Course Summary

Data Science is being used, both in the public and private sectors, to answer questions that lead to decisions in one way or another. Data scientists are increasingly facing scrutiny about what they have done and why. This course will look into the processes to understand where trust is built and lost which in turn will be the building blocks of the concept of “Trustworthy Data Science”.

Target audience

• Anyone who works with data.
• Those who are new to statistics or data science.

Course Outline

The following topics will be covered:

• Data
  • Sources & Design
  • Validity & appropriateness
  • Variables collected / available
• Statistical Analysis
  • Methods & Assumptions
  • Validity & appropriateness
• Statistical Programming
  • Reproducible programming
• Reporting Results
• Communication

Learning Outcomes

• Understanding of data science processes and thinking.
• What makes Data Science Trustworthy.

Contact Us if you are interested in this course.