July 2024
Intermediate
1h 38m
English
Closed Captioning available in English
Overview
In this 1-hour course, you will delve into the realm of Retrieval-Augmented Generation (RAG) systems. Starting from foundational concepts, the course guides you through naive to advanced techniques, including query expansion and dense retrieval. Engaging hands-on examples ensure you can implement these systems effectively.
What I will be able to do after this course
- Understand the principles of Retrieval-Augmented Generation (RAG) systems.
- Apply advanced query expansion techniques to enhance information retrieval.
- Optimize document ranking using methods such as dense passage retrieval.
- Integrate cross-encoder re-ranking for improved generation accuracy.
- Design and implement practical RAG solutions for real-world AI applications.
Course Instructor(s)
Paulo Dichone is a seasoned AI specialist with a strong background in Natural Language Processing and information retrieval systems. With years of teaching experience and a focus on real-world applications, Paulo delivers practical, engaging, and comprehensible instruction tailored for learners eager to advance their technical skills.
Who is it for?
This course is ideal for AI developers looking to deepen their knowledge of advanced NLP systems, data scientists aiming to refine retrieval and generation techniques, and technical professionals seeking to enhance their expertise in RAG implementations. Prerequisites include basic familiarity with Python programming and AI concepts.
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