Ready to build smarter applications that leverage the power of generative AI (GenAI) and real-world data? This hands-on specialization guides you through the key tools and techniques for Retrieval-Augmented Generation (RAG) and gives you practical experience with vector databases, embedding models, and advanced retrieval frameworks like LangChain and LlamaIndex.
You’ll gain a strong foundation in GenAI fundamentals and prompt engineering, then get hands-on building applications that combine large language models with real-world data using similarity search. Plus, you'll work with advanced vector databases like Chroma DB and FAISS to power retrieval, create recommendation systems, and construct RAG workflows from the ground up.
By the end, you’ll know how to design, build, and evaluate RAG-enabled GenAIapps with integrated interfaces using tools like Gradio.
If you’re looking to boost your AI engineering skills and practically apply GenAI in production environments, this 12-week program gives you the job-ready skills to hit the ground running.
Enroll today and level up your resume in less than 3 months!
应用的学习项目
Throughout this specialization, you’ll gain valuable practical experience in hands-on labs and projects. By the end, you’ll have a demonstrable grasp of how to use vector databases for better data retrieval, how RAG works behind the scenes, and how to connect these systems to real applications. You’ll also build interactive tools using GenAI and deliver more useful responses by combining smart retrieval with language generation.
Some examples of the labs included are:
Master Prompt Engineering and LangChain Prompt Templates
Build Smarter AI Apps: Empower LLMs with LangChain
Summarize Private Documents using RAG, LangChain, and LLMs
Build an AI Icebreaker Bot with IBM Granite & LlamaIndex
Similarity Search on Text Using Chroma Vector DB
Analyzing Employee Data with Similarity Search
Semantic Similarity with FAISS
YouTube Summarizer and QA Tool
