mk-data-sains

Mata Kuliah Data Sains

1. Metadata (slide-1, assignment)
2. Data Science and Python venv (slide-2, assignment)
3. Review and Mastering Python List for Data Science (slide-3a, slide-3b, assignment)
4. Plot data using Matplotlib (slide-4a, slide-4b assignment)
5. Python and pandas DataFrame (slide-5a, slide-5b, assignment)
6. Descriptive statistics and Python (slide-6, assignment)
7. Materials review and finishing previous assignment (assignment)
8. Data dan source of data (slide-8a, slide-8b, assignment)
9. Random number, Monte Carlo, discrete Fourier transform (slide-9a, slide-9b, slide-9c, assignment)
10. Neural networks intro, ANN with spreadsheet (slide-10a, slide-10b, assignment)
11. Practicing Python for ML with Iris and synthetic datasets (slide-11a, slide-11b, assignment)
12. Finishing previous assignments (slide-12, assignment)
13. TensorFlow Playground (slide-13, assignment)
14. Finding case, data, code (slide-14, assignment)