- Level Professional
- Duration 7 hours
- Course by University of California, Irvine
-
Offered by
About
Welcome to Introduction to Analytic Thinking, Data Science, and Data Mining. In this course, we will begin with an exploration of the field and profession of data science with a focus on the skills and ethical considerations required when working with data. We will review the types of business problems data science can solve and discuss the application of the CRISP-DM process to data mining efforts. A brief overview of Descriptive, Predictive, and Prescriptive Analytics will be provided, and we will conclude the course with an exploratory activity to learn more about the tools and resources you might find in a data science toolkit.Modules
Data Science: The Field and Profession
1
Discussions
- Data Science to Solve Business Problems
2
Readings
- Data Science: The Field and Profession
- Supplemental Resources
Data Science in Business
1
Assignment
- Modules 1 and 2
1
Videos
- Ethical Considerations in Data Science
2
Readings
- Data Science in Business
- Supplemental Resources
Data Mining and an Overview of Data Analytics
1
Discussions
- CRISP-DM for Solving Business Problems
2
Readings
- Data Mining and an Overview of Data Analytics
- Supplemental Resources
Solving Problems with Data Science
1
Assignment
- Modules 3 and 4
1
Discussions
- OPTIONAL: Exploring Further – Customer Success Case Study
1
Videos
- Data Science and Employee Retention
2
Readings
- Solving Problems with Data Science
- Supplemental Resources
Auto Summary
Explore the exciting world of data science with "Intro to Analytic Thinking, Data Science, and Data Mining." This professional-level course offered by Coursera delves into data science skills, ethical considerations, and business applications. Covering the CRISP-DM process, analytics types, and essential data science tools, the 420-minute course is perfect for aspiring data professionals. Available through Starter and Professional subscriptions, it's designed to equip learners with fundamental analytic thinking and data mining expertise.

Julie Pai