The good news is there are incredible free resources available for almost every aspect of AI.
- Elements of AI (University of Helsinki & MinnaLearn): This is an excellent starting point for everyone, even without a strong math or programming background. It covers the basics of what AI is, how it's created, and its societal impact. It has two parts: "Introduction to AI" and "Building AI."
- Why it's great: Demystifies AI, no complicated math, practical exercises.
- Where to find it: elementsofai.com
- Google AI Essentials / Grow with Google AI Courses: These courses are designed for a broad audience and focus on practical applications and basic concepts.
- Why it's great: Very practical, focused on using AI tools.
- Where to find it: grow.google/ai/
- IBM SkillsBuild - Free Artificial Intelligence Course: Offers foundational understanding and some hands-on experience like building a chatbot.
- Where to find it: skillsbuild.org/students/course-catalog/artificial-intelligence
- Microsoft's AI for Beginners: A comprehensive curriculum covering various AI approaches, neural networks, computer vision, NLP, and more, with code examples in TensorFlow and PyTorch.
- Why it's great: Covers a broad range of AI topics, includes coding.
- Where to find it: microsoft.github.io/AI-For-Beginners/
- DeepLearning.AI (Andrew Ng): Offers numerous free short courses and introductory specializations. While many courses require a paid subscription for certificates, the content itself is often freely auditable or available as short courses that are completely free.
- Key free courses:
- "AI for Everyone" (high-level overview, non-technical)
- "ChatGPT Prompt Engineering for Developers" (learn to use LLMs effectively)
- "Large Multimodal Model Prompting with Gemini" (specifically for Google's Gemini model)
- Why it's great: Taught by industry leaders, very practical, often code-focused.
- Where to find it: deeplearning.ai/courses/
- Key free courses:
- Google Cloud Training - Machine Learning & AI Courses: Offers many free courses and skill badges focusing on Google Cloud's AI services (Vertex AI, BigQuery ML, TensorFlow). This is excellent if you plan to use cloud-based AI.
- Why it's great: Practical, cloud-focused, industry-relevant.
- Where to find it: cloud.google.com/learn/training/machinelearning-ai
- Coursera (Audit Option): Many courses on Coursera allow you to "audit" them for free, meaning you can access most of the lecture videos and readings, but not graded assignments or certificates. Look for courses from universities like Stanford, DeepLearning.AI, IBM, and Google.
- Recommended search: "Machine Learning," "Deep Learning," "Natural Language Processing," "Computer Vision."
- Why it's great: High-quality academic content.
- Where to find it: coursera.org (look for "Audit" or "Enroll for Free" options)
- edX (Audit Option): Similar to Coursera, many edX courses from top universities can be audited for free.
- Why it's great: High-quality academic content.
- Where to find it: edx.org (filter for "Free" courses)
- Udemy (Free Courses): Udemy has a section for free AI courses, often shorter intros to specific topics.
- Where to find it: udemy.com/topic/artificial-intelligence/free/
- YouTube Channels: Many experts and organizations share free tutorials and lectures.
- Examples: freeCodeCamp.org, Krish Naik, sentdex, Jeff Heaton's Python for Machine Learning.
- Kaggle: A platform for data science and machine learning competitions. It offers free courses, datasets, and a code environment (Jupyter Notebooks in the browser) to practice building and training models.
- Why it's great: Real-world datasets, active community, excellent for hands-on learning.
- Where to find it: kaggle.com
- Google Colab: Provides free access to GPUs, allowing you to run Python code with TensorFlow and PyTorch directly in your browser without needing powerful hardware. Essential for practicing deep learning.
- Where to find it: colab.research.google.com