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Firstlink Consulting

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.

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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

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

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What's inside

Learning objectives

  • 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

Syllabus

Introduction
Local Environment Setup
General Concepts
Vector Embedding
Read more
RAG - Retrieval Augmented Generation
Learn about Haystack concepts with real world examples
Haystack Pipelines
Pipeline Real World Example
Haystack Components
Haystack Custom Component
Haystack Components Real World Example
Document Store with Real World Example
Retrievers with Real World Example
Evaluator with Real World Example
First RAG Pipeline
RAG Pipeline
Prompt Builder
Prompt Builder with Real World Example
Haystack 2.0 Advanced Topics
Hybrid Revtrieval
Self Correcting Loops
ReRankers
Metadata Filtering
Agentic Pipeline/Function Calling with ChatGPT
Build Agentic Pipelines using OpenAI's Function Calling
Evaluating Rag Pipeline using Evaluators
Haystack Integration with RAGAS evaluator

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Builds foundational skills in using Haystack 2.0 to develop LLM applications with modern, up to date concepts and methods
Provided with hands-on exercises and real-world projects to solidify understanding of concepts and methods
Covers advanced topics such as Re-Ranker, Hybrid Retriever, Advanced Filtering, Self Correcting Loops, Agentic Pipeline using ChatGPT's function calling and more
Specifically designed for AI developers, data scientists, business leaders to acquire skills in building generative AI-based applications with Haystack
Taught by Firstlink Consulting, instructor specializing in data science and AI

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Haystack - Build customizable LLM pipelines with AI Tools with these activities:
Attend a Haystack Meetup
Connect with fellow learners and experts in the Haystack community.
Show steps
  • Locate and register for a Haystack meetup in your area.
  • Attend the meetup and actively participate in discussions.
Review NLP fundamentals
Reviewing NLP and Haystack's fundamental principles can strengthen your knowledge foundation, improving comprehension throughout the course.
Browse courses on NLP
Show steps
  • Go over key NLP concepts like tokenization, stemming and lemmatization, and text processing
  • Research Haystack's architecture and explore its components, including Document Store, Retrievers, and Evaluators
  • Brush up on vector embeddings, their types, and their applications in NLP
Note Compilation and Review
Organize and review notes, assignments, and other course materials to reinforce concepts.
Show steps
  • Gather all relevant materials from the course
  • Organize and categorize the materials
  • Summarize key concepts and insights
21 other activities
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Review Vector Embedding Techniques
Reinforce knowledge of vector embedding techniques to support understanding of Haystack's underlying mechanisms.
Browse courses on Embeddings
Show steps
  • Revisit documentation on word embedding techniques, such as Word2Vec and GloVe.
  • Practice using libraries like Gensim or spaCy to generate word embeddings from text.
Brush Up on Vector Embedding
Recall the basics of vector embedding to strengthen your understanding of Haystack's vector embedding capabilities.
Browse courses on Word Embeddings
Show steps
  • Review online articles or tutorials on vector embedding concepts.
  • Complete a short online course or workshop on vector embedding.
Explore Haystack's official documentation
Delve into Haystack's official documentation to deepen your understanding of its capabilities and how to harness them effectively.
Show steps
  • Navigate the documentation to find comprehensive explanations of Haystack's core concepts and components
  • Examine code examples and tutorials to gain practical insights into using Haystack's features
  • Utilize the documentation's search functionality to quickly locate specific information and resolve queries
Engage in peer discussions
Engaging in peer discussions can broaden your perspectives, enhance understanding, and foster a collaborative learning environment.
Show steps
  • Connect with classmates or join online forums to participate in discussions related to Haystack and LLM applications
  • Actively listen to diverse viewpoints, ask clarifying questions, and contribute your own insights to enrich the discussions
  • Collaborate on projects or assignments with peers to leverage collective knowledge and support
Practice Building Haystack Pipelines
Reinforce your understanding of Haystack pipelines by working through practice exercises.
Show steps
  • Follow along with the course's guided tutorials on building pipelines.
  • Create your own custom pipelines using Haystack's components.
Prompt Engineering Exercises
Engage in exercises to refine prompt engineering skills and improve the performance of LLMs.
Show steps
  • Practice writing zero-shot prompts
  • Experiment with different prompt formats
  • Use chain-of-thought prompting to guide LLM responses
Build a Simple RAG Pipeline with Haystack
Solidify understanding of Haystack's RAG capabilities through practical implementation.
Show steps
  • Follow a guided tutorial to set up a basic RAG pipeline.
  • Experiment with different retrieval strategies, such as BM25 and DPR.
Explore advanced Haystack features with tutorials
Deepen your understanding of advanced Haystack features by following guided tutorials.
Show steps
  • Utilize Haystack's advanced features such as Re-Rankers, Hybrid Retrievers, and Self Correcting Loops.
  • Integrate Haystack with OpenAI's function calling capability.
Construct a Haystack pipeline
Creating a Haystack pipeline will provide hands-on experience in designing and implementing NLP solutions, solidifying your understanding of the framework.
Show steps
  • Identify a specific NLP task or problem that you want to address using Haystack
  • Design the pipeline architecture, selecting appropriate components such as Document Store, Retriever, and Evaluator
  • Implement the pipeline using Haystack's Python API, connecting the components and configuring them based on your requirements
  • Test and evaluate the performance of your pipeline, making adjustments as necessary to optimize its effectiveness
Collaborate on a Haystack Project
Enhance learning by working with peers on a Haystack-based project.
Show steps
  • Find a study partner or group with similar interests.
  • Brainstorm and select a project idea that aligns with course objectives.
  • Collaborate on implementing the project, dividing tasks and responsibilities.
  • Present and discuss project outcomes, sharing insights and learnings.
Develop an LLM-based Application using Haystack
Apply your Haystack knowledge to create a tangible LLM-based application that solves a real-world problem.
Show steps
  • Identify a problem or use case that can be solved with an LLM.
  • Design and implement a Haystack pipeline to address the identified problem.
  • Deploy and evaluate the developed application.
Document Store Optimization Report
Analyze and optimize a Haystack Document Store to enhance the efficiency of your NLP applications.
Show steps
  • Identify areas for improvement in the Document Store
  • Explore different indexing strategies
  • Implement query optimization techniques
  • Create a report summarizing your findings and recommendations
  • Present your report to stakeholders or peers
Build a Conversational AI chatbot using Haystack
Apply your Haystack knowledge to create a conversational AI chatbot that interacts with users in a natural language.
Show steps
  • Design the chatbot's architecture and functionality.
  • Implement a Haystack pipeline for the chatbot's natural language processing.
  • Train and evaluate the chatbot.
Contribute to the Haystack community
Contributing to the Haystack community allows you to deepen your understanding of the framework, engage with its developers, and make a meaningful impact.
Show steps
  • Explore the Haystack GitHub repository to identify areas where you can contribute
  • Submit bug reports or feature requests to enhance the framework and its documentation
  • Contribute code improvements, new features, or documentation updates to the project
  • Engage with the Haystack community on forums or social media to share knowledge and support others
Create a Visual Guide to Haystack Concepts
Develop a deeper understanding of Haystack concepts by creating visual representations.
Browse courses on Visual learning
Show steps
  • Identify key concepts from Haystack documentation and tutorials.
  • Sketch out visual representations, such as diagrams, flowcharts, or infographics.
  • Use design tools or software to create visually appealing and informative graphics.
  • Share the visual guide with others, providing explanations and insights.
Custom Haystack Pipeline Project
Build a customized Haystack pipeline for a specific use case to solidify course concepts.
Show steps
  • Define a specific problem or task for NLP
  • Research and choose appropriate Haystack components
  • Design and implement your custom pipeline
  • Evaluate and refine your pipeline's performance
RAG-based Question Answering System
Develop a question answering system powered by Haystack's RAG Pipeline to extract answers from unstructured text.
Show steps
  • Gather and prepare a dataset for question answering
  • Set up a RAG Pipeline with a suitable retriever and reader
  • Train and evaluate your question answering system
Contribute to Haystack's Documentation
Enhance your understanding of Haystack while contributing to its community.
Browse courses on Community Involvement
Show steps
  • Identify areas in Haystack documentation that need improvement or expansion.
  • Research and gather relevant information to enhance the documentation.
  • Submit a pull request to Haystack's GitHub repository.
  • Collaborate with maintainers to refine and merge your contributions.
Chatbot Project using Hybrid Retriever
Build a chatbot application using Haystack's Hybrid Retriever for improved conversational responses.
Show steps
  • Design a conversational interface
  • Integrate Haystack's Hybrid Retriever
  • Train and fine-tune the chatbot model
  • Evaluate and iterate on the chatbot's performance
Build a Haystack-Based Question Answering System
Apply your knowledge of Haystack to develop a practical application.
Show steps
  • Gather a dataset of questions and answers relevant to your domain.
  • Design and implement a Haystack pipeline for question answering.
  • Evaluate and refine your system's performance using metrics like accuracy and F1-score.
  • Deploy and share your system for use by others.
Community Contributorship
Contribute to the Haystack community by participating in discussions, reporting issues, or assisting other users.
Show steps
  • Join the Haystack community forum or discussion groups
  • Identify areas where you can contribute your knowledge or expertise
  • Participate in discussions, answer questions, or report issues

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