AWS Bedrock
Module 9 Wrap-up: The Safe Assistant
Hands-on: Implement a Bedrock Guardrail and verify your grounding instructions.
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Generative AI
Capstone Projects: Applying Your AI Knowledge
From Chatbot to RAG. Three hands-on projects to prove your mastery of Generative AI fundamentals.
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Generative AI
Module 1 Lesson 1: What Is Artificial Intelligence?
Defining AI in simple terms and exploring everyday examples of AI in our world.
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Generative AI
Module 1 Lesson 2: The AI Hierarchy
Understanding how Generative AI sits within the broader fields of Machine Learning and Deep Learning.
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Generative AI
Module 1 Lesson 3: Discriminative vs. Generative AI
Predicting labels vs. creating new data. Understanding the fundamental shift in how AI assists us.
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Generative AI
Module 1 Lesson 4: A Brief History of Generative AI
From rule-based systems to GANs and the massive Transformer breakthrough.
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Generative AI
Module 1 Wrap-up: Mapping the AI World
Reviewing the AI landscape and testing your ability to distinguish between different AI types.
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Generative AI
Module 2 Lesson 1: What Are Large Language Models (LLMs)?
Understanding the scale, training, and significance of models like GPT-4 and Claude.
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Generative AI
Module 2 Lesson 2: How LLMs Work (Conceptual)
From Tokens to Embeddings. Understanding the mechanics of how a computer 'reads' meaning.
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Generative AI
Module 2 Lesson 3: The Transformer Architecture
Attention Mechanisms and Context. Understanding the 'Secret Sauce' that allows AI to reason across long documents.
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Generative AI
Module 2 Lesson 4: Hallucinations and Bias
Common failure modes. Why AI makes things up and how to detect biased or incorrect outputs.
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Generative AI
Module 2 Lesson 5: Popular LLMs Overview
Choosing your model. Comparing the strengths and tradeoffs of GPT-4, Claude, Gemini, and Llama.
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Generative AI
Module 2 Wrap-up: Understanding the Engine
Reviewing the mechanics of LLMs and conducting a comparative model experiment.
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Generative AI
Module 3 Lesson 1: Why Prompting Matters
The Prompt as an Interface. Understanding why the quality of your input directly determines the utility of the AI.
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Generative AI
Module 3 Lesson 2: Foundational Prompting Techniques
Zero-shot, Few-shot, and Chain-of-Thought. The three pillars of professional AI interaction.
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Generative AI
Module 3 Lesson 3: System Prompts
Defining Persona and Role. How to create an 'Invisible' layer of instructions that controls the AI's personality and safety.
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Generative AI
Module 3 Lesson 4: Structuring Outputs
From Text to Table. How to force the AI to return data in specific formats like JSON, Markdown, or CSV.
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Generative AI
Module 3 Lesson 5: Iterative Prompt Design
The Refinement Loop. How to treat prompting as an experiment rather than a one-off command.
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Generative AI
Module 3 Wrap-up: Becoming a Prompt Architect
Reviewing professional prompting techniques and completing a structured output project.
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Generative AI
Module 4 Lesson 1: Image Generation and Diffusion
How AI draws. Understanding Diffusion models and the tools used to create stunning visual content from text.
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Generative AI
Module 4 Lesson 2: Audio and Video Generation
The Sound of AI. Exploring text-to-speech, music generation, and the emerging frontier of AI-generated video.
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Generative AI
Module 4 Lesson 3: Code Generation
AI as a Coding Assistant. How to use LLMs to write, debug, and explain programming languages.
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Generative AI
Module 4 Wrap-up: The Multimodal Creator
Reviewing non-text GenAI and practicing image generation and code refactoring.
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Generative AI
Module 5 Lesson 1: Retrieval-Augmented Generation (RAG)
Connecting AI to Reality. How to ground AI responses in your own private data to prevent hallucinations.
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Generative AI
Module 5 Lesson 2: Vector Databases
The Memory of AI. Understanding how we store and search 'Meaning' using embeddings and specialized databases.
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Generative AI
Module 5 Lesson 3: Agentic AI and Orchestration
From Chatbot to Coworker. Understanding AI agents that can use tools and make autonomous decisions.
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Generative AI
Module 5 Lesson 4: Local LLMs
AI on your desktop. Learn why and how to run powerful models locally for total privacy and zero cost.
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Generative AI
Module 5 Wrap-up: Building with Intelligence
Reviewing the AI tech stack and building a simple RAG pipeline and local AI setup.
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Generative AI
Module 6 Lesson 1: Responsible AI
The Weight of Creation. Discussing deepfakes, copyright, and the environmental impact of large-scale AI.
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Generative AI
Module 6 Lesson 2: Security and Privacy
Protecting the Prompt. Understanding prompt injection attacks and data leakage risks in AI systems.
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Generative AI
Module 6 Lesson 3: The Future of Generative AI
Where we are heading. Discussing Small Language Models (SLMs), autonomous agents, and the new skills required for the AI era.
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Generative AI
Module 6 Wrap-up: Designing the Future Responsibly
Finalizing the course with a discussion on ethics and an outlook on the AI co-pilot era.
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LangChain
Capstone Project: The Autonomous Market Analyst
The Final Challenge. Build a production-ready, agentic RAG system that analyzes companies and returns structured research reports via a REST API.
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LangChain
Module 1 Lesson 1: Python and Virtual Environments
The starting point. How to set up a clean, isolated Python environment for your LangChain projects.
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LangChain
Module 1 Lesson 2: Installing LangChain
The core installation. Learning about LangChain's modular package structure and how to install the base library.
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LangChain
Module 1 Lesson 3: Installing Model Providers
Connecting to the brains. How to install specialized packages for OpenAI, Anthropic, and local model providers.
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LangChain
Module 1 Lesson 4: API Keys and Environment Variables
Security First. How to securely manage your API keys using .env files and prevent accidental leaks.
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LangChain
Module 1 Lesson 5: First LangChain Run
The Hello World of AI. Initializing your first chat model and making a successful invocation.
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LangChain
Module 1 Wrap-up: Verification and First Call
Hands-on: Verify your complete installation and take the Module 1 challenge.
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LangChain
Module 10 Lesson 1: Agent Fundamentals
The Autonomous Mind. Understanding the difference between a static Chain and a dynamic Agent that makes its own decisions.
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LangChain
Module 10 Lesson 2: The Agent Loop and Tool Selection
How the Agent decides. Deep dive into the mechanics of tool selection and processing tool outputs.
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LangChain
Module 10 Lesson 3: Safety Limits (Max Iterations & Timeouts)
Guarding the Budget. How to prevent your agents from getting stuck in infinite loops and burning through your API credits.
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LangChain
Module 10 Wrap-up: Building Your First Agent
Hands-on: Combine tools, memory, and reasoning into a single autonomous Research Agent.
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LangChain
Module 11 Lesson 1: Why Structured Output Matters
From Stories to Schema. Why production AI must return machine-readable data (JSON) to interact with other software systems.
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LangChain
Module 11 Lesson 2: Output Parsers (Pydantic & JSON)
Parsing the Mess. Learning how to use OutputParsers to extract structured data even from older or less capable models.
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LangChain
Module 11 Wrap-up: Getting Reliable Data
Hands-on: Build an Information Extraction agent that converts raw text into a clean Python object.
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LangChain
Module 12 Lesson 1: Introduction to Callbacks
Listening to the Chain. How to use the Callback system to intercept events like 'LLM Start' or 'Tool End' for logging and UI updates.
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LangChain
Module 12 Lesson 2: Implementing Callbacks in Chains
Connecting the Hearths. How to pass your custom handlers to models, tools, and executors to start capturing events.
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LangChain
Module 12 Wrap-up: Inspecting the Machine
Hands-on: Build a Cost-Monitoring Callback that calculates and prints the price of every AI request.
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LangChain
Module 13 Lesson 1: Debugging Chains
Finding the Bug. Techniques and tools for identifying where a multi-step chain is failing or hallucinating.
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