LlamaIndex: Developing LLM Powered Applications Training Course
LlamaIndex is a robust indexing framework designed to extend the capabilities of Large Language Models (LLMs) by enabling them to effectively retrieve and leverage custom datasets.
This instructor-led, live training session (available online or on-site) is tailored for intermediate to advanced developers and data scientists seeking to master LlamaIndex for creating innovative LLM-driven applications.
Upon completing this training, participants will be capable of:
- Setting up and configuring LlamaIndex for integration with LLMs.
- Indexing and querying custom datasets via LlamaIndex to boost LLM performance.
- Architecting and building advanced applications that harness both LlamaIndex and LLMs.
- Grasping and applying best practices for working with LLMs and LlamaIndex.
- Navigating the ethical considerations associated with deploying LLM-powered applications.
Course Format
- Interactive lectures and discussions.
- Ample exercises and practical work.
- Hands-on implementation within a live laboratory environment.
Customization Options
- To arrange customized training for this course, please contact us.
Course Outline
Introduction to LlamaIndex
- Understanding LlamaIndex and its role in LLMs
- Setting up LlamaIndex: environment and prerequisites
- The basics of indexing custom data
LlamaIndex in Action
- Querying with LlamaIndex: techniques and best practices
- Building query and chat engines with LlamaIndex
- Creating intuitive Streamlit interfaces for LLM applications
Advanced LlamaIndex Features
- Employing retrieval-augmented generation (RAG) for enhanced data retrieval
- Leveraging vectorstores for efficient data management
- Designing and implementing LlamaIndex agents
Application Development with LlamaIndex
- Prompt engineering: chain of thought, ReAct, few-shot prompting
- Developing a documentation helper: a real-world LLM application
- Debugging and testing LLM applications
Deployment and Scaling
- Deploying LlamaIndex-based applications
- Scaling LLM applications for high performance
- Monitoring and optimizing LLM applications
Ethical and Practical Considerations
- Navigating ethical implications in LLM applications
- Ensuring privacy and data security with LlamaIndex
- Preparing for future developments in LLM technology
Summary and Next Steps
Requirements
- A solid understanding of Python programming and fundamental machine learning concepts.
- Experience with APIs and application development.
- Familiarity with natural language processing is advantageous but not mandatory.
Target Audience
- Developers
- Data scientists
Need help picking the right course?
southafrica@nobleprog.co.za or +27 (0)10 005 5793
LlamaIndex: Developing LLM Powered Applications Training Course - Enquiry
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