Don’t wait for university to learn AI, you can start now for FREE.

Aymen Sekhri
Aug 26 · 5 min read
Elon Musk Quote

Most of the Students who are interested in the AI field are waiting for the university programs to learn this area. But Actually, This is wrong because everything is free on the internet. you can learn whatever field you want whenever, and wherever.

Additionally, Most people think about AI as a domain restricted to Computer Science students or IT students. but that’s wrong. anyone who has a basic background in Math (usually any Science Department teaches the Math -Algebra, Calculus, Probability, and Statistics- ) has the ability to start this field easily.

So, As a student — who knows a bit about Math — you don’t have to wait for university to teach you the AI field. you can start now from top universities in the world, They provide high-quality content in many areas, not just AI.

As an AI learner who start Learning two years ago, I asked many researchers in this field to guide me in the learning process and they always recommended probably the same resources, So I going to share these resources with you.

1 — Linear Algebra By Professor Gilbert Strang.

!! one of the most important universities in the world. That’s a dream for every student. but do you believe that all MIT Lectures and notes in many areas are free for you. So you can start with Linear Algebra the starting point in the AI field.

An Interview with Gilbert Strang on Teaching Linear Algebra

Link to the course:

2 — Calculus, Probability, and Statistics:

These are important also. but you can learn just the basics. Actually, we studied these majors in high school but you have to develop and understand well this three-domain because you will find lots of math in AI papers.

So I highly recommend platform. It is one of the best MOOCs in the world. They provide hundreds of courses for free (in both languages English and French).

Khan Academy

Link to Calculus course: (you will find here all Math courses)

Link to Statistics & Probability course:

Note: In , they also provide these courses but they are a bit longer and they need more time and much effort to complete, so if you prefer MIT you will find everything there.

3 — Introduction to Computer Science and Programming in Python:

Wow, This is one of my favorite courses ever provided by Dr. Ana Bell, If you are new to Programming you can start from here. you will enjoy learning in this course.

Dr. Ana Bell

Introduction to Computer Science and Programming in Python is intended for students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class uses the Python 3.5 programming language. — MIT OCW —

Link to the course:

4 — Introduction to Computational Thinking and Data Science:

This course is the complement of the previous course so, it is good if you complete this course also it will give you the full knowledge about Computational Thinking and the basic data science problems.

Dr. John Guttag teaching

This course is presented by

Link to the course:

5 — Machine Learning:

After finishing all the previous courses, Now you have the ability to start Machine Learning (which is the new paradigm of solving problems). And the famous course ever for this. it is provided by on .

Machine Learning Course

The course is very very famous (over 4 million enrolled in this course). This course provides a broad introduction to machine learning, data mining, and statistical pattern recognition.

Link to the course:

6 — Deep Learning Specialization:

Congratulations, you are almost there, Now let’s talk a bit about this specialization which is provided by Andrew Ng on Coursera.

Deep Learning Specialization — Coursera —

When you finish the Machine Learning course, now you can dive into the Deep Learning field. you will find many resources in top universities like MIT, NYU ..etc. but believe me, this Specialization is the best one it gives you all that you need to know about this area. It covers all major topics from Neural Networks to Convolutional NNs and Sequence Models.

AI is transforming many industries. The Deep Learning Specialization provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career. Along the way, you will also get career advice from deep learning experts from industry and academia.

— Coursera —

Link to the Specialization:

Note: You have to pay for Coursera courses, so if you want to get these courses for free, you should apply for financial aid. If you are wondering how to apply. Just leave a comment or send me an email, I will be happy to help you.

Conclusion:

Finally, when you finish all the courses, you can go deeper into the field of artificial intelligence, because deep learning is a big area and a lot of research comes out every day, so you should stay in touch with the field by reading papers and doing some projects or following workshops.
So here’s in a nutshell how to get started in AI, there are probably different roadmaps for that but this is one of them.
If you have any questions or comments, leave them in the comments or email me.

Email: asekhri@inttic.dz

Analytics Vidhya

Analytics Vidhya is a community of Analytics and Data…

Analytics Vidhya

Analytics Vidhya is a community of Analytics and Data Science professionals. We are building the next-gen data science ecosystem https://www.analyticsvidhya.com

Aymen Sekhri

Written by

AI & ML Enthusiast | Student at the National Institute of Information and Communications Technology (INTTIC). https://www.linkedin.com/in/aymensekhri1/

Analytics Vidhya

Analytics Vidhya is a community of Analytics and Data Science professionals. We are building the next-gen data science ecosystem https://www.analyticsvidhya.com