Data science key programming, stats, And computing skills

سرفصل های دوره

1. Introduction

1. What skills you are expected to learn in this series.html

2. Key computing concepts

1. Key computing concepts relevant to Data science.html

3. Key statistical concepts

1. Part 1 - the measures of central tendency, dispersion, and position.html

2. Part 2 - Data distribution (center, spread, shape, and unusual features).html

3. Part 3 - Charts.html

4. Part 4 - populations vs samples.html

4. Python for data science

1. Part 1 - Introduction to python.html

2. Environment setup to start writing python programs.

3. Part 2 - Data Structures.html

4. Part3 - Conditionals.html

5. Part 4 - Loops.html

6. Practicing conditionals and loops.html

7. Part 5 - Functions.html

8. Part 6 - Code Tracing - Important.html

9. Part 7 - How to write a program the right way!.html

10. Part 7 - Practicing program writing - important

11. Part 8 - Object-Oriented Programming.html

12.1 project - solved.zip

12.2 project - unsolved.zip

12. Midpoint project - putting together what we learned

5. Data analysis using Pandas

1. Introduction to the Pandas library.html

2.1 cheat sheet pip.pdf

2. Pandas and Jupyter-notebooks setup - How to install Python libraries using pip

3. The Series - manipulating tabular data

4. DataFrames - manipulating tabular data - Part 1

5. DataFrames - manipulating tabular data - Part 2

6. Data visualization using the Matplotlib

1. Matplotlib Library - Intro.html

2. Matplotlib - Creating graphs.html

7. Final project - putting it all together

1.1 car basic data.csv

1.2 car engine data.csv

1.3 project - solved.zip

1.4 project - unsolved.zip

1. Part 1 - collecting, exploring, cleaning, analyzing, and visualizing car data

2. Part 2 - collecting, exploring, cleaning, analyzing, and visualizing car data

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تولید کننده: Udemy-Training