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Python
Getting Started with Data Science and Python
Getting Started with Data Science and Python
Curriculum
4 Sections
24 Lessons
10 Weeks
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Chapter 1: Discovering the Match between Data Science and Python
4
1.1
Defining the Sexiest Job of the 21st Century
1.2
Creating the Data Science Pipeline
1.3
Understanding Python’s Role in Data Science
1.4
Learning to Use Python Fast
Chapter 2: Introducing Python’s Capabilities and Wonders
6
2.1
Why Python?
2.2
Working with Python
2.3
Performing Rapid Prototyping and Experimentation
2.4
Considering Speed of Execution
2.5
Visualizing Power
2.6
Using the Python Ecosystem for Data Science
Chapter 3: Setting Up Python for Data Science
5
3.1
Considering the Off-the-Shelf Cross-Platform Scientific Distributions
3.2
Installing Anaconda on Windows
3.3
Installing Anaconda on Linux
3.4
Installing Anaconda on Mac OS X
3.5
Downloading the Datasets and Example Code
Chapter 4: Working with Google Colab
9
4.1
Defining Google Colab
4.2
Getting a Google Account
4.3
Working with Notebooks
4.4
Performing Common Tasks
4.5
Using Hardware Acceleration
4.6
Executing the Code
4.7
Viewing Your Notebook
4.8
Sharing Your Notebook
4.9
Getting Help
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