What you'll learn:
- Learn fundamentals of Haystack 2.0. Haystack theory with hands on examples
- Haystack 2.0 Concepts: Pipelines, Components, Document Store, Retrievers, Evaluators
- Haystack 2.0 Advance Topics : Re-Ranker, Hybrid Retriever, Advanced Filtering, Self Correcting Loops, Agentic Pipeline using OpenAI's function calling
- Prompt Engineering : Learn prompt engineering techniques - Zero Shot, Few Shot and Chain of Thoughts
- Model Based Evaluators - Faithfulness Evaluator(LLM-As-A-Judge), SAS Evaluator, Context Relevance Evaluator
- Advanced Retrieval Techniques : Filter Retriever, Sparse Keyword Based Retriever, Dense Embedding Retriever and Sparse Embedding Retriever - SPLADE
- RAG Pipeline: Learn about RAG, Vector store
Haystack is an end-to-end framework that accompanies you in every step of the GenAI project life cycle. Whether you want to perform document search, retrieval-augmented generation (RAG), question answering, or answer generation, Haystack can orchestrate state-of-the-art embedding models and LLMs into pipelines to build end-to-end NLP applications and solve your use case.
This beginner to advanced all-encompassing course aims to swiftly show you how to leverage the Haystack 2.0 library for LLM applications. You will acquire the expertise and insights required to create state-of-the-art LLM solutions across a wide array of subjects.
What you'll learn:
Haystack Foundations : Understand fundamentals of Haystack2.0 by learning Haystack components. Haystack theory with hands on example
Real-World Applications : Implement Haystack components with real world applications
Prompt Engineering : Learn prompt engineering techniques - Zero Shot, Few Shot and Chain of Thought
RAG Pipeline : Learn about RAG, Vector store
Haystack 2.0 Concepts : Pipelines, Components, Document Store, Retrievers, Evaluators
Advanced Retrieval Techniques : Filter Retriever, Sparse Keyword Based Retriever, Dense Embedding Retriever and Sparse Embedding Retriever - SPLADE(Sparse Lexical and Expansion Model)
Model Based Evaluators - Faithfulness Evaluator(LLM-As-A-Judge), SAS Evaluator, Context Relevance Evaluator
Haystack 2.0 Advance Topics : Re-Ranker, Hybrid Retriever, Advanced Filtering, Self Correcting Loops, Conversation/Agentic Pipeline using OpenAI's function calling, LLM-As-A-Judge, Model Based Evaluation
React Prompt and FastRAG : Build Multi Agentic pipelines with React Prompt
During the course, you will engage in practical exercises and real-world projects to solidify your grasp of the concepts and methods discussed. By the course's conclusion, you will be skilled in utilizing Haystack to develop robust, efficient, and adaptable LLM applications for a broad range of uses.
Who Should Enroll:
AI developers, data scientists, business leaders looking to acquire skills in building generative AI-based applications with Haystack
