Program Outline: Developing GenAI Solutions with RAG#
Duration:#
4 Days
Course Audience:#
Technical Leads, Technical Architects, Service Delivery Managers
Target Unit:#
Delivery CoE, Product, Internal Applications
Course Outline#
Day 1: Introduction to Generative AI and Frameworks#
Morning Sessions 9:00 AM to 1:00 PM#
1. Session 1 - Overview of Generative AI (9:00 AM - 10:30 AM)
- Evolution of Generative AI
- Applications of GenAI in Automation and Conversational Systems
2. Session 2 - Introduction to LangChain & LlamaIndex (10:45 AM - 1:00 PM)
- Overview of LangChain and its Components
- Introduction to LlamaIndex (formerly GPT Index) and Its Role in Data Interaction
Lunch 1:00 PM to 2:00 PM
Afternoon Sessions 2:00 PM to 5:00 PM#
3. Session 3 - Understanding LangChain Architecture (2:00 PM - 3:30 PM)
- Chains, Agents, and Prompts
- Integrating APIs and Tools in LangChain
4. Session 4 - Setting Up Development Environments (3:45 PM - 5:00 PM)
- Installation and Configuration of LangChain and LlamaIndex
- Best Practices for Development Setup
Day 2: Building Custom AI Applications with LangChain#
Morning Sessions 9:00 AM to 1:00 PM#
5. Session 5 - Designing and Building Custom Chains (9:00 AM - 10:30 AM)
- Creating Simple and Complex Chains
- Managing State and Context in Applications
6. Session 6 - Agents and Toolkits in LangChain (10:45 AM - 1:00 PM)
- Understanding Agents and Their Functionality
- Building a Custom Agent with LangChain
Lunch 1:00 PM to 2:00 PM
Afternoon Sessions 2:00 PM to 5:00 PM#
7. Session 7 - Conversational AI Applications (2:00 PM - 3:30 PM)
- Building Chatbots with LangChain
- Integration with Messaging Platforms
8. Session 8 - Hands-On: LangChain Use Cases (3:45 PM - 5:00 PM)
- Real-World Scenarios: Document Summarization, Sentiment Analysis
Day 3: Advanced Features and Data Integration with LlamaIndex#
Morning Sessions 9:00 AM to 1:00 PM#
9. Session 9 - Understanding LlamaIndex Architecture (9:00 AM - 10:30 AM)
- How LlamaIndex Enhances Data Access and Interaction
- Core Features: Indexing, Querying, and Retrieval
10. Session 10 - Data Integration with LlamaIndex (10:45 AM - 1:00 PM)
- Connecting to Structured and Unstructured Data Sources
- Working with Databases and File Systems
Lunch 1:00 PM to 2:00 PM
Afternoon Sessions 2:00 PM to 5:00 PM#
11. Session 11 - Query Optimization and Fine-Tuning (2:00 PM - 3:30 PM)
- Advanced Query Capabilities in LlamaIndex
- Fine-Tuning Models for Specific Use Cases
12. Session 12 - Hands-On: Building Data-Driven Applications (3:45 PM - 5:00 PM)
- Creating an Application that Combines LangChain and LlamaIndex
Day 4: Deployment, Scaling, and Capstone Project#
Morning Sessions 9:00 AM to 1:00 PM#
13. Session 13 - Deploying GenAI Solutions (9:00 AM - 10:30 AM)
- Strategies for Hosting AI Applications
- Integration with Cloud Platforms
14. Session 14 - Scaling and Monitoring AI Applications (10:45 AM - 1:00 PM)
- Techniques for Scaling GenAI Workloads
- Monitoring and Maintenance Best Practices
Lunch 1:00 PM to 2:00 PM
Afternoon Sessions 2:00 PM to 5:00 PM#
15. Session 15 - Capstone Project: End-to-End GenAI Solution (2:00 PM - 4:00 PM)
- Teams Build and Present a Complete GenAI Solution Using LangChain and LlamaIndex
16. Session 16 - Wrap-Up and Next Steps (4:00 PM - 5:00 PM)
- Key Takeaways
- Certification Distribution and Future Learning Pathways
Key Outcomes:#
- Master LangChain and LlamaIndex for developing GenAI solutions.
- Build custom conversational and data-driven AI applications.
- Integrate AI applications with diverse data sources.
- Deploy and scale GenAI solutions for enterprise environments.
Recommended Pre-Course Preparation:#
- Familiarity with Python and basic AI/ML concepts.
- Knowledge of APIs and database management.
- Review of LangChain and LlamaIndex documentation.
Materials Provided:#
- Course slides and code examples.
- Hands-on exercise files and datasets.
- Access to cloud environments for project work.
- Certificate of Completion.
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