Haystack – Build customizable LLM pipelines with AI Tools

Description

Price: 5.00 USD | Size: SIZE: 1.1 GB | Duration: 3.00+ Hrs
BRAND: Expert TRAINING | ENGLISH | INSTANT DOWNLOAD

Learn techniques for document search, RAG, question answering, and answer generation using Haystack components.

What you’ll learn:

• Haystack Foundations: Understand the fundamentals of Haystack 2.0, including its components and theoretical applications with real-world examples.
• Haystack 2.0 Concepts: Dive into Pipelines, Components, Document Store, and Retrievers.
• Advanced Haystack 2.0 Topics: Explore Hybrid Retrievers, Advanced Filtering, Self-Correcting Loops, and Rankers.
• RAG Pipeline: Get introduced to LLMs (from Guardrails), learn about Retrieval-Augmented Generation (RAG), and Vector Stores.
• Prompt Engineering: Master prompt engineering techniques such as Zero Shot, Few Shot, and Chain of Thought.

Requirements:

• This is not an introductory course. It is designed for individuals with a background in software engineering who are already proficient in Python.
• Students should be familiar with topics such as git, Python, pipenv, environment variables, classes, testing, and debugging.
• No prior experience in Machine Learning is needed.

Description:

Haystack is an end-to-end framework that supports every step of the GenAI project lifecycle. 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 comprehensive NLP applications.

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.

Course Content:

• Haystack Foundations: Learn the fundamentals of Haystack 2.0 and its components, along with theoretical applications.
• Real-World Applications: Implement Haystack components in real-world scenarios.
• Prompt Engineering: Understand prompt engineering techniques, including Zero Shot, Few Shot, and Chain of Thought.
• RAG Pipeline: Learn about Retrieval-Augmented Generation (RAG) and Vector Stores.
• Haystack 2.0 Concepts: Explore Pipelines, Components, Document Store, and Retrievers.
• Advanced Haystack 2.0 Topics: Study Rankers, Hybrid Retrievers, Advanced Filtering, and Self-Correcting Loops.

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, and business leaders looking to acquire skills in building generative AI-based applications with Haystack.
• Software engineers seeking to develop expertise in creating generative AI applications using Haystack.