How a begginer should start studies in ML? [closed]

Question

People, I am a chemistry undergrad that wants to learn ML for application in my field(chemistry), however, I had never studied programming or anything related to code in my life, for this reason, I am building a study plan for this goal.

Can you give me any advice on this endeavor? I would appreciate any suggestions to know if I am on the correct path.

Cycle 1: Learning the basic concepts of Programming

• Algorithm and Programming Logic with Python: https://www.youtube.com/playlist?list=PLQKlKz1J9WWTUUMnfa2PWaPU3qPND7GJN

• Kaggle: https://www.kaggle.com/learn

Cycle 2: Learning how to Program in Python

• Python Course for Beginners: https://www.youtube.com/playlist?list=PLyqOvdQmGdTSEPnO0DKgHlkXb8x3cyglD

• Kaggle: https://www.kaggle.com/learn

• CodingBat: https://codingbat.com/python

• Project Euler: https://projecteuler.net/

Cycle 3: Learning how to use Python for Data Analysis and learning Statistics

• Python Course for Machine Learning and Data Analysis: https://www.youtube.com/playlist?list=PLyqOvdQmGdTR46HUxDA6Ymv4DGsIjvTQ-

• Khan Academy: https://pt.khanacademy.org/math/em-mat-estatistica

• Pandas, Matplotlib and NumPy:

https://www.youtube.com/playlist?list=PL-osiE80TeTsWmV9i9c58mdDCSskIFdDS

https://www.youtube.com/playlist?list=PL-osiE80TeTvipOqomVEeZ1HRrcEvtZB_

https://www.youtube.com/playlist?list=PLzgPDYo_3xukqLLjNeuCxj4CwvkJin03Z

• How to go from ZERO to Data Science in Just One Lesson: https://www.youtube.com/watch?v=WJE4spsP-Xk

Cycle 4: Learning basic concepts about Machine Learning and Probability

• Course Introduction to Machine Learning and Machine Learning Algorithms:

https://www.youtube.com/playlist?list=PLyqOvdQmGdTSqkutrKDaVJlEv-ui1MyK4

https://www.youtube.com/playlist?list=PLyqOvdQmGdTS4PcZsAKhXgkdUyLjXnptS

• Machine Learning with Python and Scikit-learn: https://www.youtube.com/playlist?list=PLeFetwYAi-F9Z0N3ZSjPL2i24PO5iiXaY

• Kaggle: https://www.kaggle.com/learn

• Khan Academy: https://pt.khanacademy.org/math/em-mat-probabilidade

• Google Machine Learning Crash Course: https://developers.google.com/machine-learning/crash-course

Cycle 5: Learning Applications of Machine Learning in Chemistry

• EMMSB LNCC: https://www.youtube.com/playlist?list=PLIJhet1J-_l82wpFzn2ZOyCIKy-FotuND

• The Computational Toolkit: https://www.youtube.com/playlist?list=PLgCwaJhZsSlMQky78U5JLyMOgO16o6ubE

• Learn how to use RDKit or DeepChem, a collection of cheminformatics and machine learning tools for Python

Cicle 6: Learning Deep Learning Fundamentals

• Deep Learning by Andrew Ng on Coursera: https://www.coursera.org/specializations/deep-learning

• Kaggle: https://www.kaggle.com/learn

Answer 1

I graduated with a university degree in Artificial Intelligence, I only covered Artificial Intelligence a little bit on it, surprisingly, but this brings me to the actual point of my answer. I have started a bit here and there to try and learn myself I mainly use the site https://datacamp.com a lot if I am honest, as for Python when I learned this I tried to stick to one resource and learn algorithms and problems later. This is a good resource on Python: https://roadmap.sh/python and also this course is good which is free: https://futurecoder.io/

I mean your list is good, but what I would say try and find overlaps more in what you are learning because especially I find myself with programming say doing a Python programming course at beginner level, then doing another at beginner level but 'data science' you will find a lot of overlap.