AI & LLM Engineering Mastery - GenAI, RAG Complete Guide
About this course
This specialization features Coursera Coach! Learn interactively through real-time conversations to test your knowledge, challenge assumptions, and deepen understanding. You will gain the skills to master AI and Large Language Models (LLMs), focusing on Generative AI (GenAI) and Retrieval-Augmented Generation (RAG). Through hands-on projects, you’ll build AI applications that process large datasets and generate meaningful outputs. By the end, you'll develop AI systems capable of understanding context, generating content, and integrating with various data sources. The course begins with setting up your development environment and reviewing Python fundamentals. You’ll then learn about LLMs, GenAI, and RAG architecture, before moving on to building and fine-tuning AI models. Topics include prompt engineering, API integration, and creating chatbots, summarizers, and personalized AI models. Designed for developers, data scientists, and AI enthusiasts, this course is for those with basic programming knowledge who want to explore advanced AI techniques. By the end, you'll be able to set up your environment, build LLM-based applications, and integrate RAG for AI-driven solutions.
75/100
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- What the provider tells you
- 39/45
- Who stands behind it
- 20/35
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- 16/20
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What you'll learn
- understand the architecture of LLMs, GenAI, and RAG
- set up a development environment for AI applications
- build and fine-tune AI models
- integrate different data sources into AI systems
- create chatbots and personalized AI models
Course objectives
- to gain mastery over AI and LLM technologies
- to learn through hands-on projects and interactive sessions
- to develop practical AI-driven solutions
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