Welcome to our Resources page, your ultimate destination for curated and free educational content tailored for AI Engineers. Whether you're a seasoned professional or just beginning your journey in Artificial Intelligence, this page offers a comprehensive collection of top-notch tutorials and courses from around the web. Our goal is to provide you with the best resources to enhance your knowledge, sharpen your skills, and stay updated with the latest advancements in AI. Dive in and discover the wealth of information to help you excel in the dynamic field of AI engineering.

LangChain & Vector Databases in ProductionLearn about LLMs, LangChain, and Deep Lake vector database for all AI data with Activeloop, TowardsAI, & Intel Disruptor Initiative. Create efficient LLM-enabled apps in real-world scenarios.
Machine Learning in ProductionThe Machine Learning in Production course covers how to conceptualize integrated systems that continuously operate in production as well as solve common challenges unique to the production environment.
Retrieval Augmented Generation for Production with LangChain & LlamaIndexFree Course. Build Advanced Retrieval Augmented Generation Apps with LangChain & LlamaIndex. Learn to Build Multi-Modal Chat with Your Data Apps Across Industries
Training & Fine-Tuning LLMs for ProductionLearn to Train & Fine-Tune LLMs for Production. Build Custom Open-Source or Close-Source Models Across Industries. Learn to Fully Utilize Compute for LLMs.
Learn the fundamentals of generative AI for real-world applicationsIn Generative AI with Large Language Models (LLMs), created in partnership with AWS, you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.
TensorFlow: Advanced Techniques SpecializationIn this Specialization, you will expand your knowledge of the Functional API and build exotic non-sequential model types. You will learn how to optimize training in different environments with multiple processors and chip types and get introduced to advanced computer vision scenarios such as object detection, image segmentation, and interpreting convolutions.
Practical Deep Learning for Coders part 1This free course is designed for people (and bunnies!) with some coding experience who want to learn how to apply deep learning and machine learning to practical problems. Deep learning can do all kinds of amazing things. For instance, all illustrations throughout this website are made with deep learning, using DALL-E 2.
Practical Deep Learning for Coders part 2: Deep Learning Foundations to Stable DiffusionIn this course, containing over 30 hours of video content, we implement the astounding Stable Diffusion algorithm from scratch! That’s the killer app that made the internet freak out, and caused the media to say “you may never believe what you see online again”.
Intermediate: Gemini for Google Cloud Learning PathThe Gemini for Google Cloud learning path provides examples of how Gemini can help make engineers of all types more efficient in their daily activities. Gemini provides a natural language chat interface which you can quickly chat with to get answers to cloud questions, or receive guidance on best practices.
Machine Learning for Games CourseThis course will teach you the most fascinating topic in game development: how to use powerful AI tools and models to create unique game experiences.
Hugging Face Diffusion Models CourseIn this free course, you will: Study the theory behind diffusion models, Learn how to generate images and audio with the popular Diffusers library, Train your own diffusion models from scratch, Fine-tune existing diffusion models on new datasets
How to build your career in AIThis book delivers insights from AI pioneer Andrew Ng about learning foundational skills, working on projects, finding jobs, and joining the machine learning community. A practical roadmap to building your career in AI.
The Big Book of MLOps: 2nd EditionDiscover the latest strategies for deploying generative AI and machine learning models efficiently. The Big Book of MLOps covers how to collaborate on a common platform using powerful, open frameworks such as Delta Lake for data pipelines, MLflow for model management (including LLMs) and Databricks Workflows for automation.
A Beginner’s Guide to LLMsThe goal of this book is to help enterprises understand what makes LLMs so groundbreaking compared to previous solutions and how they can benefit from adopting or developing them. It also aims to help enterprises get a head start by outlining the most crucial steps to LLM development, training, and deployment.