Agentic AI by Andrew Ng at DeepLearning.ai

View Course on DeepLearning.ai

Legend:
M: Module
L: Lesson


M1 - Introduction to Agentic Workflows


M1L2 - What is Agentic AI




M1L3 - Degrees of Autonomy




M1L4 - Benefits of Agentic AI




M1L5 - Agentic AI Applications




M1L6 - Task Decomposition - Identifying the steps in a workflow




M1L7 - Evaluating Agentic AI (evals)




M1L8 - Agentic Design Patterns




M1L9 - Quiz




Setup Steps (part of module-1 lab)


M2 - Reflection Design Pattern


M2L1 - Reflection to improve outputs of a task




M2L2 - Why not just direct generation




M2L3 - Chart Generation Workflow




M2L4 - Evaluating the impact of reflection




M2L5 - Using External Feedback




M2L6 - Quiz




Open Module-2 Lab Assignments

M3 - Tool Use


M3L1 - What Are Tools




M3L2 - Creating a Tool




M3L3 - Tool Syntax




M3L4 - Code Execution




M3L5 - MCP




M3L6 - Quiz




Open Module-3 Lab Assignments

M4 - Practical Tips for Building Agentic AI


M4L1 - Evaluations (evals)




M4L2 - Error Analysis and prioritizing next steps




M4L3 - More error analysis examples





M4L4 - Component-level evaluations




M4L5 - How to address problems you identify




M4L6 - Latency, cost optimization




M4L7 - Development process summary




M4L8 - Quiz



Open Module-4 Lab Assignment


M5 - Patterns for Highly Autonomous Agents

M5L1 - Planning Workflows




M5L2 - Creating and executing LLM plans




M5L3 - Planning with code execution




M5L4 - Multi-agentic workflows




M5L5 - Communication patterns for multi-agent systems




M5L6 - Quiz



Open Module-5 Lab Assignments

Tags: Technology,Agentic AI,Artificial Intelligence,