How I learned AI as a non-technical person in 4 months for free.

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This was around mid 2022, I was amongst the thoughts that in current times if you don’t understand technology then you are kind of illiterate. 

With technology affecting so much of our business, personal and social lives, it’s very easy to see yourself out of place. 

So, I decided to explore the latest technologies. The initial idea behind this was to at least understand what tech people say and not get completely lost.

I first started with Blockchain. I learned the basics of it, some solidity and for learning Javascript, I stumbled upon Sololearn

They have a basic AI/ML course as well and I took that. The course was good. It did give me an introduction to ML. 

On first look, it didn’t seem that tough as they covered basic maths, statistics, and a couple of Python libraries

But at that time my focus was Web3/ Blockchain and AI was not something I was looking to learn specifically. So, I didn’t pursue it and continued my journey of learning Web3. 

In case you are wondering, who am I? I am Nikhilesh Tayal –

Here is my LinkedIn profile –

Serious learning

As I learned Blockchain/ Web3, I had a startup idea of building a Blockchain based platform for ‘Mother creators’ to monetize their knowledge. 

While I was exploring that idea, we realised that this platform would require a few AI models and without those we would not be able to build our platform.

This prompted me to take up learning AI sincerely and was looking for the right approach to learning AI/ML.

The time was around mid-Nov 22 and I was discussing this with my friend – Amit Agrawal, CEO, Entit Consultancy Services

In order to help me, he introduced me to his friend – Manish Jain (a senior AI professional). He guided me and suggested this approach

So, as suggested, I started with a Machine learning specialization course available on Coursera. It is a free course if you opt for the “Audit this course” option. 

The course’s rating is 4.9/5 and with the first video itself, you understand why the course is so highly rated and recommended.

And no wonder, Andrew is so popular in AI communities.

Andew’s course was a good build-up to Sololearn’s course. You actually get the hang of ML and understand the AI world – what exactly it is, what it is made of, what it can do and what it takes to learn it.

The maths covered in this course can get overwhelming even for people who were good in it in classes 11 and 12. But my suggestion is – don’t spend too much time trying to understand it completely. 

Just understand what you can. Somehow, this maths is not at all required for practical purposes.

After completing the first course, I started Jeremy’s course but I found this course difficult at that time. I did force myself to watch 4 lecture videos but could not continue beyond that.

Deep learning

In one of Andrew’s lectures, he mentioned Kaggle – a community of Data Scientists by Google. I checked the community and saw a list of courses on it for data scientists. 

It took me almost 1 month to complete all the listed courses. I would say this is a treasure trove of knowledge which is available at no cost. I highly recommend these courses for complete beginners.

These courses combine theory with practical experience.

The courses are designed in such a way that once you complete them, the next step is to solve competitions listed on the website. I also did the same. 

But Kaggle courses are more for Data scientists. 

Though they have a couple of courses on Neural Networks and Computer Vision, I felt I yet not aware of how the latest AI works which we hear in the news and use on social media, for ex- Text to speech, Music generation, Large Language Models etc.

Basically, they lacked a) Computer Vision and b) Natural Language Processing (NLP). These 2 fields are building blocks of modern AI. 

So, I searched on Google and somehow again landed on Andrew’s Deeplearning’s advanced courses. Somehow I again found the treasure trove which is available at no cost. All you need to spend is your time. 

Learnings regarding Learning

By this time, I had been learning new technologies and coding for 9-10 months. And one of my learning regarding how to learn is – Don’t get stuck and don’t spend much time on something you don’t understand completely. 


  • Most of the time that thing would not be useful for practical purpose
  • Or you don’t need to understand it completely, a basic know how would be sufficient
  • Or you will understand that thing later with other concepts sinking in
  • Or if it’s really essential, you can always spend time later mastering it

So, following this approach, I took the following courses and completed them in about a month and a half.

Again, all the above courses are free if you opt for “Audit the course”. It’s just that you don’t get access to Practical Labs (which I was fine with).

After taking all the above-mentioned courses, you will be well aware of the AI world, and its terminologies and do not feel out of place when someone throws AI/ML words around 

But by this time, my hunger had increased.

Now, I just don’t want to be satisfied with the theoretical knowledge, but I want to build something and apply my knowledge to a practical scenario. Something useful. Something valuable.

Practical learning

As I was grappling with these thoughts, I recollected Jeremy’s course, which did not make sense earlier to me.

I thought I should check and see if I could understand that now. 

I did the same and this time it was a piece of cake. Jeremy tried to use Transfer Learning in the first lecture itself and created an image segmentation tool.

Using that course, I built a model that could distinguish between an infected plant and a healthy plant. 

Building that was fun.

While I was learning Blockchain, I took a couple of courses from Buildspace. One day I was just checking if they have any new courses and figured that they have a couple of AI courses

I took AI writing assistance using OpenAI API. 

Alongside AI courses, I also learned Python, Git, and Shell programming. I learned these through Sololearn, Udemy, Simplilearn and Upgrad. However, there are multiple websites to learn these. You can opt as per your convenience

A couple of other AI courses I found interesting were – 

  1. Andrej Karpathy –

(It’s a five video series) – If you are particularly interested in building NLP projects, you might find it interesting.

This course was suggested to me by Adarsh Jain

  1. PyTorch Fundamentals –

If you are especially interested in learning PyTorch, you may want to explore them.

Well, in my opinion, these above courses are sufficient for anybody to master AI. 

Don’t be intimidated by a four-month timeline. I used to learn for 4-6 hours a day and I have an average learning speed. You could learn and master AI faster.

Biggest Learning

No matter what you want to learn, no matter what background you come from, and no matter how old are you, you can learn anything if you develop an interest in that.

In case you would like to discuss anything related to AI, please connect with me on LinkedIn –

Thanks for choosing to read it completely.

Happy Learning!

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Nikhilesh Tayal
Nikhilesh Tayal
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