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How would you learn more about AI: Highly recommended learning sources by our data scientists

Written by
Dulamsuren Bayaraa
Published on
June 16, 2023
Table of contents

Are you interested in expanding your knowledge of Artificial Intelligence (AI)? Maybe you're looking for practical AI solutions to integrate into your business — but you're not sure where to begin, or which learning sources are actually useful for someone without a technical background.

Good news: you're not alone — and you're not too late.

Our team has gathered trusted, beginner-friendly learning resources that will help you understand AI concepts, apply them to real-world scenarios, and even experiment with tools — all without needing to become a data scientist.

Who Are These For?

These sources are perfect if:

  • You’re new to AI and want a stress-free introduction
  • You’re a business owner or team leader looking to go more data-driven
  • You’re curious about automation, machine learning, and smarter decision-making
  • You don’t know how to code — and want to keep it that way

Online Courses

We recommend starting with these well-loved courses.

Platform & Course What Makes It Unique
Coursera – AI for Everyone by Andrew Ng
Best for: Non-technical professionals
Not a coding course, but a strategic overview of AI. Andrew Ng explains how AI impacts businesses and how to approach it thoughtfully. Ideal for marketers, executives, and team leads.
edX – CS50’s Introduction to AI with Python
Best for: Learners with coding experience
From Harvard’s CS50 team, this course teaches foundational AI concepts through real projects. It covers search algorithms, game-playing agents, and neural networks.
Udemy – Python for Data Science & ML Bootcamp
Best for: Beginners in tech
A practical, project-based course with guided coding lessons. Helps learners build real models using Python. Great for hands-on learners.
DeepLearning.AI – Machine Learning Specialization
Best for: Aspiring ML engineers
Offers a strong foundation in ML, led by Andrew Ng. It covers theory and implementation with code, plus new micro-courses on trending AI topics like LLMs and MLOps.
Uxcel – Psychology of UX & AI
Best for: Designers & product teams
Focuses on building intuitive, human-centered AI interfaces. Explains how to apply UX psychology when designing AI-powered products, from onboarding to personalization.

Books Worth Reading

Looking for insights you can enjoy at your own pace? These books break down AI concepts through real-world examples, humor, and business strategy.

Book Why It’s Worth Reading
Artificial Intelligence: A Guide for Thinking Humans
by Melanie Mitchell
An accessible, critical look at what AI can (and can’t) do — written in plain language. Great for anyone who wants a realistic view of AI's capabilities without hype.
You Look Like a Thing and I Love You
by Janelle Shane
A hilarious and insightful introduction to how AI works — through experiments, weird stories, and real-world fails. Perfect for beginners who want to learn without being overwhelmed.
Deep Learning
by Ian Goodfellow, Yoshua Bengio & Aaron Courville
The gold standard for technical readers. This is a textbook-level resource packed with theory, algorithms, and practical applications — used by universities and professionals alike.
Prediction Machines: The Simple Economics of Artificial Intelligence
by Ajay Agrawal, Joshua Gans & Avi Goldfarb
Explains AI in economic terms — showing how it affects business models, decisions, and costs. A smart choice for executives and entrepreneurs.

Hands-On Practice

If you prefer learning by doing, these platforms let you experiment and explore at your own pace:

Tool Why It’s Great
Kaggle Real datasets, guided notebooks, and competitions for beginner-level exploration.
Google Colab Run and edit machine learning code directly in your browser — no setup required.
Hugging Face Try powerful, pre-trained AI models like chatbots and text generators instantly with no installation needed.
NIKO AutoML A no-code AI platform that lets businesses build, train, and use models without technical skills — perfect if you want results, not code.

💬 Final Thoughts from Our Team

You don’t need to learn everything at once — just start small and stay curious.

We believe learning AI should feel exciting, not intimidating. These tools and resources were handpicked because they make AI feel human, approachable, and practical — just the way it should be.

If you're ready to explore what AI can do for you or your business, these are the best first steps.

Dulamsuren Bayaraa

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