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Python for Data Science, AI & Development
Chapters

1Python Foundations for Data Work

2Data Structures and Iteration

3Numerical Computing with NumPy

4Data Analysis with pandas

5Data Cleaning and Feature Engineering

6Data Visualization and Storytelling

7Statistics and Probability for Data Science

8Machine Learning with scikit-learn

9Deep Learning Foundations

10Data Sources, Engineering, and Deployment

Working with Files and FormatsJSON and XML ParsingWeb Scraping BasicsREST APIs and requestsAuthentication and TokensSQL Fundamentalspandas with SQLAlchemyGit and GitHub WorkflowsSpark for Large DatasetsData Versioning with DVCPackaging with Poetry or pipTesting with pytestLogging and ConfigurationBuilding REST APIs with FastAPIContainers and Deployment
Courses/Python for Data Science, AI & Development/Data Sources, Engineering, and Deployment

Data Sources, Engineering, and Deployment

37296 views

Acquire data from files, web, and databases; then test, package, version, and deploy reliable services.

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13 of 15

Logging and Configuration

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