If you are a beginner curious about data science but not sure which language or library to focus on, this free survey course offers a broad overview of the landscape. It covers Python programming, NumPy, Pandas, Matplotlib, Seaborn, machine learning basics, R programming, and data visualization in both Python and R.

This Course Offers

• A Broad Survey of the Data Science Ecosystem: You will get exposure to Python, R, NumPy, Pandas, Matplotlib, Seaborn, and machine learning concepts all in one course, helping you understand the landscape before diving deeper.
• Hands On with Key Libraries: The course covers data analysis using NumPy and Pandas, data visualization using Matplotlib and Seaborn, and data extraction techniques.
• Coverage of Both Python and R: You will learn data visualization using both Python and R, plus a dedicated section on R programming, giving you exposure to two major data science languages.
• A Free, Comprehensive Starting Point: With 8 hours of content across 14 lectures, this free course provides a substantial introduction to multiple data science topics.

Why We Love This Course

1. It is free and comprehensive. You can get exposure to Python, R, and multiple data science libraries without any financial commitment, making it an excellent starting point for curious beginners.
2. It covers both Python and R. Many introductory courses focus on one language. This one gives you exposure to both, helping you decide which path to pursue.
3. It is popular. With over 141,000 students, this course has helped a large number of learners take their first steps in data science.
4. It includes code templates. The course provides Python and R code templates you can download and use on your own projects.

If you are a beginner curious about data science and want a broad, free overview of the tools and libraries before committing to a deeper specialization, this course provides a solid starting point. Note that the course was last updated in 2020, so some library versions and best practices may have changed.

• Beginner Python and R developers curious about data science and machine learning.
• Data analysts and business analysts who want to add Python and R to their toolkit.
• Students and professionals who want a broad, free survey of the data science landscape before choosing a specialization.
• Anyone who wants exposure to both Python and R for data analysis and visualization.

• The course is designed for all graduates, data analysts, and business analysts.
• No prior data science experience is required, though basic programming familiarity is helpful.
• A willingness to explore both Python and R is essential.

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