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Data Science Learning

==The purpose of this page is to keep track of various learning resources, a learning plan and progress tracker==

  • [[Data Science Cheat Sheet]]

Personal Projects​

  • [[aaronson-oracle-baseball]]

Progress Tracker​

On-going​

  • [[Coursera - Machine Learning Specialization]]

Planned​

  • [[fast-ai]]
  • [[Coursera - Deep Learning Specialization]]

Finished​

  • [[Hands On Machine Learning]]

Resources​

Courses​

  • [[fast-ai]]
    • A top down approach to teaching you advanced ML, should be done in conjunction with Andrew's [[Deep Learning Specialization]] course
    • 7/10
  • [[Big Data Specialization Degree]]
    • 4 full courses, will require a lot of commitment
    • 6/10
  • [[Coursera - Machine Learning Specialization]]
  • [[Coursera - Deep Learning Specialization]]
    • Advanced Andrew Ng's course on neural networks, picks up after his intro ML class [[Machine Learning]]
    • How does this differ from [[fast-ai]]?
      • fast-ai works from top-down while this course goes from bottom-up
      • fast-ai teaches the art of driving, while deep learning ai teaches you the engineering behind the car
    • 8/10
  • [[Data Science A-Z]] #course
    • Paid on Udemy, ranked highly
    • 21 hours of content, emphasizes on concepts instead of programming application because it is taught in gretl, tableau and excel instead of R or python
    • 9/10
  • [[Applied Data Science with Python Specialization]] #course
    • 5 courses, requires large dedication
    • Focused on teaching tools like pandas, scikit-learn, nltk, networkx to gain insights to data
    • 8/10
  • [[Fast Deep RL]]
  • [[Hugging Face Course]] #course

Books​