Udemy – RAG and Generative AI with Python 2024 2024-9

Published on: 2024-09-16 22:28:02

Categories: 28

Descriptions

RAG and Generative AI with Python 2024, As the amount of digital content grows exponentially, it becomes increasingly challenging to create AI models that can efficiently sift through vast data to provide accurate and meaningful responses. Traditional search engines and basic AI models often fall short in delivering the context-aware results needed in today’s fast-paced digital landscape. RAG and Generative AI with Python is designed to solve this problem by teaching you how to build powerful Retrieval-Augmented Generation (RAG) systems using Python. This course will guide you through the essentials of combining retrieval techniques with generative models to develop applications that are both highly responsive and contextually accurate. This course is perfect for data scientists, software developers, AI enthusiasts, and anyone with a basic knowledge of Python who wants to build smarter, more efficient AI systems. If you’re ready to overcome the limitations of traditional models and lead the charge in AI innovation, this course is for you. Take the next step in your AI journey with RAG and Generative AI with Python and learn how to create the advanced AI tools that the world needs now. Enroll today and start transforming the way you build AI systems!

What you’ll learn

Gain a solid foundation in information retrieval concepts, including tokenization, preprocessing, indexing, querying, and ranking.
Implement various retrieval models in Python, such as the Vector Space Model, Boolean Retrieval, and Probabilistic Retrieval, using real-world datasets.
Understand how text generation models work, including the principles behind transformers and attention mechanisms.
Acquire hands-on experience in using Python libraries to build, fine-tune, and deploy generative models like GPT for various text generation tasks.
Learn how to effectively combine retrieval and generative models to build robust Retrieval-Augmented Generation (RAG) systems.
Utilize Python for advanced RAG system components, such as tokenization, embedding creation, FAISS indexing, and context distance definition.

Who this course is for

Data Scientists and Machine Learning Engineers looking to deepen their knowledge of generative AI systems.
AI Researchers and Enthusiasts interested in exploring the latest advancements in (RAG) and generative AI technologies.
oftware Developers and Programmers who want to expand their skill set to include AI and machine learning techniques.
Technical Product Managers and AI Strategists who manage AI projects and need a deeper technical understanding of how RAG systems work and their potential applications.
AI Consultants and Data Analysts aiming to add AI capabilities to their skillset