Fundamentals of Data Analytics in Python

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01 - Introduction to Fundamentals of Data Analytics in Python.mp4

05:25

02 - Learning objectives.mp4

00:55

03 - 1.1 Obtain the software.mp4

03:25

04 - 1.2 Explore the Python command line from IPython.mp4

03:22

05 - 1.3 Experiment and chronicle in the IPython Notebook.mp4

04:55

06 - Learning objectives.mp4

00:41

07 - 2.1 Retrieve data from the web.mp4

05:25

08 - 2.2 Load, access and modify dictionaries of data.mp4

08:45

09 - 2.3 Analyze data in Python dictionaries.mp4

07:29

10 - 2.4 Understand advanced Python analytics.mp4

03:14

11 - 2.5 Visualize Python dictionary data with matplotlib.mp4

07:02

12 - Learning objectives.mp4

00:42

13 - 3.1 Understand NumPy.mp4

03:21

14 - 3.2 Create arrays of data in NumPy.mp4

07:47

15 - 3.3 Access and modify array elements.mp4

04:35

16 - 3.4 Compute on arrays.mp4

08:15

17 - 3.5 Understand advanced NumPy.mp4

25:35

18 - Learning objectives.mp4

00:35

19 - 4.1 Understand SciPy.mp4

00:58

20 - 4.2 Compute means, medians, quartiles, and other statistics.mp4

03:22

21 - 4.3 Fit data and interpolate.mp4

08:39

22 - 4.4 Understand sci-kit learn.mp4

03:43

23 - Learning objectives.mp4

00:58

24 - 5.1 Understand Pandas.mp4

02:18

25 - 5.2 Use series objects.mp4

04:21

26 - 5.3 Understand dataframes objects.mp4

04:27

27 - 5.4 Handle missing data.mp4

03:06

28 - 5.5 Perform input and output.mp4

04:43

29 - 5.6 Understand advanced Pandas.mp4

09:14

30 - Learning objectives.mp4

00:41

31 - 6.1 Understand Pythons graphical data exploration tools.mp4

11:52

32 - 6.2 Embed Python charts into graphical applications.mp4

06:12

33 - 6.3. Create web-based graphics from Python.mp4

10:45

34 - 6.4 Visualize 3D datasets using Python.mp4

04:07

35 - Summary of Fundamentals of Data Analytics in Python LiveLessons.mp4

02:44

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