Getting Started with AI

AI is a very broad field that requires different skills depending on the context, approach and problem that is addressed. Some people think that you need to be a coding expert, a math wiz or a brain researcher to do meaningful things with AI, but that is not necessarily the case.

KTHAIS is an open community and we want to encourage you and spark your curiosity for AI no matter your current level of understanding. Whether you are into programming, engineering, mathematics, statistics, psychology, business, neuroscience, music, or something completely different, we welcome you to contribute with what you know, participate and learn more.

AI can get very technical, but doesn't have to be. Depending on your ambition and prior expertise, you may choose different approaches. This post is intended as a starting point for your learning journey, according to your own ambitions. Non-technical content is marked ⭐️.

First steps

If you're completely new to AI, it's really helpful learn the fundamental terms and concepts. We recommend doing the freely available Elements of AI ⭐️ course. For an introduction to key AI technologies and implications, Introduction to AI gives a good conceptual understanding of the technology as well as the social and ethical aspects of AI. For something more technical, including Python programming exercises go for Building AI.

Elements of AI - Introduction to AI & Building AI

We regularly host a mini-course combining this material with keynote speakers. It makes for a more rewarding and social learning experience. Keep an eye out on our website, Facebook page or Slack so you don't miss it when it goes live.

For something more practical, check out our Tutorial Challenge: Decision Trees and Forests. A short Kaggle tutorial where you can get your hands dirty training two machine learning models, and get a sense of the ML workflow. A small time investment that really pays off.

Online Resources

There are so many online resources that we can hardly give a fair representation of what's out there. Below is a curated list of different resources that we like. They are grouped by what kind of resource it is, and we hope you can find something you like, pick out and combine different resources to find whatever helps you learn effectively.

If you have any feedback or suggestions for what we could add to this list, just let us know.

Video Lectures from Universities

Competitions and Learn-By-Doing (Data Science)


Blogs, News and Aggregators


Youtube Channels


Course platform MOOCs and Certificates

There are various course platforms with free/paid courses, guided projects, learning paths, certificates and even full degrees in AI fields. Search on for example edX, coursera or Udacity to find what you are looking for.

AI and other fields


Course books

Literature ⭐️

Courses at KTH

If you are a KTH student, you can take many courses within your program or as electives. There are various courses about or related to AI, most being masters-level courses that are technically advanced. DD2421 Machine Learning and DD2380 Artificial Intelligence are both good places to start.

Click here for the full list