Data Analysis & Visualizations

תוכן הקורס

1. 10 היכרות עם המרצה2:37צפייה חופשית
2. 27.0 data analysis visualization- introduction18:52
3. 37.1.1 jupyter_conda- jupyter notebook19:27
4. 47.1.2 - jupyter_conda - conda20:35
5. 57.2.1 statistics - types of data9:14
6. 67.2.2 statistics - basic statistic21:59
7. 77.2.3 statistic - probability18:56
8. 87.2.4 statistics - probability distributions20:28
9. 97.3.1 data generation - intoduction21:41
10. 107.3.2 data generation - challenges20:58
11. 117.3.3 data generation - strategies21:13
12. 127.4.1 pandas - introduction21:05
13. 137.4.2 pandas - selections20:04
14. 147.4.3 pandas - operations20:59
15. 157.4.4 pandas - exercises21:14
16. 167.5.1 vectors - introduction12:58
17. 177.5.2 vectors - vector operations21:18
18. 187.5.3 vectors - linear transformations and norm20:27
19. 197.6.1 matrices - introduction21:35
20. 207.6.2 matrices - matrices multiplication21:37
21. 217.6.3 matrices - properties of matrices multiplication20:00
22. 227.6.4 matrices - transpose identity and inverse21:08
23. 237.7.1 linear algebra - determinant17:57
24. 247.7.2 linear algebra - eigenvalues and eigenvectors15:11
25. 257.7.3 linear algebra - system of equations21:56
26. 267.8.1 numpy - introduction19:23
27. 277.8.2 numpy - basic operations20:27
28. 287.8.3 numpy - indexing and iterating21:58
29. 297.8.4 numpy - shape manipulations21:06
30. 307.8.5 numpy - boolean indexing17:36
31. 317.9 scipy19:57
32. 327.10.1 visualization using matplotlib20:09
33. 337.10.2 visualization using matplotlib - pie chart8:11
34. 347.11 visualization using seaborn17:42
35. 357.12.1 MongoDB - introduction and installation17:49
36. 367.12.2 MongoDB - CRUD queries21:55
37. 377.12.3 MongoDB - aggregations part A21:44
38. 387.12.4 MongoDB - aggregations part B19:47
39. 397.12.5 MongoDB - search and visualization9:42
40. 407.12.6 MongoDB - exercises part A22:32
41. 417.12.7 MongoDB - exercises part B15:58