Course Summary
Credit Type:
16 weeks (80 hours total)
Dates Offered:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Lower-Division Baccalaureate 3 Data Sciences
Lower-Division Baccalaureate 1 Introduction to Programming
Lower-Division Baccalaureate 1 Introduction to Statistics
Lower-Division Baccalaureate 2 Introduction to Database and SQL Programming


This course is offered through Coursera, which is an ACE Authorized Instructional Platform.

The course objective is to learn what data science is and what data scientists do. Learners will discover the applicability of data science across fields and learn how data analysis can help them make data-driven decisions. Learners find that they can kick-start their career path in the field without prior knowledge of computer science or programming languages. This Specialization will give learners the foundation they need for more advanced learning to support their career goals. The course topics include What is Data Science; Tools for Data Science; Data Science Methodology, and Databases and SQL for Data Science.

Learning Outcomes:

  • Describe what data science and machine learning are, their applications and use cases, and various types of tasks performed by data scientists
  • Develop the mindset to work like a data scientist, and follow a methodology to tackle different types of data science problems
  • Gain hands-on familiarity with common data science tools including JupyterLab, R Studio, GitHub and Watson Studio
  • Write SQL statements and query Cloud databases using Python from Jupyter notebooks

General Topics:

  • What is Data Science?
  • Tools for Data Science
  • Data Science Methodology
  • Databases and SQL for Data Science with Python
Instruction & Assessment

Instructional Strategies:

  • Audio Visual Materials
  • Computer Based Training
  • Discussion
  • Laboratory
  • Lectures
  • Practical Exercises

Methods of Assessment:

  • Other
  • Quizzes
  • peer-reviewed exercises

Minimum Passing Score:

Supplemental Materials