SUGGESTED TRAINING MATERIALS
🚶♀️To start:
1. [online course] Linear Algebra for Machine Learning. Free youtube playlist: https://www.youtube.com/playlist?list…
2. Introduction to data science: https://www.coursera.org/specializati…
3. [book] Deep Learning with Python: https://www.manning.com/books/deep-le…
4. [online course] Machine Learning Andrew Ng: https://www.coursera.org/learn/machine-learning
5. [online course] https://ocw.mit.edu/
🚴♀️To further advance:
– Stanford Computer Vision: http://cs231n.stanford.edu/
– Stanford Natural Language: http://web.stanford.edu/class/cs224n/
– [online course] Udacity Natural Language Processing: https://www.udacity.com/course/natura…
– [online course] Udacity Computer Vision: https://www.udacity.com/course/introd…
🚀To prove yourself:
1. SA Associate (to get familiarity with the cloud)
2. AWS ML Specialty – https://aws.amazon.com/certification/… To learn about ML services;
3. [optional] AWS Big Data Specialty – to expand knowledge in data engineering on AWS.
☁AWS materials:
– Machine Learning practical career paths in ML: https://aws.amazon.com/training/learn…
– AWS ML Blog: https://aws.amazon.com/blogs/machine-…
Have fun!