Uncategorized AI October 8, 2025 0 Comments

If You Can`t Beat Em, Join Em. How and Where To Learn AI For Free

Numerous online platforms and tech companies offer free resources to learn about AI, from introductory concepts to more technical programming. Your best path depends on your background and specific interests, from understanding the basics to advanced technical development.

For beginners

Google AI Essentials

Focus: A quick, non-technical introduction to AI fundamentals.
Content: A course from Google that covers the basics of generative AI, its applications, and responsible use.
Where to find it: Grow with Google or Coursera.

DeepLearning.AI’s “AI for Everyone”

Focus: An introductory course for a general audience.
Content: Explains the possibilities and limitations of AI without deep technical details. Auditing the course is free on Coursera.
Where to find it: Coursera.

Microsoft’s “AI for Beginners”

Focus: A hands-on, beginner-friendly introduction to AI and machine learning.
Content: Offers short lessons and practical examples, such as building a simple neural network and an image classifier. It is an open-source project hosted on GitHub.
Where to find it: GitHub.

OpenAI Academy

Focus: For anyone looking to understand and apply AI tools.
Content: Features free enrollment and resources to learn about prompt engineering and how to integrate AI into daily tasks.
Where to find it: The OpenAI website.

For technical learning (with a programming background)

Fast.ai Practical Deep Learning

Focus: A “code-first” approach to deep learning.
Content: Teaches deep learning using the PyTorch framework, getting straight into coding without heavy theory.
Where to find it: The Fast.ai website.

Harvard’s CS50’s Introduction to Artificial Intelligence with Python

Focus: A foundational course for building an AI base with a popular language.
Content: Covers machine learning principles, neural networks, and more through problem sets.
Where to find it: The edX platform.

MIT Introduction to Deep Learning

Focus: A more intensive, graduate-level introduction to deep learning.
Content: A short but dense course covering neural networks, presented through lectures.
Where to find it: YouTube, and the course materials are on the MIT OpenCourseWare platform.

H2O.ai free AI and ML learning

Focus: Hands-on experience with an industry-leading AI platform.
Content: Courses and labs cover machine learning algorithms, automated machine learning (AutoML), and ethical AI.
Where to find it: The H2O.ai website.

For hands-on projects and community

Kaggle

Focus: A community and platform for data science and machine learning.
Content: Provides tutorials, datasets, and competitions to help you build practical skills by working on real-world problems.
Where to find it: The Kaggle website.

GitHub

Focus: A repository of code and projects, many open-source.
Content: Search for AI and machine learning projects and tutorials. You can contribute to open-source code and follow projects from top tech companies.
Where to find it: The GitHub website.

How to get started

Define your goals: Decide if you want a broad, non-technical overview or a deep, technical dive.
Start with the basics: If you have no programming experience, begin with an intro course like Google AI Essentials or DeepLearning.AI’s “AI for Everyone.”
Learn Python: If you want to get technical, Python is the most popular language for AI. There are many free tutorials to help you learn the fundamentals.
Practice hands-on: Combine courses with practical experience on Kaggle or by contributing to projects on GitHub.
Follow a roadmap: Consider a learning path like the one suggested on Reddit, starting with foundational knowledge and progressing to specific areas like deep learning and NLP.

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