Udacity

AI Engineering Lab is a free, self-paced 24-week AI engineering course developed by Zorost Intelligence AI Lab. It takes learners from Python and machine learning through deep learning, LLM internals, prompt and context engineering, retrieval-augmented generation with vector search, quantization, LoRA and DPO fine-tuning, evaluation harnesses, coding-agent harnesses, AI agents, MCP, and cloud and Databricks platforms including Azure AI Foundry, Google Vertex AI, AWS Bedrock, and Databricks. The curriculum uses one continuous fictional freight-company case study. Each week pairs a concept with a runnable Python, SQL, or PySpark artifact; from Week 3 onward, the work includes a metric and an error note. The repository contains 43 runnable notebooks, publishes the full curriculum online, requires no signup or paid API key, and states that the first eight weeks require no GPU. It is MIT licensed.

DeepLearning.AI courses is an online catalog of AI education from DeepLearning.AI, covering prompting, retrieval-augmented generation, agents, generative models, LLM operations, search and retrieval, AI coding, and related subjects. The catalog is organized into short courses, broader courses, and professional certificates with beginner and intermediate levels, topic filters, and collaborator listings. Featured courses include AI Prompting for Everyone, Build with Andrew, and Agentic AI; the video notes that many courses are free and can be audited.

MEGA is a four-week online learning program for developers who already build with AI. Taught by Kent C. Dodds, Angie Jones, John Lindquist, and Theo Browne, it combines 20 weekday lessons, written companions, real repositories, and weekly live workshops. Its curriculum progresses from the mechanics of generative AI and context-based model steering to agent frameworks, tools, memory, MCP, multi-agent collaboration, reliability, AI-native product development, verification, autonomous systems, orchestration, and self-improving engineering systems.

AI Engineering Hub is a curated learning repository covering LLMs, retrieval-augmented generation, AI agents, model development, MCP, and production AI systems. It organizes more than 90 example projects and tutorials by beginner, intermediate, and advanced difficulty, including OCR and chat interfaces, RAG workflows, multi-agent systems, voice applications, fine-tuning, model comparisons, deep research, and deployment. The repository also includes an AI engineering roadmap, welcomes contributions through forks and pull requests, and is licensed under the MIT License.

AI Studio is a platform for creating, testing, and beginning to use managed agents, including applications that showcase agent capabilities. The videos describe it as a place to build applications such as a stock-research app using managed agents that run in cloud sandboxes.