📅 Date: 30 March

⏰ Time: 4PM

🌐 Location: Virtual

What’s Happening in Week 7?

In this session, we’ll introduce the concepts behind Generative AI Agents and their practical applications. 

Participants will learn about the components of AI agents and how to design them for various tasks.

After the session, participants will continue with self-paced study to deepen their understanding and apply their knowledge to build generative AI-powered systems.

About the Session: Generative AI Agents

Topics Covered in the Session:

1️⃣ What Are Generative AI Agents? – Learn how AI agents combine generative models with task-specific logic to perform dynamic actions.

2️⃣ Core Components of AI Agents – Understand the building blocks of generative agents, including:

• Memory
• Planning
• Decision-making logic
• Interaction and response generation

3️⃣ Iterative Development – Explore the process of building and refining agents for specific use cases, from chatbots to creative AI systems.

4️⃣ Real-World Applications – Examples include:

• Autonomous customer service agents
• Game-playing AI agents
• Creative agents for art or content generation

Session Highlights:

• How to integrate generative AI models (e.g., OpenAI GPT, Bard) into agent frameworks
• Practical tools and libraries for building AI agents, like LangChain or AutoGPT
• Tips for testing and refining agent behavior

Requisites for Week 7:

1️⃣ Completion of Week 6’s Embeddings and Vector Stores/Databases 📚

2️⃣ Familiarity with foundational generative models and prompt engineering from Week 5 🌐

3️⃣ Access to a generative AI API or framework for hands-on experimentation ✅

This session will empower participants to create AI agents that can act autonomously, interact dynamically, and adapt to tasks, opening new possibilities in AI-driven automation and creativity.

Complete Series Overview

This program unfolds across multiple weeks, offering foundational insights and advanced explorations into machine learning and generative AI.

ML Study Jam Weekly Plan:

1️⃣ Week 1: Intro to Machine Learning

2️⃣ Week 2: Intermediate Machine Learning

3️⃣ Week 3: Intro to Deep Learning

4️⃣ Week 4: Intro to AI Ethics

5️⃣ Week 5: Foundational Models & Prompt Engineering

6️⃣ Week 6: Embeddings and Vector Stores/Databases

7️⃣ Week 7: Generative AI Agents

8️⃣ Week 8: Domain-Specific LLMs

9️⃣ Week 9: MLOps for Generative AI

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