RM Masters
Ok. So the thing in the back of my mind is to find the best way to master these skills most efficiently considering the limitations I have (full-time job, family obligations, etc.)
One possibility is to take some time off and do a full-time Bootcamp or a part-time one.
Another path is to enroll in a master’s degree.
All this time, I have been making a list of all the cool things I want to learn eventually. It is getting pretty long.
I just watched a video by Daniel Bourke, where he describes his path. Instead of spending tens of thousands of dollars on a rigid master’s degree that may not suit his interests or even thousands in a Bootcamp, he chose a different path.
He created a list of courses and books that together form the syllabus of the Daniel Bourke Masters Degree.
I completely agree with him. There are just so many good courses and resources online, some free and some with a small cost, that it makes a lot more sense to assemble your degree, especially if you are good at staying motivated and learning.
So, I have decided that this is going to be my path. I now present to you:
Rogelio Montemayor’s Master’s Degree in Data Science and Machine Learning:
- Main Courses:
- Foundations
- CS50 on edX
- DataCamp shell and git courses
- Data Science / Machine Learning / AI
- DataCamp Data Scientist With Python Track
- DataCamp Machine Learning Scientist With Python Track
- DataCamp Data Engineer with Python Track
- DataCamp SQL Fundamentals Skill Track
- DataCamp Python Programming Skill Track
- HarvardX Data Science Professional Certificate on edX
- Kaggle courses
- Kaggle competitions (aim for expert status)
- Elite Data Science Machine Learning Accelerator
- Google Machine Learning Crash Course
- Fast.ai Machine Learning Course
- UM Applied Data Science with Python on Coursera
- Andrew Ng’s Machine Learning on Coursera
- Udacity Deep Learning Nanodegree Foundations
- CS50’s Introduction to Artificial Intelligence with Python on edX
- Udacity Artificial Intelligence Nanodegree
- Big Data
- Google Certified Associate Cloud Engineer
- Google Certified Professional Data Engineer
- Google Certified Professional Cloud Developer
- Google Certified Professional Machine Learning Engineer
- Math
- Khan Academy Matrices
- Khan Academy Linear Algebra
- Khan Academy Calculus and Multivariable Calculus
- 3blue1brown series
- Math for Machine Learning on Coursera
- Books
- Take control of the Mac Command Line with Terminal
- Information Theory, Inference and Learning Algorithms by David MacKay
- An introduction to Statistical Learning by James G., Witten D., et al.
- Naked Statistics by Charles Wheelan
- Learn Python the Hard Way by Zed Shaw
- Data Science from Scratch by Joel Grus
- Hands-on Machine Learning with Scikit-Learn and TensorFlow by Aurélien Géron
- The Hundred-Page Machine Learning Book by Andriy Burkov
- Artificial Intelligence: A Modern Approach by Peter Norvig and Steven Russell
- Deep Learning with Python by François Chollet
- Neural Networks and Deep Learning by Michael Nielsen
- Build a Career in Data Science by Emily Robinson and Jacqueline Nolis
*Bold means completed
Undoubtedly, this blueprint will change as I finish courses and keep learning. It is great to have a roadmap for this journey!