Data Science Fundamentals - Learning Basic Concepts, Data Wrangling, and Databases with Python

Colleagues, in the Data Science Fundamentals - Learning Basic Concepts, Data Wrangling, and Databases with Python: Walk through the data science process by building a simple recommendation system. After this introduction, you dive deeper into each of the specific steps involved in the first half of the data science process–mainly how to acquire, transform, and store data (often referred to as an ETL pipeline). You learn how to download data that is openly accessible on the Internet by working with APIs and websites, and how to parse this XML and JSON data. With this structured data, you learn how to build data models, store and query data, and work with relational databases. Along the way, you learn the fundamentals of programming with Python (including object-oriented programming and the standard library) as well as the best practices of building sustainable data science applications. Learn to get up and running with a Python data science environment, the essentials of Python 3, including object-oriented programming, The basics of the data science process and what each step entails, How to build a simple (yet powerful) recommendation engine for Airbnb listings, Where to find high-quality data sources and how to scrape websites if no existing dataset is available, How to work with APIs programmatically, including (but not limited to) the Foursquare API, Strategies for parsing JSON and XML into a structured form, How to build data models and work with database schemas, The basics of relational databases with SQLite and how to use an ORM to interface with them in Python, Best practices of data validation, including common data quality checks, How to query data in a database, including joining data tables and aggregating data, The fundamentals of exploratory data analysis, How to find and handle missing or malformed data, and The importance of creating reproducible analyses and how to share them effectively.

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For your listening-reading pleasure:

Explore our Data-Driven Organizations Audible and Kindle book series on Amazon:

1 - Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

Much career success, Lawrence E. Wilson - Data Science Academy (share with your team)