Python for Data Science
6h 21m 57s
English
Paid
Course description
Master the key Python skills for data analysis, visualization, statistical analysis, and machine learning. Build a solid foundation for a successful start to your journey in data science.
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/ #1: Introduction
All Course Lessons (21)
| # | Lesson Title | Duration | Access |
|---|---|---|---|
| 1 | Introduction Demo | 15:09 | |
| 2 | Best Coding Practices | 05:32 | |
| 3 | Python & PyCharm (IDE) Configuration | 16:09 | |
| 4 | Demo 1: Data Types & Creating Variables | 18:39 | |
| 5 | Demo 2: Lists/Matrices/Dictionaries | 17:30 | |
| 6 | Demo 3: For-Loops in Python | 16:54 | |
| 7 | Demo 4: If-Else Statements | 20:00 | |
| 8 | Demo 5: Python Libraries for Data Science | 18:04 | |
| 9 | Demo 6: Loading Data in Python | 16:06 | |
| 10 | Demo 7: Data Exploration & Preprocessing | 14:33 | |
| 11 | Demo 8: Random Data Generation (Data Simulation) | 19:53 | |
| 12 | Demo 9: Filtering, Sorting, Grouping | 21:08 | |
| 13 | Demo 10: Descriptive Statistics | 15:50 | |
| 14 | Demo 11: Merging & Joining Datasets | 21:27 | |
| 15 | Demo 12: User Defined Functions (UDF) | 13:50 | |
| 16 | Demo 13: Text Cleaning and Preparation in NLP | 21:11 | |
| 17 | Demo 14: Data Visualization in Python | 20:57 | |
| 18 | Demo 15: Data Sampling (Part 1) - Theory | 28:16 | |
| 19 | Demo 16: Data Sampling (Part 2) - Coding | 20:34 | |
| 20 | Demo 17: A/B Test Results Analysis (Part 1) - Theory | 22:49 | |
| 21 | Demo 18 - A/B Test Results Analysis (Part 2) - Coding | 17:26 |
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Read Book Python for Data Science
| # | Title |
|---|---|
| 1 | Python_Cheat_Sheet |
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