This course attempts to strike a balance between presenting the vast set of methods within the field of data science and Python programming techniques for implementing them. Problem-solving and programming implementation will be emphasized throughout the course. All techniques presented will be introduced using real-world programming examples. A major goal of the course is to ensure that when you finish the course, you will have the programming and conceptual expertise you need to join the field of data science.
Several Python modules such as pandas, scikit-learn, scipy.stats, and statsmodels will be introduced that are useful for data analysis, data visualization, and data mining. The course will gradually shift from introductory topics such as a review of Python, matrix operations, and statistics to applications and implementing programs involving data mining, visualization, statistical models, and time series analysis.
Step-by-Step Guide to Begin Credential
- Explore the CS250 course information
- Then log in or sign up for a Saylor.org account by linking your existing Google or Facebook accounts, or creating a standalone account
- You’ll then need to verify your account credentials via email and complete the user account profile to continue
- Navigate to the “Courses” tab at the top left of the page
- Then, either scroll to Computer Science or search for CS250
- Then select the course and enroll, free of charge