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Data Science Foundations

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Overview

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Learn to clean, analyze, and visualize data with Python and SQL. Includes **Python 3**, **SQL**, **Pandas**, **Matplotlib**, **Data Visualization**, **Data Cleaning**, and more.

Syllabus

  • Welcome to Data Science Foundations
    • Preview what lies ahead on your Data Science journey.
  • Principles of Data Literacy
    • Discover the world of data in this fully conceptual course where you will learn how to think about, visualize, and analyze data.
  • Learn SQL
    • Learn SQL — a popular language that’s used for communicating with databases and working with data.
  • Python Fundamentals for Data Science (Part I)
    • Build a foundation in programming with Python with a focus on Data Science!
  • Python Fundamentals for Data Science (Part II)
    • Continue building your Python Skills while applying them to real data science challenges including finding and working with real data.
  • Portfolio Project: U.S. Medical Insurance
    • Use your understanding of Python syntax to sort and analyze data about U.S. medical insurance costs!
  • Python Pandas for Data Science
    • Learn how to use the Python pandas library and lambda functions for Data Science.
  • Exploratory Data Analysis in Python
    • Learn about exploratory data analysis (EDA) techniques for Data Science
  • Statistics Fundamentals for Data Science
    • Learn how and when to use the essential statistical tools Data Scientists use to analyze data.
  • Data Visualization Fundamentals with Python
    • If a picture is worth a thousand words, then a visualization is worth more than a thousand data points. Learn how to make them here!
  • Portfolio Project: Data Visualization
    • Use your understanding of data visualization to analyze and plot data about GDP and life expectancy.
  • Data Wrangling, Cleaning, and Tidying
    • Clean, well-structured data is essential to data science but cleaning data requires both a keen eye and technical skills. Develop both here!
  • Communicating Data Science Findings
    • Communication is an important part of your work as a data scientist. Learn best practices for effectively explaining your analysis.
  • Data Analysis Portfolio Project
    • Use your knowledge of data analysis to interpret data about endangered animals for the National Park Service.
  • Next Steps
    • Explore your learning options after the Data Science Foundations!

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