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Your complete guide to mastering AI, RAG, and model
fine-tuning through expert courses and resources
In this video, Andrew Ng explains the basics of generative AI—what it is, how it works, and why it’s becoming a transformative technology across industries. He breaks down complex concepts with simple examples to help anyone understand the foundation of modern AI.
Full Course →In this course, Rob Zuber explains how to test AI systems using modern LLM-based techniques. He covers rule-based and model-graded evaluations, and shows how continuous integration tools can automate testing to make AI applications more reliable and efficient.
Full Course →In this course, Isa Fulford and Andrew Ng explain how to write effective prompts for building real-world AI applications. You’ll learn practical techniques for guiding LLMs, explore new ways to use ChatGPT in development, and get hands-on experience creating and refining prompts with the OpenAI API.
Ful Course →In this video, Don Woodlock explains how Retrieval-Augmented Generation works and why it’s used to build AI systems that answer questions using your own internal data. He breaks down the RAG architecture with simple examples to show how it improves accuracy and makes AI responses more reliable.
In this course, Nikita Namjoshi explains how RLHF is used to align language models with human preferences. You’ll learn the core concepts behind the RLHF process, fine-tune a model using Google Cloud tools, and evaluate how human feedback improves model behavior.
This course by Harrison Chase walks through the latest advancements in LLM APIs and shows how to build powerful agents using LangChain’s new Expression Language (LCEL). You’ll learn how to compose tools, customize agent logic, and create a fully functional conversational agent using modern LLM capabilities.
Full Course →A short, practical DeepLearning.AI course that teaches the fundamentals of finetuning LLMs. Learn how finetuning differs from prompt engineering, when to use each technique, and how to work with real datasets to train and evaluate your own models.
Full Course →Get hands-on training directly from the source. In this beginner-friendly course, Harrison Chase guides you through the fundamentals of LangChain, including document loading, vector stores, and memory. By the end, you'll have a fully functional chatbot capable of interacting with specific information from your documents.
Full Course →A beginner-friendly short course (49 minutes) that teaches you how to quickly create and demo machine learning applications using Gradio. Learn to build image generation, image captioning, and text-summarization apps with just a few lines of code. The course covers creating user-friendly interfaces for non-coders, working with large language models, and sharing your apps on Hugging Face Spaces. Taught by Apolinário Passos, Machine Learning Art Engineer at Hugging Face, this free course includes 7 video lessons and 5 code examples to help you rapidly prototype and deploy AI applications.
Full Course →A beginner-level short course (1 hour 38 minutes) that teaches you how to build powerful LLM applications using the LangChain framework. Learn directly from Harrison Chase, the creator of LangChain, alongside Andrew Ng. This free course covers essential skills for expanding language model capabilities, including how to apply LLMs to proprietary data for building personal assistants and specialized chatbots, use agents and chained calls to enhance LLM functionality, and implement memories to manage conversations and context.
Full Course →In today's AI-driven software development environment, we need broad knowledge along with an in-depth specialisation. Reading and acquiring new knowledge can upskill people for today's environment of agility and DevOps
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