A curated list of 43 free AI courses and learning hubs, sorted by topic with level and direct links in the last column. Start with the official academies if you want structured paths from the model providers.
🏫 Official AI academies
| Resource | Level | What you'll learn | Link |
|---|---|---|---|
| Claude Academy | All levels | Free courses, tutorials, and use cases from Anthropic on using Claude safely, effectively, and with intention. | Open on academy.claude.com → |
| Microsoft Learn — Copilot training | All levels | Browse Copilot-focused learning paths, modules, and certifications on Microsoft Learn. | Open on learn.microsoft.com → |
| OpenAI Academy Courses | All levels | Practical tracks for everyday work, building with the API and Codex, leading adoption, and teaching with AI — with assessments and badges. | Open on academy.openai.com → |
🧠 AI Foundations
| Resource | Level | What you'll learn | Link |
|---|---|---|---|
| Generative AI for Beginners (Microsoft) | Beginner | Learn how generative AI works with 18 lessons, hands-on demos, and GitHub code samples. | Open on learn.microsoft.com → |
| Microsoft AI Introduction Course | Beginner | Get a foundation in AI: terminology, machine learning, neural networks, and deep learning. | Open on learn.microsoft.com → |
| Elements of AI (University of Helsinki) | Beginner | Globally popular, non-technical introduction to AI, its applications, and limitations. | Open on elementsofai.com → |
| AI for Everyone (Andrew Ng, Coursera Audit) | Beginner | Non-technical overview of AI’s impact and how businesses adopt it. | Open on coursera.org → |
| Harvard – Introduction to AI with Python | Beginner | 7-week course covering search algorithms, neural networks, and reinforcement learning. | Open on cs50.harvard.edu → |
| Fundamentals of Deep Learning (NVIDIA) | Beginner–Intermediate | Hands-on training in neural networks, image recognition, and text analysis. | Open on courses.nvidia.com → |
| AI in the Data Center (NVIDIA) | Intermediate | Covers AI workflows, GPU architecture, and infrastructure for deep learning. | Open on learn.nvidia.com → |
| Accelerate Data Science Workflows with Zero Code Changes (NVIDIA) | Intermediate | Learn how to use GPU acceleration in data science without modifying code. | Open on learn.nvidia.com → |
| Accelerating Data Engineering Pipelines (NVIDIA) | Intermediate | Optimize pipelines with GPU acceleration for large-scale data processing. | Open on learn.nvidia.com → |
✍️ Prompt Engineering
| Resource | Level | What you'll learn | Link |
|---|---|---|---|
| Prompt Engineering for ChatGPT (Vanderbilt University) | Beginner–Intermediate | 6-module course on effective prompting strategies for better outputs. | Open on coursera.org → |
| ChatGPT Prompt Engineering for Developers (OpenAI + Andrew Ng) | Intermediate | Hands-on best practices for prompting in applications. | Open on learn.deeplearning.ai → |
| AI Applications & Prompt Engineering (edX) | Intermediate | Introductory course combining prompt engineering with applied AI use cases. | Open on edx.org → |
🤖 Generative AI & LLMs
| Resource | Level | What you'll learn | Link |
|---|---|---|---|
| Introduction to Generative AI (Google Cloud) | Beginner | Covers fundamentals of generative AI and real-world applications. | Open on cloudskillsboost.google → |
| Generative AI Explained (Google Cloud) | Intermediate | Dive deeper into how generative AI works, its limitations, and future potential. | Open on cloudskillsboost.google → |
| 5-Day Generative AI Intensive (DeepLearning.AI) | Intermediate | Project-based deep dive into GANs and transformers. | Open on learn.deeplearning.ai → |
| Introduction to Large Language Models (Google Cloud) | Intermediate | Learn what LLMs are, how they function, and their applications. | Open on cloudskillsboost.google → |
| LLMOps (Google Cloud + DeepLearning.AI) | Advanced | Full lifecycle management of LLMs, from preprocessing to deployment. | Open on coursera.org → |
| Augment Your LLM with Retrieval-Augmented Generation (NVIDIA) | Advanced | Use RAG to combine retrieval with generation for better performance. | Open on learn.nvidia.com → |
| Building RAG Agents with LLMs (LangChain/NVIDIA) | Advanced | Learn scalable deployment with vector databases and LangChain. | Open on learn.nvidia.com → |
| Vector Search and Embeddings (Google Vertex AI) | Intermediate–Advanced | Hands-on with embeddings and semantic search systems. | Open on cloud.google.com → |
| Inspect Rich Docs with Gemini Multimodality + RAG | Advanced | Use multimodal AI to process text and images with retrieval-augmented generation. | Open on ai.google → |
🖼️ AI for Images & Creativity
| Resource | Level | What you'll learn | Link |
|---|---|---|---|
| Image Generation (NVIDIA) | Intermediate | Learn how to train and deploy models for generating images. | Open on learn.nvidia.com → |
| Getting Started with AI on Jetson Nano (NVIDIA) | Intermediate | Build image classification models on NVIDIA’s Jetson Nano hardware. | Open on developer.nvidia.com → |
🔎 Core Architectures
| Resource | Level | What you'll learn | Link |
|---|---|---|---|
| Encoder–Decoder Architecture (Google Cloud) | Intermediate | Foundation for models used in translation and summarization. | Open on cloudskillsboost.google → |
| Transformers & BERT Models (Google Cloud) | Intermediate | Learn about Transformers and BERT, two pillars of modern NLP. | Open on cloudskillsboost.google → |
| Attention Mechanism (Google Cloud) | Advanced | Deep dive into how attention improves AI models. | Open on cloudskillsboost.google → |
📊 Applied AI
| Resource | Level | What you'll learn | Link |
|---|---|---|---|
| Mastering Recommender Systems (DeepLearning.AI + Kaggle) | Advanced | Covers candidate generation, ensembling, and optimization for recommender systems. | Open on learn.deeplearning.ai → |
| Big Data, Artificial Intelligence & Ethics (UC Davis) | Intermediate | Understand big data, AI applications, and their ethical limitations. | Open on coursera.org → |
🎓 Extra Resources
| Resource | Level | What you'll learn | Link |
|---|---|---|---|
| Machine Learning Specialization (Andrew Ng, Coursera Audit) | Beginner–Intermediate | Linear regression, classification, supervised/unsupervised learning. | Open on coursera.org → |
| Deep Learning Specialization (Andrew Ng, Coursera Audit) | Intermediate–Advanced | Covers CNNs, RNNs, sequence models, optimization. | Open on coursera.org → |
| Introduction to Computer Vision (Georgia Tech, Udacity) | Intermediate | Basics of computer vision and object recognition. | Open on udacity.com → |
| Intro to TensorFlow for Deep Learning (Udacity, Google) | Beginner–Intermediate | Learn TensorFlow to build and train deep learning models. | Open on udacity.com → |
| Natural Language Processing with Classification & Vector Spaces (Coursera Audit) | Intermediate | NLP basics with embeddings, classification, and semantics. | Open on coursera.org → |
| AI for Medicine (Coursera Audit) | Intermediate | Applications of AI in diagnostics, treatment, and personalised care. | Open on coursera.org → |
| Practical Deep Learning for Coders (fast.ai) | Intermediate–Advanced | Hands-on, code-first course to train real models quickly. | Open on course.fast.ai → |
| Hugging Face – NLP Course | Intermediate | Work with Hugging Face Transformers and fine-tuning models. | Open on huggingface.co → |
| Stanford CS224N: NLP with Deep Learning | Advanced | Popular academic NLP course, includes lectures and assignments. | Open on web.stanford.edu → |
| MIT – Generative AI & Foundation Models (MIT OpenCourseWare) | Advanced | Lectures on large-scale models, training, and applications. | Open on introtodeeplearning.com → |
| IBM AI Engineering Professional Certificate (Coursera Audit) | Intermediate–Advanced | Covers ML, DL, NLP, and deployment pipelines. | Open on coursera.org → |
| AWS Machine Learning Foundations (Udacity) | Beginner–Intermediate | Learn ML concepts using AWS tools and workflows. | Open on udacity.com → |
Tip: Many Coursera links support free audit — choose “Audit” at enrollment if you do not need a certificate.
