ressources.md

Collection of helpful ressources for data science career

0. Full Stack Data Scientist Tutorials Collection: https://www.kdnuggets.com/2021/09/path-full-stack-data-science.html

1. Python : https://lnkd.in/grD8XUS6

2. Pandas : https://lnkd.in/g4yTJ7CP

3. NumPy : https://lnkd.in/gg9Uw-km

4. Matplotlib : https://lnkd.in/gahrGicD

5. Seaborn : https://lnkd.in/gcu4UKpw

6. Scikit-learn : https://lnkd.in/gGfkNu5i

7. TensorFlow : https://lnkd.in/g3fw3uRV

8. Keras : https://lnkd.in/gfPTfbgg

9. PyTorch : https://ow.ly/6TQI50PjRA5

10. SQL : https://lnkd.in/gnwe4qcb

11. GeoPandas : https://lnkd.in/d-hnRaJt

12. Git : https://lnkd.in/gyzhztvH

13. AWS : https://bit.ly/3ZQWMS1

14. Azure : https://bit.ly/42f4N4V

15. Google Cloud Platform : https://bit.ly/3JJADzv

16. Docker : https://bit.ly/3Lt2zJe

17. Kubernetes : https://lnkd.in/gjXCT7Mb

18. Linux Command Line : https://bit.ly/3FtcTgw

19. Jupyter Notebook : https://lnkd.in/g7cPmgHQ

20. Data Wrangling : https://bit.ly/3TiMibP

21. Data Visualization : https://lnkd.in/gQ52Jd_J

22. Statistical Inference : https://lnkd.in/grNXVQh5

23. Probability : https://lnkd.in/gvnWCphc

24. Linear Algebra : https://lnkd.in/gty6XpVF

25. Calculus : https://lnkd.in/gjhsmsxu

26. Time Series : https://bit.ly/3Fvuep4

27. NLP : https://bit.ly/3Fvursm

28. Neural Network : https://lnkd.in/gThs2AAp

29. Deep Learning : https://lnkd.in/gVbSPae2

30. Machine Learning : https://bit.ly/3mZ5Wh3

31. Apache Spark : https://lnkd.in/ge7Rj-Yr

32. Hadoop : https://bit.ly/3Lq34DR

33. Big-O Notation : https://lnkd.in/gfYqM8WU

34. Regular Expression : https://lnkd.in/gE9kZTZW

35. Unix/Linux Permissions : https://bit.ly/3ZUfwA8

36. Python String Formatting : https://lnkd.in/d4s3W779

37. Flask : https://lnkd.in/gGzbSTgU

38. Django : https://lnkd.in/grZcWz8y

39. Plotly : https://lnkd.in/d8SKxbdA

40. PostgreSQL : https://lnkd.in/gzfiW7zB

41. MySQL : https://lnkd.in/g4JnPVTe

42. MongoDB : https://lnkd.in/gHc4F4ER

43. TensorFlow Probability Cheat Sheet : https://lnkd.in/gr3bgDGP

44. OpenAI GPT-3 Documentation : https://lnkd.in/gawB_SC9

45. GPT-3 API Reference : https://lnkd.in/gtCGZvX8

46. SciPy : https://ow.ly/JYCN50PjRG7

47. Chat GPT Cheat Sheet : https://lnkd.in/e43cDB9q

48. Colors in dataviz : https://lnkd.in/dWU6WkhU

49. Geospatial data science in Python : https://lnkd.in/gCbqNXFn

50. Network analysis : https://ow.ly/fYm550PjRyf

Tutorials for data science

David Munoz Tord

Useful tutorials for data science in R, Pyhton and MATLAB:

Git

Make sure you are familiar with the basics of git and that you know how to “fork” a repository to your personal computer and “push” modifications to github.

Fork a repository:

https://docs.github.com/en/github/getting-started-with-github/fork-a-repo

Commit:

https://dont-be-afraid-to-commit.readthedocs.io/en/latest/git/commandlinegit.html

Creating an issue:

If you encounter issues during the homework you are encouraged to speak about it (that IS one of the main goal of this workshop!) However make it simpler and available to others we privilegy that you juste create an “issue” -> https://docs.github.com/en/github/managing-your-work-on-github/creating-an-issue

Matlab or GNU Octave (free alternative to Matlab) :

Basics (online - free - active coding - videos) https://www.mathworks.com/learn/tutorials/matlab-onramp.html

Getting familiar with data wrangling and visualization (free - active coding - videos)

https://drive.switch.ch/index.php/s/ZYGtqDasSgNPo3b

Transitioning from Matlab to Python (free - docs)

https://drive.switch.ch/index.php/s/dThUOtWJevWgsKz

Transitioning from Matlab to R (free - docs)

https://drive.switch.ch/index.php/s/pfo9GtrYiyKLk5x

R:

Basics (online - free - active coding - videos)

https://learn.datacamp.com/courses/free-introduction-to-r

Getting familiar with data wrangling and visualization (online - free - active coding - videos)

https://beanumber.github.io/sds192/schedule.html

Basic statistical inference course (online - free - active coding - videos)

https://campus.datacamp.com/courses/statistical-inference-and-data-analysis/

Python:

Basics (online - free - active coding - videos)

https://www.learnpython.org/en/

Getting familiar with data wrangling and visualization (free - active coding - videos)

https://drive.switch.ch/index.php/s/qdbgPKqQ5xljYoA

Getting familiar with Machine Learning (free - active coding - videos)

https://drive.switch.ch/index.php/s/X6mlUhVvdQcEw6S

Neuroimaging with Python (Nipy - FSL - AFNI - SPM)

https://github.com/NIDS2020-instructor?tab=repositories