This repository and the accompanying course guide (in PDF format) are designed to help you on your journey toward becoming a Data Science, Machine Learning, or AI Engineering professional.
There are many platforms, such as Coursera, edX, Udacity, Udemy, etc..... that now even offer opportunities to pursue a Master's degree in these fields.
While these programs are valuable and well-credited by the institutions offering them, they can still be prohibitively expensive for many people around the world.
With annual tuition fees often reaching $10,000, $20,000, or even $50,000, this guide aims to provide alternative pathways to acquiring comparable knowledge at a significantly lower cost.
That said, I must admit a personal bias: I prefer the Coursera platform, which is frequently referenced throughout this guide. But there are plans to include more Udacity courses or alternative platforms, MOOcs etc. to reduce this bias. Comments/Suggestions are welcome ;-)
The idea is straightforward: secure an annual subscription on Coursera (often available at a discounted rate) and aim to complete as many relevant courses as possible.
Depending on your prior knowledge, you may not need to start at the beginner level, which is more suitable for those without a solid foundation in mathematics or IT skills.
At the intermediate and advanced levels, you can choose from the listed courses.
Since personal preferences vary—what works well for one person might not for another—you can decide which courses suit you best or opt to complete them all.
All the courses listed are carefully selected to prepare you for tackling "professional-level" courses later on.