance
Task completion, cost, reliability — how to measure agent quality
M8
Risks and Failure Modes
What goes wrong with agents — and the categories of failure to design against
Equip your agents with memory, knowledge, and reasoning capabilities. Learn how agents store context, access information, and plan across multi-step tasks.
Live8 Modules
Course modules
M1
Memory Types for Agents
Short-term, episodic, semantic, and procedural memory — what each does
M2
Implementing Working Memory
Context management, summarization, and keeping agents on track
M3
Long-Term Memory with Vector Databases
Embeddings, retrieval, and giving agents persistent knowledge
M4
Knowledge Graphs for Agents
Structured knowledge and when graphs outperform vector search
M5
Agent Planning Strategies
Task decomposition, subgoal generation, and backtracking
M6
Reasoning Under Uncertainty
How agents handle ambiguity, missing information, and conflicting signals
M7
Skill Libraries and Agent Capabilities
Building reusable skill modules that agents can compose
M8
Benchmarking Agent Cognition
How to measure reasoning and planning quality — practical eval methods
Give your agents real capabilities through tool use — web browsing, code execution, API calls, and MCP integration. Build agents that act in the real world.
Live8 Modules
Course modules
M1
Tool Use Fundamentals
Function calling, tool schemas, and how agents decide which tool to use
M2
Web Search and Browsing Tools
Search APIs, browser automation, and web-capable agent design
M3
Code Execution Environments
Sandboxed code runners — security, capabilities, and integration patterns
M4
File System and Document Tools
Reading, writing, and manipulating files safely within an agent
M5
API Integration Patterns
Connecting agents to third-party services — auth, rate limits, and error handling
M6
MCP Integration
Model Context Protocol — architecture, setup, and building MCP-compatible agents
M7
Tool Selection and Orchestration
How to design tool selection logic that doesn't get expensive or stuck
M8
Security and Safety for Tool-Using Agents
Injection attacks, privilege limits, and safe tool design
Build and deploy OpenClaw — a production-grade AI agent framework. Full implementation, testing, and real-world deployment patterns from architecture to launch.
Live8 Modules
Course modules
M1
OpenClaw Architecture Overview
Design decisions, component structure, and the philosophy behind the framework
M2
Core Agent Loop Implementation
Building the perception-reasoning-action cycle from scratch
M3
Tool Registry and Plugin System
Dynamic tool loading, schema validation, and plugin architecture
M4
Memory System Implementation
In-memory and persistent memory — the OpenClaw approach
M5
Orchestration and Sub-Agent Management
How OpenClaw handles multi-agent coordination
M6
Observability and Logging
Tracing agent runs, debugging failures, and monitoring in production
M7
Testing Your Agent System
Unit tests, integration tests, and end-to-end agent evaluation
M8
Deploying OpenClaw to Production
Containerization, scaling, and operating an agent system in the real world
Design production-grade AI applications. Learn the architectural patterns, infrastructure decisions, and system design principles that make AI apps reliable and scalable.
Coming Soon8 Modules
Course modules
M1
AI Application Architecture Patterns
Gateway, pipeline, mesh — the major patterns for AI app structure
M2
Model Routing and Selection
Dynamic model selection — routing by task, cost, and quality requirements
M3
Latency Management
Streaming, async patterns, and designing for perceived vs. actual response time
M4
Caching Strategies for AI
Semantic caching, prompt caching, and when caching helps vs. hurts
M5
Context Management at Scale
Handling long contexts, conversation history, and multi-user state
M6
Multi-Model Pipelines
Chaining models — when to split tasks and how to manage handoffs
M7
Infrastructure and Deployment
Containerization, orchestration, and scaling AI workloads
M8
Reliability and Fallback Design
Graceful degradation, fallback models, and building systems that hold
Master prompt engineering as a technical discipline — system prompts, few-shot examples, chain-of-thought, structured outputs, and the full toolkit for production AI.
Live8 Modules
Course modules
M1
Prompt Engineering as Engineering
Treating prompts as code — version control, testing, and iteration
M2
System Prompt Design
Persona, constraints, output format — the anatomy of a good system prompt
M3
Few-Shot Examples
When to use examples, how many, and how to select the right ones
M4
Chain-of-Thought Techniques
Getting models to reason step by step — and when it helps
M5
Structured Output Prompting
JSON, XML, and format enforcement — reliable structured generation
M6
Prompt Injection Defense
How injection attacks work and how to design prompts that resist them
M7
Evaluating and Testing Prompts
Building test suites for prompts — coverage, regression, and red-teaming
M8
Prompt Management in Production
Storage, versioning, A/B testing, and prompt deployment workflows
Learn to operate AI systems in production — observability, logging, alerting, cost tracking, and the practices that keep models performing after launch.
Live8 Modules
Course modules
M1
AI Observability Fundamentals
What to measure in an AI system and why standard APM isn't enough
M2
Logging for AI Applications
What to log, at what granularity, and how to do it without killing performance
M3
Tracing LLM Calls
End-to-end tracing from user request to model response — tools and patterns
M4
Monitoring Model Quality Over Time
Drift detection, output quality monitoring, and knowing when to retrain
M5
Alerting and Anomaly Detection
Setting up alerts that catch real problems without alert fatigue
M6
Cost Monitoring and Budgeting
Tracking token spend, setting limits, and building cost dashboards
M7
Incident Response for AI Systems
On-call runbooks, postmortems, and recovering from AI outages
M8
Continuous Evaluation in Production
Running evals continuously — not just at deployment
Build retrieval-augmented generation systems from the ground up — embeddings, vector databases, chunking strategies, hybrid search, and production RAG architecture.
Live8 Modules
Course modules
M1
Why RAG Exists
The problem RAG solves — grounding, currency, and context limits
M2
Embeddings Deep Dive
How text becomes vectors — models, dimensions, and similarity search
M3
Chunking Strategies
Fixed-size, semantic, and recursive chunking — what works for different content
M4
Vector Databases
Pinecone, Weaviate, Chroma, pgvector — comparing the options and tradeoffs
M5
Hybrid Search
Combining dense and sparse retrieval for better coverage and precision
M6
Retrieval Quality and Evaluation
Measuring retrieval — recall, precision, and end-to-end quality
M7
RAG Pipeline Design
Query rewriting, re-ranking, and the full retrieval-to-generation pipeline
M8
Production RAG Architecture
Scale, latency, cost, and operating a RAG system in production
Build production applications on Claude — Messages API, tool use, vision, streaming, and the patterns that make Anthropic API integration reliable and efficient.
Live8 Modules
Course modules
M1
The Messages API
Request structure, roles, content types, and the basics of the API
M2
System Prompts and Context
How to structure system prompts and manage conversation context at scale
M3
Tool Use and Function Calling
Defining tools, handling tool calls, and building reliable tool-use workflows
M4
Vision and Document Input
Passing images and documents to Claude — formats, limits, and use cases
M5
Streaming Responses
Server-sent events, incremental processing, and streaming UX patterns
M6
Rate Limits and Error Handling
Understanding limits, implementing retries, and building resilient clients
M7
Cost Optimization
Prompt caching, token efficiency, and controlling spend on Claude
M8
Production Patterns
Batching, async processing, and architectural patterns for Claude at scale
Learn when and how to fine-tune — LoRA, QLoRA, instruction tuning, and dataset preparation. Understand the tradeoffs between fine-tuning and prompting.
Coming Soon8 Modules
Course modules
M1
When Fine-Tuning Beats Prompting
The cases where training beats prompting — and the ones where it doesn't
M2
Full Fine-Tuning vs. PEFT
The spectrum from full retraining to lightweight adapters — tradeoffs explained
M3
LoRA Deep Dive
Low-rank adaptation — the math, the intuition, and the practical parameters
M4
QLoRA and Memory Efficiency
4-bit quantization plus LoRA — fine-tuning large models on consumer hardware
M5
Dataset Preparation
Collecting, cleaning, and formatting training data for instruction fine-tuning
M6
Training Configuration
Learning rates, batch size, epochs, and the knobs that matter most
M7
Evaluation and Avoiding Catastrophic Forgetting
Measuring fine-tuned model quality and preserving base capabilities
M8
Deploying Fine-Tuned Models
Serving your model — inference infrastructure and integration patterns
In Development
🔒
Development · Course 13 of 20
AI Security and Red-Teaming
Learn to build AI systems that hold up under adversarial pressure — prompt injection, jailbreaks, data leakage, and the security practices that matter for production AI.
Live8 Modules
Course modules
M1
The AI Security Threat Model
Mapping the attack surface — what adversaries want and how they get it
M2
Prompt Injection Attacks
Direct and indirect injection — how they work and defense strategies
M3
Jailbreaking and Policy Bypass
Techniques for bypassing safety training and how to harden against them
M4
Data Exfiltration via LLMs
How attackers extract sensitive data through AI systems — and how to prevent it
M5
Model Inversion and Extraction
Reconstructing training data or model weights — attack and defense
M6
RAG System Security
Poisoning retrieval, manipulating context, and securing the knowledge pipeline
M7
Red-Teaming Methodology
How to structure an AI red-team exercise — scope, techniques, and reporting
M8
Building a Secure AI System
Defense in depth — layered security for production AI applications
Learn to read, understand, and validate AI-generated code. Spot hallucinated APIs, phantom dependencies, logic errors, and silent failures before they reach production.
Live8 Modules
Course modules
M1
Why AI Code Needs a Different Review Process
How AI-generated code fails differently than human-written code
M2
Reading AI Output Like an Expert
Patterns, tells, and what to look for first when reviewing AI code
M3
Hallucinated APIs and Phantom Dependencies
Finding functions and libraries that don't exist or behave differently than assumed
M4
Logic Errors and Silent Failures
Code that compiles and runs but does the wrong thing
M5
Type Safety and Data Flow Analysis
Tracing data through AI-generated code to catch type mismatches and bad assumptions
M6
Documentation and Assumption Auditing
Identifying undocumented assumptions baked into AI-generated logic
M7
Testing AI-Generated Code
Writing tests that catch the specific failure modes AI code introduces
M8
Building a Personal Review Checklist
Creating a repeatable process you can apply to any AI-generated codebase
Find the vulnerabilities AI code introduces — injection flaws, authentication gaps, insecure data handling, and supply chain risks. Learn to catch them before they ship.
Live8 Modules
Course modules
M1
Why AI Gets Security Wrong
The specific ways AI models reproduce and introduce security vulnerabilities
M2
Injection Vulnerabilities in AI Code
SQL, command, and prompt injection patterns that AI models commonly miss
M3
Authentication and Authorization Gaps
How AI-generated auth logic fails and how to spot it
M4
Insecure Data Handling and Secrets
Logging, storage, and transmission mistakes AI code makes with sensitive data
M5
Dependency and Supply Chain Risks
Evaluating the packages and versions AI recommends before you install them
M6
Input Validation and Output Encoding
The missing checks AI code almost always skips
M7
Cryptography Mistakes
Identifying weak algorithms, bad key management, and broken implementations in AI output
M8
Security Review Workflows and Tooling
Static analysis, SAST tools, and how to integrate security review into your AI dev process
Build systematic review processes for AI-assisted development teams. Set quality gates, define acceptance criteria, and maintain code standards at scale.
Live8 Modules
Course modules
M1
Designing a Team AI Code Review Process
What a structured review workflow looks like when AI is generating most of the code
M2
Quality Gates and Acceptance Criteria
Defining what good enough means for AI-generated code in your context
M3
Automated Linting and Static Analysis
Tools and configurations that catch AI code issues before human review
M4
Code Review Metrics and Tracking
Measuring review quality and catching patterns in recurring AI mistakes
M5
Onboarding Reviewers to AI Code
Training team members to review AI output with the right skepticism and speed
M6
When AI and Human Disagree
How to handle conflicts between AI-generated code and reviewer judgment
M7
Building a Review Knowledge Base
Documenting patterns, anti-patterns, and decisions so the team learns over time
M8
Scaling Audit Practices Across Teams
How review standards evolve as more of the org adopts AI-assisted development
Build real agents on Google's Gemini Enterprise Agent Platform from scratch. Hands-on work with Agent Designer, Skills, function calling, multi-turn conversations, and the Agent2Agent protocol — everything you need to deploy an agent that does something useful.
Live8 Modules
Course modules
M1
The Vertex AI Agent Platform — Architecture and Setup
GCP project setup, enabling Vertex AI, understanding Agent Designer, Model Garden, and the platform structure
M2
Your First Gemini Agent — Authentication and First API Call
Service accounts, API keys, the Gemini SDK, and making your first programmatic agent call
M3
Defining Agent Behavior — System Prompts, Skills, and Instructions
Writing effective system prompts, creating Skills in Agent Designer, controlling what your agent does and doesn't do
M4
Giving Agents Tools — Function Calling and External APIs
Defining tool schemas, connecting agents to real APIs, handling function call results and errors
M5
Managing Context — Sessions, Memory, and Long-Running Agents
The model isn't the bottleneck — your data is. Learn to connect Vertex AI agents to BigQuery, Cloud Storage, Knowledge Catalog, and cross-cloud data sources. Build agents that can read your warehouse, answer from your documents, and act on real enterprise data.
🌐
AI & Climate
The same technology that's straining the grid may also be the best tool we have for understanding what to do about it.
💡
Don't Get Fooled: AI and Lies
Understanding the long history of fabricated reality — and why this moment is genuinely different.
🔬
Understanding AI Bias and Fairness
Algorithms already shape who gets hired, who gets a loan, and who gets flagged as a threat — this course asks whether they do so fairly.
📊
AI Ethics & Decision-Making
Ethics used to be a subject studied in universities. AI made it a subject debated in procurement meetings.
🎯
AI Governance
Every consequential technology has eventually faced its governance reckoning. AI is facing it now.
⚙️
AI in Society
AI has quietly become a layer of public life. This course makes the invisible visible.
🔭
Building Production Agents with Vertex AI
Why orchestrated AI agents on managed cloud infrastructure represent a genuine architectural break — not an incremental upgrade.
🖥️
Building with AI
For three decades we built software by typing. That changed. This course is about building on the other side of the change.
🤝
Coded Unfair: AI Bias Exposed
Every powerful technology arrives promising neutrality — and delivers the prejudices of its makers.
🎨
How Large Language Models Work
LLMs look like magic until you see the mechanics. Then they become something you can use with judgment.
💼
Make It Yours: Create With AI
Why this course exists — and what you'll actually be able to do when it's done.
🛡️
The Context Window Race
Why the size of what an AI can hold in mind at once matters more than almost anything else about it
🧠
The Future of Intelligence
A course about reading where machine intelligence is going — and why the trajectory matters more than today's headlines.
⚡
Agentic Data Workflows on Google Cloud
Every powerful AI agent is only as useful as the data it can reach — this course is about closing that gap on Google Cloud.
🔮
What's Really Inside AI?
This course exists because almost everyone using AI has no idea what it actually does.
🎨
Make Something Real with AI
This course exists because the question isn't whether AI belongs in your creative process — it's how to use it without losing what makes the work yours.
🛡️
Say It Right: Talk to AI
Every transformative tool arrives with a learning curve nobody warned you about
Live6 Modules
Course modules
M1
The Magic Words That Aren't Magic
What a prompt actually is, and why "just ask it" is incomplete advice
M2
Module 2
M3
Why AI Gives the Wrong Answer
Understanding what actually goes wrong — and why it's rarely the AI's fault alone
M4
The Persona Prompt
Telling AI who to be before asking it what to do
M5
Helpful Prompts: What Actually Works
Why clear, honest requests unlock AI's real power — and vague ones waste it.
M6
Putting It All Together
Everything you have learned about prompts — role, context, format, iteration — converges into one skill: writing prompts that consistently produce excellent results.
Learn how AI systems can perpetuate unfair biases and discrimination in hiring, lending, healthcare, and criminal justice. Develop skills to recognize biased AI outputs and understand approaches for creating more equitable artificial intelligence.
Explore how AI systems collect, process, and potentially misuse personal information in our digital lives. Master practical strategies to protect your privacy while understanding emerging laws and regulations governing AI development.
Coming Soon4 Modules
Proposed modules
M1
How AI Uses Personal Data
M2
Privacy Risks and Threats
M3
Protecting Your Digital Footprint
M4
AI Governance and Regulation
In Development
🌐
AIP Draft
AI's Impact on Future Work
Discover which jobs AI will automate, augment, or create in the coming decades across different industries. Learn essential skills and strategies to thrive in an AI-enhanced workplace and adapt your career for the future.
Artificial intelligence is changing who creates the news, how stories are told, and which audiences receive which information — raising urgent questions about truth, trust, and editorial accountability. This course unpacks the AI systems behind modern media production and gives learners the tools to critically evaluate the news they consume.
Coming Soon8 Modules
Proposed modules
M1
Automated Reporting: Bots Writing News
M2
AI Tools in Modern Newsrooms
M3
Personalization Algorithms and News Bubbles
M4
Synthetic Media and Editorial Responsibility
M5
Fact-Checking at Machine Speed
M6
Audience Manipulation and Influence Campaigns
M7
Ethics of AI-Assisted Journalism
M8
Designing Trustworthy AI-Powered Media
In Development
🌐
AIP Draft
AI Superpowers for Small Business
Small business owners often assume AI is only for big corporations with big budgets — this course proves otherwise. From chatbots to content creation, learners will discover practical, affordable AI tools and how to integrate them into daily operations.
Coming Soon8 Modules
Proposed modules
M1
AI Tools Any Business Can Afford
M2
Automating Customer Service With AI
M3
Smarter Marketing Using AI Insights
M4
Inventory and Operations Made Easier
M5
Writing and Content With AI Assistance
M6
Protecting Your Business Data
M7
Choosing and Evaluating AI Vendors
M8
Building an AI-Ready Business Culture
In Development
💡
AIP Draft
AI and Misinformation
Understand how AI can create and spread misinformation at scale. Develop skills to identify false content and verify information authenticity.
From unlocking your phone with your face to helping doctors spot tumors, computer vision is quietly embedded in dozens of everyday technologies most people never think twice about. This course demystifies how machines interpret images and video, and what that means for your privacy, safety, and rights.
AI isn't going to replace your creativity â but creators who know how to work with it are producing more, faster, and on their own terms. This course teaches you how to use AI as a genuine collaborator on your actual projects without losing what makes your work yours.
You're competing against hundreds of applicants â many of whom are already using AI to get ahead. This course teaches you exactly how to use AI tools at every stage of your job search so you stand out, not just keep up.
The AI side hustle space is full of hype â but buried in that hype are real opportunities that people your age are already monetizing. This course cuts through the noise and shows you which approaches actually generate income, and how to start one this week.
College is expensive, exhausting, and competitive â AI won't do the work for you, but it can make the work you do dramatically more effective. This course shows you the specific tools and techniques that actually help with real coursework, not hypothetical scenarios.
You've grown up online, which means AI systems have been learning from you â your clicks, your searches, your posts â for years. This course shows you what's actually been collected, how it's used to influence you, and what you can do about it.
Explore how AI creates art, music, and literature alongside human artists. Examine the changing relationship between technology and human creativity.
Coming Soon4 Modules
Proposed modules
M1
AI-Generated Art and Music
M2
Creative Collaboration with AI
M3
Intellectual Property Questions
M4
Future of Human Creativity
In Development
🛡️
AIP Draft
Is This AI Fair to You?
AI systems make consequential decisions about loans, jobs, healthcare, and news every single day — but who is ensuring those decisions are fair? This beginner-friendly course gives you the practical vocabulary and critical thinking tools to question, evaluate, and advocate around AI ethics in your daily life.
Coming Soon8 Modules
Proposed modules
M1
What Ethics Actually Means for AI
M2
Who Decides What AI Values?
M3
Fairness: Easy Word, Hard Problem
M4
Transparency and the Right to Know
M5
Accountability When AI Causes Harm
M6
Privacy as a Human Right
M7
Ethics in Action: Real Case Studies
M8
Becoming an Ethical AI Citizen
In Development
🚀
AIP Draft
Teaching AI to Want Good Things
AI safety and alignment asks one of the most important questions of our time: how do we build powerful AI systems that reliably pursue goals humans actually care about? This course demystifies the technical and philosophical challenges of alignment for a general audience, explaining real risks and real solutions without requiring a computer science degree.
Small business owners do not need a tech team to start benefiting from AI — they just need the right roadmap. This hands-on course walks entrepreneurs through the most practical, affordable AI tools available today, with real examples from retail, hospitality, services, and more.
Explore how artificial intelligence is transforming hospitals, clinics, and medical research — from diagnosing cancer to accelerating drug development. This course explains complex medical AI applications in plain language, empowering patients, caregivers, and healthcare workers alike.
Coming Soon8 Modules
Proposed modules
M1
Why Healthcare Needs AI Now
M2
AI That Reads Medical Images
M3
Predicting Disease Before It Starts
M4
AI in Drug Discovery and Research
M5
Electronic Records and Intelligent Assistants
M6
Bias and Equity in Medical AI
M7
Patient Privacy and Data Rights
M8
The Future Doctor-AI Partnership
In Development
⚡
AIP Draft
AI, Automation, and Your Career
This course moves beyond headlines to give learners a clear-eyed, evidence-based look at which jobs AI is realistically automating, which it is augmenting, and what workers and policymakers can do about it. Whether you are a student, a professional, or a lifelong learner, you will leave with a practical framework for navigating the changing world of work.
Modern penetration testers use LLMs and AI tooling to accelerate reconnaissance — OSINT, attack-surface mapping, target enumeration — without losing analyst judgment. This course teaches the workflow end-to-end with hands-on labs.
Modern network and infrastructure pentesting workflows that use AI for service identification, attack-path analysis, and lateral-movement planning across on-prem and hybrid environments.
Live8 Modules
Proposed modules
M1
Network Pentesting Foundations Refresher
M2
AI-Assisted Service Identification
M3
Vulnerability Mapping at Scale
M4
Active Directory Attack Paths
M5
Lateral Movement and Persistence Planning
M6
Cloud and Hybrid Pivots
M7
Detection Engineering Feedback
M8
Network Pentest Reporting and Remediation Tracking
How AI changes the modern web-application pentest workflow — from automated discovery to assisted exploit crafting — without producing slop reports. Includes burn-down labs against intentionally vulnerable apps.
Coming Soon8 Modules
Proposed modules
M1
AI in the Web Pentest Workflow
M2
LLM-Assisted Spidering and Discovery
M3
Auth and Session Attacks with AI
M4
Injection Classes Revisited
M5
Logic Flaws and Business-Workflow Abuse
M6
API and GraphQL Surface Coverage
M7
Triage, False Positives, and Re-Verification
M8
Web Pentest Reporting in the AI Era
In Development
🎯
AIP Draft
Pen Testing AI Agents and Tool Use
Agentic AI systems — autonomous LLMs with tool access, memory, and goals — present a new attack surface that classic pentests do not cover. Learn how to scope, run, and report tests against real agent stacks.
Live8 Modules
Proposed modules
M1
Agent Architecture for Pentesters
M2
Goal Hijacking and Misaligned Tool Use
M3
Tool-Surface Attacks
M4
Memory Poisoning and Long-Horizon Manipulation
M5
Multi-Agent and Inter-Agent Attacks
M6
Sandbox Escape and Resource Abuse
M7
Test Plans and Evidence Collection for Agent Pentests
Hands-on penetration testing of LLM-powered applications — chatbots, RAG pipelines, agents, and plugins — using the OWASP LLM Top 10 as the playbook. Build a complete test plan and produce findings that engineering teams can act on.
Deploying AI agents without a structured risk and oversight model is how organizations create expensive, embarrassing, or dangerous failures â often without seeing them coming. This course equips managers, architects, and domain experts with the frameworks to evaluate agent risk, design meaningful oversight checkpoints, and build accountable AI systems.
Live8 Modules
Proposed modules
M1
The Failure Landscape: How Autonomous Agents Go Wrong
M2
Prompt Injection, Goal Misgeneralization, and Emergent Behavior
M3
Designing Human-in-the-Loop Controls for Agentic Systems
M4
Monitoring, Logging, and Detecting Drift in Production Agents
M5
Liability, Accountability, and Organizational Governance
M6
Risk Frameworks: Evaluating Agents Before Deployment
M7
Case Studies: High-Profile Agent Failures and What They Cost
M8
Apply It: Conduct a Risk Audit of an Agent in Your Organization
AI coding assistants are reshaping what software teams can ship and how they work â but adoption without strategy creates technical debt, security exposure, and uneven productivity gains. This course equips engineering managers and senior developers to evaluate, deploy, and govern AI coding tools as a deliberate team capability rather than an individual perk.
Coming Soon8 Modules
Proposed modules
M1
The AI-Augmented Developer: Productivity Realities Beyond the Hype
M2
Tool Landscape: Copilot, Cursor, Codeium, and the Category Map
M3
Integrating AI Tools into Existing Engineering Workflows and CI/CD Pipelines
M4
Code Review, Quality, and the Problem of Plausible-But-Wrong Suggestions
M5
Security Implications: Training Data, IP Exposure, and Autocompleted Vulnerabilities
M6
Team Adoption Strategies: Rollout, Measurement, and Managing Skepticism
M7
AI-Assisted Testing, Documentation, and Legacy Code Modernization
M8
Leading an AI-Augmented Engineering Team: Norms, Metrics, and the Evolving Role of the Developer
In Development
🔬
Professional
Automate AI Workflows with n8n
n8n gives professionals a visual, code-optional environment to wire AI models into real business workflows â without surrendering control to opaque SaaS products. This course teaches you to design robust, production-grade automation pipelines that combine LLMs with the systems your organization already uses.
Coming Soon8 Modules
Proposed modules
M1
n8n's Execution Model: Nodes, Triggers, and Data Flow Fundamentals
M2
Integrating LLMs: Connecting OpenAI, Anthropic, and Local Models to Workflows
M3
Building Intelligent Pipelines: Conditional Logic, Branching, and Error Handling
M4
Working with External Data: APIs, Databases, Webhooks, and File Ingestion
M5
Automating Real Work: Email Triage, Report Generation, and Document Processing
M6
Human-in-the-Loop Design: When and How to Insert Approval Steps
M7
Apply It: Map and Automate a Repetitive Workflow from Your Own Role
M8
Self-Hosting, Security Considerations, and Scaling n8n in an Organization
In Development
🌐
Professional
Building Multi-Agent Teams with CrewAI
Multi-agent frameworks let professionals decompose complex, multi-step problems into coordinated AI workflows that no single model can handle alone. This course teaches you to design, build, and deploy CrewAI-powered agent teams â from role architecture to production-grade orchestration.
Coming Soon8 Modules
Proposed modules
M1
Why Multi-Agent Systems Outperform Single Agents
M2
CrewAI Architecture: Agents, Tasks, and Crews
M3
Designing Agent Roles and Delegation Hierarchies
M4
Connecting Tools, APIs, and External Data Sources
M5
Orchestration Patterns for Complex Workflows
M6
Testing, Debugging, and Observing Agent Behavior
M7
Apply It: Build a Crew for Your Own Use Case
M8
Scaling, Cost Control, and Production Readiness
In Development
⚡
Professional
Cloud AI Services for Working Professionals
AWS, Azure, and GCP each offer mature but divergent AI service ecosystems â and professionals making platform decisions without a comparative framework are routinely locked into suboptimal choices. This course gives technical leads, architects, and decision-makers an honest, side-by-side analysis of capabilities, tradeoffs, and strategic considerations across all three major cloud AI platforms.
Coming Soon8 Modules
Proposed modules
M1
The Cloud AI Landscape: How AWS, Azure, and GCP Have Divided the Market
M2
Core Managed AI Services: Vision, Language, Speech, and Prediction APIs
M3
Foundation Model Access and Fine-Tuning on Each Platform
M4
MLOps Pipelines: SageMaker, Azure ML, and Vertex AI Compared
M5
Cost Modeling, Vendor Lock-In, and Multi-Cloud AI Strategy
M6
Security, Compliance, and Data Residency for Enterprise AI Workloads
M7
Selecting the Right Platform for Your Use Case: A Decision Framework
M8
Architecting a Cloud AI Solution for a Professional Scenario
In Development
🔮
Professional
Claude at Work: Professional Mastery
Claude is built around a distinct set of values and reasoning behaviors that make it exceptionally capable for professional knowledge work â if you know how to work with it. This focused course moves you from casual user to power practitioner, covering Claude's unique strengths, its principled limitations, and the workflows where it delivers the highest return.
Coming Soon5 Modules
Proposed modules
M1
What Makes Claude Different: Strengths, Limits, and Design Philosophy
M2
Prompt Engineering for Claude's Reasoning Style
M3
High-Stakes Use Cases: Analysis, Drafting, and Decision Support
M4
Working Within Claude's Values and Safety Guardrails
M5
Advanced Features, API Access, and Workflow Integration
In Development
📊
Professional
Perplexity AI for Professional Research
Perplexity AI sits at the intersection of search and language generation â and knowing how to use it deliberately separates professionals who get actionable intelligence from those who get plausible-sounding noise. This focused course teaches working professionals how to query effectively, assess citations critically, and embed Perplexity into research workflows without sacrificing accuracy for speed.
Coming Soon5 Modules
Proposed modules
M1
What Perplexity Actually Does: Search, Synthesis, and Where It Differs from Google
M2
Prompt Strategies That Get Research-Grade Answers, Not Summaries
M3
Evaluating Source Quality and Spotting Hallucination in Cited Responses
M4
Integrating Perplexity into Daily Professional Research Workflows
M5
When Not to Use Perplexity: Knowing the Tool's Hard Limits
In Development
📊
Young Adult · Ages 17-25
Launch Your AI Side Project
You've got an idea and a handful of AI tools â but most side projects stall before they get anywhere real. This course teaches you a lightweight agile workflow designed specifically for solo builders and small teams using AI, so you can stop planning and start shipping.
LiveAges 17-258 Modules
Proposed modules
M1
Why Most Side Projects Die and How Agile Fixes That
M2
Scoping Your Idea: Using AI to Go from Vague to Viable
M3
Sprint Cycles for Solo Builders: Ship in Weeks, Not Months
M4
AI Tools for Every Stage: Research, Build, Test, Repeat
M5
Handling Scope Creep When AI Makes Everything Feel Possible
M6
Getting Real Feedback Fast: Users, Iteration, and Pivots
M7
Turning a Side Project into a Portfolio Piece or Income Stream
M8
Your First Sprint: Plan and Launch Something in 30 Days
AI agents are being handed more and more real-world tasks â browsing the web, sending emails, managing files â and most people using them have no idea what happens when they go wrong. This course gives you the mental models and practical instincts to use agents confidently without getting burned.
LiveAges 17-258 Modules
Proposed modules
M1
What AI Agents Actually Are and Why Everyone's Building Them
M2
Failure Modes: How Agents Go Off the Rails
M3
Real Incidents: Cases Where AI Agents Caused Real Harm
M4
The Control Problem: How Humans Stay in the Loop
M5
Evaluating an Agent Before You Trust It With Anything
AI has made online scams, impersonation, and data harvesting dramatically more sophisticated â and most of the advice you've heard is already outdated. This course walks you through the real threats targeting people your age and gives you concrete steps to protect yourself, your identity, and your accounts.
Ages 17-25Coming Soon8 Modules
Proposed modules
M1
How AI Changed the Threat Landscape â and Why You're a Target
M2
Deepfakes, Voice Clones, and AI-Powered Scams Targeting You
What AI Knows About You: Data, Profiles, and Who's Buying Them
M5
Protecting Your Accounts and Devices in an AI-Powered World
M6
AI Tools That Defend You: What's Worth Using
M7
Cybersecurity as a Career: How AI Is Reshaping the Field
M8
Your Personal Security Audit: Lock Things Down This Week
In Development
💡
Young Adult · Ages 17-25
Is the AI Hype Even Real?
Every week there's a new headline saying AI will either save the world or end it â and most of those headlines are selling you something. This course gives you the thinking tools to evaluate AI claims on your own so you're never the person repeating nonsense at dinner.
LiveAges 17-258 Modules
Proposed modules
M1
How AI Hype Gets Made and Who Benefits From It
M2
What AI Is Actually Good At Right Now â Honestly
M3
What AI Gets Wrong: Hallucinations, Bias, and Blind Spots
AI is reshaping every layer of game design â from how worlds are built to how characters talk back to you. In this course, you'll learn how to use generative AI tools to prototype, design, and pitch interactive experiences, whether you're aiming for a career in gaming or just want to build something people actually play.
LiveAges 17-258 Modules
Proposed modules
M1
How AI Is Changing Game Development Right Now
M2
Generative AI for Characters, Dialogue, and Storytelling
M3
Procedural Worlds: Using AI to Build Environments and Levels
M4
AI-Powered NPCs: Making Characters That Actually React
M5
Prototyping Your Game Idea with AI Tools
M6
Ethics and Player Trust: When AI Goes Wrong in Games
M7
The Business Side: Indie Dev, Studios, and AI Job Roles
M8
Ship Something: Build and Present Your AI-Enhanced Game Concept
Whether you're writing a paper at midnight or pitching a freelance client, ChatGPT can do a lot of the heavy lifting â if you know how to use it properly. This course teaches you the workflows that actually save time and the habits that keep you sharp instead of dependent.
Ages 17-25Coming Soon5 Modules
Proposed modules
M1
Getting Oriented: What ChatGPT Actually Is (Not the Hype Version)
M2
Student Mode: Studying, Summarizing, and Surviving Deadlines
M3
Freelancer Mode: Client Work, Proposals, and Deliverables
M4
Customizing ChatGPT: Memory, Custom Instructions, and GPTs
M5
Staying Honest: Academic Integrity and When Not to Use It
In Development
🔬
Young Adult · Ages 17-25
Claude: Write, Research, Build
You've probably heard of Claude but maybe haven't figured out how to make it actually useful for your life â this course fixes that fast. You'll go from casual user to someone who uses Claude to produce real output: better writing, sharper research, and projects you can show people.
Ages 17-25Coming Soon5 Modules
Proposed modules
M1
What Claude Does Differently (and Why It Matters)
M2
Writing With Claude: Essays, Emails, and Side Projects
M3
Research Mode: Summarizing, Synthesizing, and Fact-Checking
M4
Building Something Real: Projects, Pitches, and Portfolios
M5
Where Claude Falls Short and How to Work Around It
In Development
🌐
Young Adult · Ages 17-25
Deep Learning: Build Real Things
Deep learning is what powers the AI tools everyone is talking about â and you can start building with it without a PhD or expensive hardware. This course gives you the conceptual foundation and hands-on experience to go from curious to capable.
LiveAges 17-258 Modules
Proposed modules
M1
What Deep Learning Actually Is (Skip the Hype)
M2
How Neural Networks Learn: The Intuition Behind the Math
M3
Your First Model: Hands-On in 30 Minutes
M4
Computer Vision â Teaching Machines to See
M5
Natural Language Processing â Teaching Machines to Read
M6
Training, Testing, and Knowing When Your Model Fails
M7
Tools of the Trade: PyTorch, Hugging Face, and Free GPUs
M8
Build Something Real: Your Own Mini Deep Learning Project
If you already live in Google Docs, Gmail, and Drive, Gemini is already in your corner â you just haven't turned it on yet. This course shows you how to use it across your whole Google ecosystem to study smarter, communicate better, and actually get things done.
LiveAges 17-255 Modules
Proposed modules
M1
Gemini Across Google: Where It Lives and What It Touches
M2
Supercharge Your Research and Note-Taking
M3
Drafting Emails, Essays, and Applications Without Losing Your Voice
M4
Multimodal Magic: Working with Images, PDFs, and Audio
You don't need a co-founder, a CS degree, or venture capital to launch an AI product â you need a real problem and the right process. This course walks you through every stage from raw idea to live product with people actually using it.
Ages 17-25Coming Soon8 Modules
Proposed modules
M1
Finding a Real Problem Worth Solving with AI
M2
Validating Your Idea Before You Build Anything
M3
AI-Powered MVPs: What to Build and What to Borrow
M4
Prompting and Wiring: APIs, No-Code Tools, and Glue Logic
M5
Talking to Users: Get Feedback That Actually Changes What You Build
M6
Pricing, Positioning, and Your First Paying Customer
M7
Funding Paths for Young AI Founders: Grants, Accelerators, Bootstrapping
M8
Launch Week: Ship It, Measure It, Iterate
In Development
📊
Young Adult · Ages 17-25
NotionAI: Study, Plan, Build
You already have a million tabs open â NotionAI can help you actually organize your work, not just move it around. This course gets you productive fast with real setups for school, side projects, and everything in between.
Ages 17-25Coming Soon5 Modules
Proposed modules
M1
What NotionAI Actually Does (and What It Can't)
M2
Build Your Personal Study System in 20 Minutes
M3
Project Planning Without the Overwhelm
M4
Writing, Summarizing, and Drafting with NotionAI
M5
Make It Yours: Customize Your Workspace for Your Life
In Development
🛡️
Young Adult · Ages 17-25
Open Source AI: Use It, Own It
You don't have to depend on OpenAI or Google â a massive ecosystem of free, powerful AI tools exists outside Big Tech, and knowing how to use it is becoming a serious career advantage. This course gets you hands-on with open source AI so you can build, experiment, and stay in control of your own work.
Ages 17-25Coming Soon8 Modules
Proposed modules
M1
What Open Source AI Actually Means and Why It's a Big Deal
M2
The Landscape: Key Models, Tools, and Communities to Know
M3
Running AI Locally: What You Need and How to Get Started
M4
Customizing and Fine-Tuning Without a PhD
M5
Privacy, Control, and Why Big Tech Doesn't Want You Here
M6
Open Source AI for Your Career: Skills That Get You Hired
M7
Contributing to the Community Without Being an Expert
M8
Building Something Real: Your First Open Source AI Project
In Development
🎯
Young Adult · Ages 17-25
Python for AI: Zero to Project
Python is the language of AI, and you don't need a CS degree to get started â you need the right path and a real project to finish. This course skips the filler and gets you to something you built yourself using Python and a live AI API.
Ages 17-25Coming Soon8 Modules
Proposed modules
M1
Why Python and Why Now: The AI Developer's On-Ramp
M2
Python Basics That Actually Matter for AI Work
M3
Working With Data: Files, APIs, and Inputs
M4
Your First AI Integration: Calling a Model From Your Own Code
M5
Building a Real Project: Design, Build, and Ship
M6
Reading and Fixing AI-Generated Code Confidently
M7
Sharing Your Work: GitHub, Portfolios, and Getting Noticed
M8
What to Learn Next and How to Keep Momentum
In Development
🎙️
Elective · AI Tools & Apps
Wispr Flow: Voice Dictation Mastery
Master every default shortcut, feature, and workflow in Wispr Flow. Go from slow typing to fluid voice dictation across any app — in a single hands-on module.
Live1 Module
Proposed modules
M1
Dictation Fundamentals: From Zero to Fluent
Push-to-talk, toggle mode, voice punctuation, and every default shortcut you need
The difference between AI giving you something usable and AI wasting your time is almost always the prompt â and it's a learnable skill, not a talent. This course gives you a practical system for writing prompts that get real results across every major AI tool you'll use.
LiveAges 17-258 Modules
Proposed modules
M1
Why Your Prompts Are Probably Failing (and the Fix)
M2
The Core Techniques: Role, Context, Format, and Constraints
M3
Prompting for Your Goals: Writing, Coding, Research, and More
M4
Chaining Prompts: Getting Complex Work Done in Steps
M5
Testing and Improving: How to Know When a Prompt Is Actually Good
M6
Prompting Across Tools: ChatGPT, Claude, Gemini, and Others
M7
Building a Personal Prompt Library You'll Actually Use
M8
Advanced Patterns: Few-Shot, Chain-of-Thought, and When They Help
You receive a viral video that could change everything â but is it real? In this story-driven course, you play a junior investigator who must use critical thinking and AI-detection skills to expose fakes before they cause harm.
An AI system in your city is making decisions that keep failing the same group of people â and you've been asked to investigate. You'll follow the bias from the training data all the way to real-world impact, then decide what should actually be done about it.
You've been given one week, one AI tool, and one brief â create something that matters to you. This course drops you into a real creative challenge where every decision about how to use AI shapes the final result, and teaches you when to trust the machine and when to take back control.
Follow Nadia, a student who discovers her school's new AI recommendation system is giving everyone the same suggestions â and sets out to understand why by pulling apart how AI actually thinks. This course uses hands-on experiments and story choices to demystify machine learning from the inside out.
You're a creator with a deadline, a vision, and a powerful AI co-pilot â but every tool comes with a catch. This course puts you inside real creative dilemmas where you'll learn to use AI art, writing, and music tools effectively while grappling with the ownership, originality, and ethics they raise.
Something funny is going on â your AI helper keeps misunderstanding you, and only you can figure out the magic words to fix it. Through playful story puzzles, you'll discover how AI understands language and learn the art of writing prompts that actually work.
Meet Pixel, an AI who only does exactly what you say â and nothing more. In this playful adventure, you help Pixel complete missions by learning to write clearer, smarter, more creative instructions, discovering along the way that talking to AI is a real skill anyone can learn.
Step into a breaking news crisis where AI-generated stories are spreading fast â and you're the only one who can figure out what's real. Through choices that have real consequences inside the story, you'll learn exactly how AI creates and spreads misinformation, and build the skills to stop it.
You've been hired as a junior engineer at a company whose AI keeps making strange mistakes â and it's your job to figure out why. By investigating each glitch inside the story, you'll uncover exactly how AI models are trained, how they reason, and where they fall apart.
Follow three students navigating a school that has rolled out AI tools across every subject â and discover the tensions between convenience, fairness, privacy, and learning that nobody fully thought through. This course challenges you to think like a policy-maker and produce a realistic proposal for how AI should and shouldn't be used in your own school.
Ages 8-16Coming Soon6 Modules
Proposed modules
M1
The Essay the AI Wrote for Everyone
M2
Surveillance, Grades, and Predictive Systems
M3
When Personalization Becomes a Box
M4
Academic Integrity in the AI Era
M5
What Schools Won't Always Tell You
M6
Propose Your School's AI Use Policy
In Development
🔬
Youth · Ages 8-16
Build Powerful AI Without Coding
You're a startup founder with a real problem and zero engineers â so you must build an AI-powered workflow using no-code tools to solve it before your pitch meeting. Each module adds a new layer of complexity, and you'll defend every automation decision in a final board-room scenario.
One post. One algorithm. One chain of consequences you didn't expect â this course drops you into the middle of a social media spiral powered by AI recommendation systems and asks you to make the calls that shape what happens next. You'll leave having written your own digital citizenship code for the AI age.
You're a student tester hired to audit AI tutors â including Khanmigo and others â by actually using them, breaking them, and judging whether they help or mislead learners like you. Each module puts you in a scenario where you must decide how much to trust the AI's guidance and why.
A curious kid stumbles into a behind-the-scenes tour of a chatbot factory, where the machines can talk but nobody has explained how â and it is your job to figure it out by running experiments, making choices, and fixing things when they go hilariously wrong. This wonder-driven adventure builds real intuition for how language models work through play, not explanation.
Ages 8-16Coming Soon6 Modules
Proposed modules
M1
The Robot That Talks Back
M2
Where Do the Words Come From?
M3
Teaching a Bot With Examples
M4
When the Bot Gets Confused
M5
Give the Bot a Job to Do
M6
Draw Your Own Chatbot Brain
In Development
📊
Youth · Ages 8-16
Real or Generated: You Decide
A viral image has caused chaos at your school â but was it real? Work through a mystery where you examine photos, articles, and video clips, learning to spot the telltale signs of AI generation before the truth gets buried. The final challenge asks you to create a piece of AI content and then write the guide that helps others detect it.
Investigative journalists, civil rights advocates, and skeptical teenagers all need the same skill: the ability to look at an AI-powered system and ask hard questions about who it serves and who it harms. This course puts you in the role of an AI investigator working through four real-world scenarios where the stakes are high and the answers are not obvious.
In this course you play a high schooler navigating a school that has quietly rolled out AI tools for grading, monitoring, and advising — and something starts to feel off. You'll investigate real risk categories like data privacy, algorithmic bias, and over-reliance, and decide what students should actually do about them.
Ages 8-16Coming Soon4 Modules
Proposed modules
M1
The Algorithm That Grades You
M2
Privacy, Data, and Your Digital Trail
M3
When AI Advice Goes Wrong
M4
Push Back or Accept? Your Call
In Development
🔮
Youth · Ages 8-16
AI Tools Field Guide
A young journalist is handed a school magazine story with no guidance — just a collection of AI tools and a deadline, and every choice about which tool to use and how to verify its output is yours to make. Students explore the landscape of AI tools across writing, image generation, research, and organisation, developing real judgment about fit, quality, and risk.
Ages 8-16Coming Soon6 Modules
Proposed modules
M1
The Toolkit Nobody Gave You
M2
Image Makers and Word Builders
M3
Picking the Right Tool for the Job
M4
When the Tool Misleads You
M5
Stack Your Tools: A Real Project
M6
Rate It: Your AI Tool Reviews
In Development
📊
Youth · Ages 8-16
AI in Class: Use It or Lose It
You are a student adviser helping a school board decide which AI tools belong in classrooms and which ones should be banned — and why. This course builds the critical vocabulary and evaluative skills to assess AI tools the way educators, ethicists, and students all need to.
You step inside the fictional AI tutoring platform MIRA and play both student and designer — experiencing how an AI tutor decides what to say, what to skip, and when to encourage you. By reverse-engineering its choices, you learn what real systems like Khanmigo are actually doing beneath the surface.
You're facing a deadline, a confusing assignment, and an AI tool that can write the whole thing in seconds — this story puts you in that moment and makes the consequences real. By playing through different choices, you'll develop your own honest, smart approach to using AI on schoolwork.
Ages 8-16Coming Soon4 Modules
Proposed modules
M1
Shortcut or Cheat? You Decide
M2
AI as a Tutor, Not a Ghost Writer
M3
The Credit Question: Who Did This?
M4
Your Personal AI Homework Policy
In Development
🧠
Youth · Ages 8-16
Homework and the AI Question
Follow a student who discovers AI can finish their homework in seconds — and then has to live with the consequences of every choice they make about how to use it. This course challenges learners to draw their own lines between smart assistance and dishonest shortcuts, leaving with a personal policy they actually believe in.
Ages 8-16Coming Soon6 Modules
Proposed modules
M1
The Essay That Wrote Itself
M2
Shortcut or Cheat? You Decide
M3
When AI Helps You Learn More
M4
Spotting AI Slop in the Wild
M5
The Honesty Audit
M6
Your Personal AI Use Policy
In Development
⚡
Youth · Ages 8-16
How Machines Actually Learn
You're an AI auditor called in after three different machine learning systems — a hiring tool, a medical screener, and a content filter — have made decisions that hurt real people. You have to dig into the data and training choices to find out exactly why.
Step inside a newsroom where an AI assistant keeps feeding your team information — some true, some dangerously wrong — and every choice you make affects the story that gets published. By the end, you'll have built a personal checklist for deciding when to believe what AI tells you.
In the village of Pebbletown, an AI called SORTR decides who gets the good library books, the best lunch table, and the starring role in the school play — and something feels wrong. You play a kid detective who must figure out why SORTR keeps making unfair choices and then redesign its rules so everyone gets a fair chance.
You are a consultant hired to choose the best AI model for five very different clients — a novelist, a coder, a journalist, a student, and a small business owner. Every choice you make has real consequences inside the story, and by the end you will have built a reusable decision framework you can apply outside it.
You're a junior investigator at a news agency where AI-generated images, voices, and text keep slipping through — and it's your job to catch them before they go public. Every choice you make changes what gets published and who gets hurt.
Join a cast of kids who accidentally teach a classroom robot some very strange habits, then race to fix it by understanding how machines actually learn from examples. You will make real decisions about what data to feed an AI and see the results immediately in the story.
Ages 8-16Coming Soon4 Modules
Proposed modules
M1
The Machine That Watches and Learns
M2
Feeding an AI: Data Is Its Food
M3
What Happens When Data Is Wrong?
M4
Train Your Own Sorting Machine
In Development
🧠
Youth · Ages 8-16
AI Thinks? Really? Show Me.
Through a choose-your-own mystery adventure, you and a quirky AI sidekick solve puzzles that reveal how artificial intelligence actually processes information — no magic involved. By the end you will have built a simple decision tree that makes choices the same way a real AI does.
Ages 8-16Coming Soon4 Modules
Proposed modules
M1
Robots, Rules, and Real Brains
M2
Patterns Everywhere: How AI Sees
M3
AI Versus Human: Who Decides?
M4
Build Your Own Decision Tree
In Development
🔬
Youth · Ages 8-16
AI: Your Curious New Neighbor
Follow Zara, a friendly AI helper, through a neighborhood full of problems to solve — and make choices that show you exactly how AI thinks, learns, and sometimes fails. By the end, you'll build your own idea for an AI tool that helps someone you know.
Ages 8-16Coming Soon6 Modules
Proposed modules
M1
Meet Zara the Robot Helper
M2
How Does Zara Learn Things?
M3
When Zara Gets It Wrong
M4
AI in Your Everyday World
M5
Is Zara Alive or Just Smart?
M6
Build Your Own AI Idea
In Development
🌐
Youth · Ages 8-16
Chat With AI: You're in Charge
Step inside a story where you trade messages with an AI called Pixel and discover what chatbots can and cannot do. Every choice you make teaches you how to ask better questions and stay safe online.
Ages 8-16Coming Soon4 Modules
Proposed modules
M1
Meet Pixel: Your AI Pen Pal
M2
What Can Chatbots Actually Do?
M3
When Pixel Gets It Wrong
M4
Write Your Own Chatbot Rules
In Development
🛡️
Professional
RAG and Agent Workflows with LlamaIndex
Retrieval-Augmented Generation has become the dominant architecture for grounding LLMs in organizational knowledge â and LlamaIndex is the leading framework for building these systems at scale. This course moves beyond conceptual overviews to give developers and technical professionals the design patterns and practical skills needed to build, evaluate, and maintain production RAG pipelines and autonomous agents.
Coming Soon8 Modules
Proposed modules
M1
Why RAG Exists: Limitations of Base LLMs and When Retrieval Solves Them
Diagnosing where base LLMs fail and retrieval helps
M2
LlamaIndex Core: Documents, Nodes, Indexes, and Query Engines
Mastering LlamaIndex's fundamental data and query abstractions
M3
Designing Retrieval Pipelines for Real-World Document Corpora
Architecting robust retrieval for messy, heterogeneous document collections
M4
Building Agents: Tool Use, Reasoning Loops, and Multi-Step Query Handling
Creating autonomous agents that plan, retrieve, and act across steps
M5
Evaluating RAG Quality: Metrics, Failure Modes, and Iteration Strategies
Measuring retrieval and generation quality to drive systematic improvement
M6
Connecting LlamaIndex to External Data Sources and APIs
Extending RAG systems with live data sources and third-party integrations
M7
Scaling, Caching, and Cost Optimization in Production RAG Systems
Engineering RAG pipelines for throughput, reliability, and cost efficiency
M8
Applying LlamaIndex to a Domain-Specific Professional Knowledge Base
Integrating course skills into a complete, domain-tailored RAG deployment
In Development
🎯
Professional
Autonomous AI Agents at Work: Manus
Manus represents a new class of autonomous AI agent that can plan, browse, code, and execute multi-step tasks with minimal human hand-holding â a meaningful shift from chat-based AI assistance. This course gives professionals a clear-eyed understanding of what Manus can and cannot reliably do, and builds the task-design and oversight skills needed to delegate real work to it without losing control of outcomes.
Coming Soon5 Modules
Proposed modules
M1
What Manus Actually Does: Architecture, Capabilities, and Honest Limitations
Building an accurate mental model of how Manus operates
M2
Delegating Real Tasks: What Works, What Fails, and How to Tell the Difference
Matching task types to what autonomous agents can handle
M3
Designing Task Instructions That Autonomous Agents Can Execute Reliably
Writing task briefs that leave no room for costly misinterpretation
M4
Oversight, Verification, and Knowing When to Trust Agent Output
Building routines that catch agent errors before they propagate
M5
Integrating Manus into Professional Workflows: Use Cases Across Roles
Translating agent capabilities into role-specific productivity gains
In Development
🧠
AIP Draft
AI for Accessibility
Discover how AI technologies can help people with disabilities access information and services. Learn principles for designing inclusive AI systems.
Coming Soon4 Modules
Proposed modules
M1
Assistive Technology Applications
M2
Inclusive AI Design
M3
Breaking Down Barriers
M4
Universal Access Principles
In Development
🔬
AIP Draft
Autonomous AI Systems
Explore AI systems that operate independently in the physical world. Understand the technology behind autonomous vehicles, drones, and robots.
Headlines about AI stealing jobs tell only part of the story — this course gives you the full picture, from which roles are genuinely at risk to the new opportunities emerging in an AI-shaped economy. Walk away with practical strategies for navigating your own career.
Coming Soon8 Modules
Proposed modules
M1
Separating Automation Myths from Facts
M2
Which Tasks AI Automates First
M3
Jobs Created by the AI Boom
M4
Vulnerable Industries: An Honest Look
M5
Reskilling Strategies That Actually Work
M6
AI as Your Workplace Collaborator
M7
Policy Responses Around the World
M8
Designing Your AI-Resilient Future
In Development
🎯
AIP Draft
AI Ethics: Right and Wrong
This course introduces everyday people to the moral questions shaping AI development, from bias and privacy to accountability and human rights. No technical background needed — just curiosity about the world AI is building around us.
Examine how AI systems make decisions that affect people's lives. Learn when to trust AI recommendations and how to maintain human oversight.
Coming Soon4 Modules
Proposed modules
M1
Automated Decision Systems
M2
Human-AI Collaboration
M3
Decision Quality and Accuracy
M4
Accountability in AI Decisions
In Development
📊
AIP Draft
AI Governance and Regulation
Explore how governments and organizations are regulating AI development and deployment. Understand current policies and emerging governance frameworks worldwide.
Discover how artificial intelligence is transforming music composition, sound design, and voice generation — from apps that write songs in seconds to tools that clone human voices with startling accuracy. This course equips learners to use, evaluate, and think critically about AI audio tools shaping entertainment, media, and creative industries.
AI safety is one of the most debated topics in tech, yet most people have never encountered a clear, jargon-free explanation of what it means. This course demystifies alignment, risk, and the global effort to keep powerful AI beneficial.
AI safety is one of the most debated topics in technology, yet most people have never heard a clear explanation of what it actually means. This course demystifies alignment, risk, and oversight so that informed citizens can participate in the conversation.
As AI systems grow more capable, ensuring they reliably do what we actually want — and not something subtly or dangerously different — has become one of the most urgent challenges in technology. This course demystifies AI safety and alignment research so curious learners can understand the stakes and join an informed global conversation.
Understand how AI shapes your social media experience through content filtering and targeted advertising. Learn about algorithmic content moderation and social influence.
Learn principles for designing effective interactions between humans and AI systems. Explore how to build trust and create intuitive AI-powered experiences.
Learn about AI's environmental costs and energy consumption. Discover approaches to developing more sustainable and environmentally friendly AI systems.
Coming Soon4 Modules
Proposed modules
M1
AI's Environmental Impact
M2
Energy-Efficient AI Models
M3
Carbon Footprint Measurement
M4
Sustainable Development Practices
In Development
💬
Professional · Intermediate
Using Claude AI Chat
A hands-on workshop for professionals who want to stop dabbling with Claude and start using it as a serious productivity tool. You'll learn how to craft prompts that get real results, manage complex multi-turn conversations, and build a personal library of prompts that save you hours every week.
Live4 Modules
Course modules
M1
Getting Claude to Do What You Mean
Prompting with intent: instructions, context, and format
M2
Prompting for Professional Deliverables
Reports, emails, summaries, and structured outputs
Stop using Claude like a search engine and start using it like a thinking partner. This course teaches you how to structure open-ended collaboration sessions, delegate tasks across Claude conversations, and bring AI into your actual team workflows — not just your personal ones.
Live4 Modules
Course modules
M1
Structuring a Cowork Session
Framing problems, setting context, and iterating fast
M2
Agent Delegation and Task Handoff
Subagent patterns, parallel tasks, and handoff protocols
M3
Team Workflows with Claude
Shared prompts, review cycles, and collaborative output
M4
Reviewing and Trusting AI Output
Verification habits, hallucination awareness, and quality gates
Claude Code is Anthropic's terminal-based AI coding agent — and it changes how serious developers work. This course takes you from installation through advanced workflows: hooks, MCP servers, multi-agent pipelines, and production-grade PR review. Built for developers who want the real thing, not the toy version.
Live4 Modules
Course modules
M1
Setup, Configuration, and First Runs
Installing Claude Code, CLAUDE.md, and project setup
M2
Hooks, Permissions, and Safety
Pre/post tool hooks, permission models, and guardrails
M3
MCP Servers and Extended Capabilities
Connecting tools, databases, and APIs through MCP
M4
PR Workflows and Team Integration
Code review, multi-agent pipelines, and CI/CD integration