Road map to AI(Artificial Intelligence) — Part 2
I have sourced the best online courses for ML and gathered them here. Let’s start with basic Programming. You’re not bound to these courses. You can use other courses from other sources as well as these. Most of these courses are free and can be found udacity.com, khanacademy.org, coursera.org.
1. Basic Programming
Programming is the first thing you should learn. You can start with Python or C++. I’ll recommend learning both. Here is a free course for Python: Introduction to Python Programming- Udacity, as well as C++: C++ For Programmers- Udacity. Both of these courses will take about 2 to 3 months to complete. You can go further with C++ with paid courses. Learn advance C++ with real-life projects here: Become a C++ Developer. This course will cost you USD $716 for 4 months of access. Alternatively, you can pay as you go for USD $199 per month. This course will take approximately 4 months to complete, or less if you attend more in a day. You’ll get a certificate on completing this course, which you can share on LinkedIn or anywhere.
2. Math
Statistics is the first thing you have to learn. Here’s a short free course of basic statistics: Intro to Statistics. This topic doesn’t end here. You have to learn advanced statistics. I’ll suggest Intro to Descriptive Statistics and Intro to Inferential Statistics for better learning of statistics. End of math? No! It’s not even the end of statistics. Complete another course for statistics, and you’ll be done with statistics. I suggest Statistics and Probability (Khan Academy).
Math doesn’t end here. Let’s learn some algebra. Try this free course from Udacity: Linear Algebra Refresher. Now comes the hardest part of math, Calculus! Consider Calculus 1 and Differential Calculus from Khan Academy. Let’s end maths here. Let’s go to the Data Science Part.
3. Data Science
Here we will learn about basic data science. Intro to Data Science and Data Analysis will help us on this journey. Both are from Udacity and are free. I don’t want to go further with data science because that’s an entirely different path.
4. Advanced
Congratulations! You just completed all the prerequisites of Machine learning. Yes! That's enough. You’ve come this far without spending money. But this part will cost you a lot more. All of these courses are paid. Let’s go find us some best courses for ML as well as DL and RL.
Let’s try this course Data Analyst. Complete? Okay, let's go further with Become a Machine Learning Engineer. Things are getting pretty interesting now. You are about to complete your journey as a new Machine Learning Engineer as well as an AI Engineer. Hold on, just a second. You are not done yet. Complete this Machine Learning by Stanford University course on coursera.org. Done? Congratulations! You are a Machine Learning Engineer now! You can continue your carrier by working or you can continue your learning journey to be an RL Engineer by learning about self-driving cars and drones. Just a few more steps to go to be a full-stack AI developer. Let’s learn about self-driving cars by completing Intro to Self-Driving Cars. Now it’s time to learn about robotics, so try this course by udacity.com: Become a Robotics Software Engineer. What about drones and autonomous flights? Give this course a try: Flying Car and Autonomous Flight Engineer. You are almost here. You are already an AI developer. I’m suggesting these courses for further knowledge. The last course suggestion from me: Expand Your Knowledge of Artificial Intelligence.
You are a full-stack AI developer now. If you plan to study and learn more, you’re welcome. I won’t suggest more. There are plenty of resources online, go grab them.
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