1

Step 1

Intro to Python for Data Science

2

Step 2

Intermediate Python for Data Science

3

Step 3

Python Data Science Toolbox (Part 1)

4

Step 4

Python Data Science Toolbox (Part 2)

5

Step 5

Importing Data in Python (Part 1)

6

Step 6

Importing Data in Python (Part 2)

7

Step 7

Cleaning Data in Python

8

Step 8

Pandas Foundations

9

Step 9

Manipulating DataFrames with pandas

10

Step 10

Merging DataFrames with pandas

11

Step 11

Introduction to Databases in Python

12

Step 12

Introduction to Data Visualization with Python

13

Step 13

Interactive Data Visualization with Bokeh

14

Step 14

Statistical Thinking in Python (Part 1)

15

Step 15

Statistical Thinking in Python (Part 2)

16

Step 16

Supervised Learning with scikit-learn

17

Step 17

Machine Learning with the Experts: School Budgets

18

Step 18

Unsupervised Learning in Python

19

Step 19

Deep Learning in Python

20

Step 20

Network Analysis in Python (Part 1)

21

Step 21

STATEMENT OF ACCOMPLISHMENT

1

Step 1

Intro to Python for Data Science

2

Step 2

Intermediate Python for Data Science

3

Step 3

Python Data Science Toolbox (Part 1)

4

Step 4

Python Data Science Toolbox (Part 2)

5

Step 5

Importing Data in Python (Part 1)

6

Step 6

Importing Data in Python (Part 2)

7

Step 7

Cleaning Data in Python

8

Step 8

Pandas Foundations

9

Step 9

Manipulating DataFrames with pandas

10

Step 10

Merging DataFrames with pandas

11

Step 11

Introduction to Databases in Python

12

Step 12

Introduction to Data Visualization with Python

13

Step 13

Interactive Data Visualization with Bokeh

14

Step 14

Statistical Thinking in Python (Part 1)

15

Step 15

Statistical Thinking in Python (Part 2)

16

Step 16

Supervised Learning with scikit-learn

17

Step 17

Machine Learning with the Experts: School Budgets

18

Step 18

Unsupervised Learning in Python

19

Step 19

Deep Learning in Python

20

Step 20

Network Analysis in Python (Part 1)

21

Step 21

STATEMENT OF ACCOMPLISHMENT

29 July 2018
Goal completed 8 August 2018
Career & Work

DataCamp. Data Scientist with Python

Маленькая часть моей большой цели тык

 Goal Accomplishment Criteria

Все 22 пункта пройдены, законспектированны, составлены шпаргалки

Ежедневный отчет о проделанной работе, общее время цели.

 Personal resources

время( около 200 часов), деньги(минимум 30 $ на подписку), два ствола (если соседи снова будут мешать заниматься)

  1. Intro to Python for Data Science

    Step cost — 30 $

  2. Intermediate Python for Data Science

  3. Python Data Science Toolbox (Part 1)

  4. Python Data Science Toolbox (Part 2)

  5. Importing Data in Python (Part 1)

  6. Importing Data in Python (Part 2)

  7. Cleaning Data in Python

  8. Pandas Foundations

  9. Manipulating DataFrames with pandas

  10. Merging DataFrames with pandas

  11. Introduction to Databases in Python

  12. Introduction to Data Visualization with Python

  13. Interactive Data Visualization with Bokeh

  14. Statistical Thinking in Python (Part 1)

  15. Statistical Thinking in Python (Part 2)

  16. Supervised Learning with scikit-learn

  17. Machine Learning with the Experts: School Budgets

  18. Unsupervised Learning in Python

  19. Deep Learning in Python

  20. Network Analysis in Python (Part 1)

  21. STATEMENT OF ACCOMPLISHMENT

  • 1224
  • 29 July 2018, 00:05
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