Data Analysis and Interpretation Specialization

Course Cover
compare button icon

Course Features

icon

Duration

5 months

icon

Delivery Method

Online

icon

Available on

Limited Access

icon

Accessibility

Desktop, Laptop

icon

Language

English

icon

Subtitles

English

icon

Level

Beginner

icon

Effort

3 hours per week

icon

Teaching Type

Self Paced

Course Description

You can learn SAS and Python programming and expand your knowledge about analytical methods and their applications. Additionally, you can conduct original research that will help inform complex decisions. In just four courses, the Data Analysis and Interpretation Specialization will take you from a data novice to a data expert. Basic data science tools will be taught, such as data management, visualization, and modeling. You can also use Scikit-learn or SAS to learn Python. The Specialization will allow you to analyze a research question and then summarize your findings. The Capstone Project will allow you to use real data to solve a pressing social issue. You will then present your findings in a professional-quality document. The Connection and DRIVENDATA will be your industry partners. Join one of their competitions to help DRIVENDATA tackle some of the most pressing social problems in the world. Or, help The Connection understand the recidivism risk of people who are on parole for substance abuse treatment. You will get feedback from your peers, which will help you to change the way you think about the question. This specialization will help you whether your goal is to work in data analytics, have a career in the field, or just to answer some questions. You don't need any prior experience. You will be able to use statistical methods to perform original research that informs complex decisions.

Course Overview

projects-img

Virtual Labs

projects-img

International Faculty

projects-img

Post Course Interactions

projects-img

Instructor-Moderated Discussions

projects-img

Case Studies, Captstone Projects

Skills You Will Gain

What You Will Learn

Learn to develop a research question, describe the variables and their relationships, calculate basic statistics, and present your results clearly

Use powerful data analysis tools – either SAS or Python – to manage and visualize your data, including how to deal with missing data, variable groups, and graphs

Learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific data and question

Learn the assumptions underlying regression analysis, how to interpret regression coefficients, and how to use regression diagnostic plots and other tools to evaluate the quality of your regression modelLearn how to apply, test, and interpret machine lear

Course Instructors

Lisa Dierker

Professor

Lisa Dierker is a Professor of Psychology at Wesleyan University with training in chronic disease epidemiology. With expertise in the application of innovative statistical methods, she has spent her ...

Jen Rose

Research Professor

Jen Rose is the instructor for this course
Course Cover