Building Intelligent Agents with LLMs
FREE
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Course Overview
Schedule of Classes
Course Curriculum
8 Subjects
Building Intelligent Agents with LLMs
1 Exercises • 7 Learning Materials
Module 1: Introduction to AI Agents and LLMs
AGENDA
Module 2: Foundations of LLM APIs
AGENDA
Module 3: Architecting an AI Agent
AGENDA
Module 4: Building a Basic Conversational Agent
AGENDA
Module 5: Advanced Agent Capabilities
AGENDA
Module 6: Agents with External Integrations
AGENDA
Module 7: Security, Ethics, and Deployment
AGENDA
Module 1: Introduction to AI Agents and LLMs
10 Exercises • 7 Learning Materials
1.1 Understanding AI Agents
Presentation
Assignment - Classify AI agents
Test
1.2 Fundamentals of Large Language Models (LLMs)
Presentation
Assignment - Tokenization in LLMS
Assignment - Fine-Tuning DistilBERT
1.3 History and Evolution of AI and NLP
Presentation
Assignment - Rule-Based and NLP-Based Chatbots
1.4 How LLMs Work
Presentation
Assignment - Self-Attention Score Calculation
Assignment - Preprocessing and Visualization of a Dataset
1.5 Popular LLMs and Their Use Cases
Presentation
Assignment - Interactive LLM Use Case Explorer
1.6 Challenges and Limitations of LLMs
Presentation
Assignment - Optimizing Text Summarization
1.7 The Role of AI Agents in Modern Workflows
Presentation
Assignment - Chatbot Development with LLM API
Module 2: Foundations of LLM APIs
9 Exercises • 7 Learning Materials
2.1 Introduction to LLM APIs
Presentation
Assignment - LLM API Text Generation in Python
2.2 How LLM APIs Work
Presentation
Assignment - Secure API Authentication & Error Handling
Assignment - LLM API Request & JSON Parsing
2.3 Tokenization and API Usage Costs
Presentation
Assignment - API Cost Calculator for Token Usage
2.4 Understanding Prompts and Responses
Presentation
Assignment - Impact of Context Windows on LLM Accuracy
Assignment - API Calls for Different Prompt Styles
2.5 Rate Limits and API Constraints
Presentation
Assignment - Optimizing API Calls with Batching & Delays
2.6 Customizing API Responses
Presentation
Assignment - Effect of Temperature, Top-K & Top-P on Responses
2.7 Streaming vs. Batch Requests
Presentation
Assignment - Streaming Responses from LLM API
Module 3: Architecting an AI Agent
7 Exercises • 7 Learning Materials
3.1 Designing an AI Agent Framework
Presentation
AI Agent Framework in Python
3.2 AI Agent Workflow and Data Flow
Presentation
LLM API: Input Processing & Output Formatting
3.3 State Management in AI Agents
Presentation
AI Agent with Context Retention for Better Responses
3.4 AI Agent Decision-Making Models
Presentation
Hybrid AI Agent: Merging Rules & Machine Learning
3.5 Handling Unstructured Data in AI Agents
Presentation
LLM-Powered Information Retrieval with FAISS
3.6 Agent-Powered Task Automation
Presentation
Automating a Workflow Using an AI Agent
3.7 Evaluating and Improving AI Agent Performance
Presentation
AI Agent Performance Metrics Implementation
Module 4: Building a Basic Conversational Agent
7 Exercises • 6 Learning Materials
4.1 Fundamentals of Conversational AI
Presentation
Assignment - Building a Simple Chatbot with Python (NLTK/spaCy)
Assignment - User Intent Analysis and Context Extraction in Python
4.2 Setting Up a Conversational AI Pipeline
Presentation
Assignment - Multi-Turn Conversational Chatbot with FastAPI
4.3 Enhancing User Interaction and Experience
Presentation
Assignment - Interactive Exercise to Measure Chatbot Personalization Impact
4.4 Error Handling and Fallback Mechanisms
Presentation
Assignment - Enhancing Chatbot Accuracy with User Feedback
4.5 Implementing Context Awareness
Presentation
Assignment - Dynamic Summarization to Handle Context Window Limits
4.6 Deployment of Basic Conversational Agent
Presentation
Assignment - Chatbot Interaction Monitoring and Logging Tool
Module 5: Advanced Agent Capabilities
5 Exercises • 5 Learning Materials
5.1 Advanced Prompt Engineering Techniques
Presentation
Assignment - Dynamic Prompt Chaining for Gemini Travel Planner
5.2 Knowledge Retrieval with AI Agents
Presentation
Assignment - Building a RAG (Retrieval-Augmented Generation) Pipeline
5.3 Handling Multi-modal Inputs
Presentation
Assignment - Image Captioning with Pretrained Vision-Language Models (BLIP)
5.4 Multi-Agent Collaboration
Presentation
Assignment - Collaborative Multi-Agent Workflow for Goal Achievement
5.5 Fine-Tuning AI Agents
Presentation
Assignment - Domain-Specific Customization and Fine-Tuning of LLMs
Module 6: Agents with External Integrations
3 Exercises • 3 Learning Materials
6.1 API-based Integrations
Presentation
Assignment - API Error Handling and Retry Mechanism
6.2 Integrating AI Agents with Databases
Presentation
Assignment - Vector Database for Contextual Data Retrieval in AI Agents
6.3 AI Agents in Enterprise Workflows
Presentation
Assignment - AI Agent for CRM Task Automation (Lead Categorization)
Module 7: Security, Ethics, and Deployment
4 Exercises • 3 Learning Materials
7.1 Ethical Considerations in AI Development
Presentation
Assignment - Detecting and Mitigating Bias in AI Outputs
Assignment - Evaluating AI Decisions for Responsible AI Compliance
7.2 AI Security Best Practices
Presentation
Assignment - Securing API Keys with Environment Variables
7.3 Deploying AI Agents at Scale
Presentation
Assignment - Deploying and Monitoring AI Agent on Cloud Infrastructure
Course Instructor
Mentor
27 Courses • 2698 Students
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