LlamaIndex: Developing LLM Powered Applications Training Course
LlamaIndex serves as a robust indexing framework designed to augment the capabilities of Large Language Models (LLMs) by enabling them to effectively retrieve and leverage custom datasets.
This instructor-led, live training—available either online or onsite—is tailored for intermediate to advanced developers and data scientists who aim to master LlamaIndex in order to create innovative applications driven by LLMs.
Upon completion of this training, participants will be able to:
- Install and configure LlamaIndex for integration with LLMs.
- Index and query custom datasets using LlamaIndex to improve LLM performance.
- Design and build sophisticated applications that harness both LlamaIndex and LLMs.
- Understand and implement best practices for working with LLMs and LlamaIndex.
- Navigate the ethical considerations associated with deploying LLM-powered applications.
Course Format
- Interactive lectures and group discussions.
- Extensive exercises and practical practice.
- Hands-on implementation within a live-lab environment.
Customization Options
- To request a tailored training version of this course, please contact us to make arrangements.
Course Outline
Introduction to LlamaIndex
- Understanding LlamaIndex and its role in the LLM ecosystem.
- Setting up LlamaIndex: environment setup and prerequisites.
- Basics of indexing custom data.
LlamaIndex in Practice
- Querying with LlamaIndex: techniques and best practices.
- Building query and chat engines using LlamaIndex.
- Creating intuitive Streamlit interfaces for LLM applications.
Advanced LlamaIndex Capabilities
- Implementing retrieval-augmented generation (RAG) for superior data retrieval.
- Leveraging vector stores for efficient data management.
- Designing and implementing LlamaIndex agents.
Application Development with LlamaIndex
- Prompt engineering strategies: chain of thought, ReAct, and few-shot prompting.
- Developing a documentation assistant: a practical real-world LLM application.
- Debugging and testing LLM applications.
Deployment and Scaling
- Deploying applications built on LlamaIndex.
- Scaling LLM applications for high performance.
- Monitoring and optimizing LLM application performance.
Ethical and Practical Considerations
- Navigating ethical implications in LLM applications.
- Ensuring privacy and data security when using LlamaIndex.
- Preparing for future advancements in LLM technology.
Summary and Next Steps
Requirements
- A solid understanding of Python programming and foundational machine learning concepts.
- Hands-on experience with APIs and application development.
- Familiarity with natural language processing is advantageous, though not mandatory.
Target Audience
- Software 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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