Curated learning path for Information Retrieval. Build practical skills through expert-selected courses.
Basic probability concepts
Python fundamentals; string manipulation
Follow these courses in order to complete the learning path. Click on any course to enroll.
A university-level course on information retrieval, with all lecture videos and materials available for free online. The course covers fundamental concepts of search and ranking, including inverted indexes, ranking models like TF-IDF and BM25, and evaluation metrics. The lectures are in-depth and provide a strong theoretical foundation.
An extensive course on advanced Retrieval Augmented Generation (RAG) techniques using Llama Index and LangChain, created in collaboration with Llama Index. It covers industry-specific projects and features like Deep Memory for improved retrieval accuracy.
This course focuses on tuning Elasticsearch for low latency and high performance. It covers the index distribution architecture, cluster configuration, shards and replicas, similarity models, and advanced search techniques to improve the performance of search queries.
The OpenAI API is one of the most exciting advancements in the world of natural language and code processing.Its powerful models and flexible endpoints offer a wealth of possibilities for web developers looking to take their skills to the next level.In this comprehensive course, you will gain a deep understanding of the OpenAI API and its capabilities, along with hands-on experience in building your applications using Node JS, ReactJS, and NextJS.Whether you are a seasoned web developer or just starting, this course has something for everyone.What You Will Learn :The Completions Endpoint: at the heart of the OpenAI API, the completions endpoint is flexible enough to solve a wide range of language processing tasks, including content generation, summarization, semantic search, and sentiment analysis Models: explore the different models available through the OpenAI API, including the cutting-edge GPT-3 language model, and discover how they can be used to solve unique use cases Prompt Design and Settings: master the art of prompt design and settings and learn how they can impact the API's output Tokens: acquire a comprehensive understanding of tokens and how to use them to control the API's outputQuick Start Tutorial :In this course, you'll dive into the world of OpenAI and GPT-3 language models. Our focus will be on the completions endpoint and how it can be applied to text completion and various other language-processing tasks You'll learn how to use the OpenAI playground to experiment with code examples and understand the concepts of prompt design and settings, tokens, and models.The course will also include a Quick Star
The AI revolution is accelerating at an unimaginable pace, and those who master Large Language Models (LL Ms) and Agentic AI will define the future of technology. The "Large Language Models (LL Ms) & AI Agents Masterclass" is an intensive hands-on program designed to equip professionals and enthusiasts with the skills needed to build real-world AI applications. Whether you’re a developer, data scientist, researcher, or technology leader, this bootcamp provides the tools and knowledge to navigate and innovate in this fast-evolving space confidently.You will begin by exploring the foundations of LL Ms and agent frameworks, including how to benchmark models using LM Studio. The course then guides you through working with powerful closed-source AP Is from providers like OpenAI, Gemini, and Claude. You will learn how to structure system and user messages, understand tokenization, and control outputs to build projects such as AI-powered text generators and vision-enabled calorie trackers.As you advance, you’ll dive into the world of open-source LL Ms. You will fine-tune models on Hugging Face using state-of-the-art techniques like LoRA and Parameter-Efficient Fine-Tuning (PEFT). Alongside this, you’ll gain experience designing AI-powered web applications using Gradio, creating interactive streaming apps, and building intelligent AI tutors.A core component of the bootcamp focuses on mastering prompt engineering, including zero-shot, few-shot, and chain-of-thought prompting techniques to achieve consistent and controlled outputs. You'll also explore advanced capabilities such as building Retrieval-Augmented Generation (RAG) pipelines and working with embeddings for semantic search and knowledge retrieval.The program concludes with the development of next-generation AI agents. You will use frameworks like Auto Gen, OpenAI Agents SDK, Lang Graph, n8n, and MCP t
Explore related content to expand your skills beyond this learning path.
Enroll in this path to track your progress and stay motivated.