As Artificial Intilligence continue to explode, companies and businesses are looking for talented people to help them intigrate AI into their businesses .
One of the fasicanting field in AI is computer vision .
But how would I learn computer vision in 2025 ?
In this article I will breakdown the steps to learn and master the field .
Maths
I would start with the basic maths of computer vision : Calculus, Algebra, Statistics and Probability .
Learning these would help you have a solid understanding and you wont struggle learning the other theories of computer vision as these are the backbones of the field .
Python
Next, I will need to learn Python. Start with the basics such as variables, functions, classes.
When you have master these you can jump to machine learning libraries like Pandas, NumPy, Matplotlib and OpenCv .
These libraries are essential as it will save you a lot of time .
Learn Basic Modeling.
How can you train a machine learning model ? How to evaluate it ? How to make inference ? How to work with different datasets ? How to deploy it to production ?
I would suggest to learn about sickit-learn library . It has many built in machine learning architectures such as Linear regression, Random forests, Logistic regressions just to name a few !
You can import and use them right a way
Now you will move to the next level.
Learn about Neural Network
Dive into neural Network, theory behind it , try to implement it from scratch using NumPy only . Build models for real use cases and try to play around with the parameters and see what works best .
Learn about different activation functions, back propagations.
If you can try implement everything from scratch that will be extra .
Now pick a deep learning framework like Pytorch or Tensorflow .
I would suggest Pytorch as many state-of-the-art models built using Pytorch such as GPT .
Learn the basics of the framework and try to get used to it .
Explore CNN architecture
How deos it works ? Use it to build mini projects such as hand digits recognition and animal classification .
Bonus : Dont stuck on watching tuto, create your own projects and for each project you finish, try to deploy it to production and create documentation on how to use it .
Dont be selfish, when you have figure something new share it on public, someone may stuck and you have just helped them .
Read papers , implement them , create articles, conduct experiments on different models and publish your findings.
You have be more curious and hungry for knowledge .
Make sure you learn something new everytime, there is no end line in learning .
Remember, this field is all about experiment.
What work for other people deos not necessary means it will work for you . Them are not you , test by yourself and see what work and what didn’t
EXPERIMENT ,EXPERIMENT, EXPERIMENT !
And that is it , I hope you have find something useful here .