Data Science Certificate Program

Crash Course on Data Science

Learn the Basics and Intermediaries of Data Science in this 8-week Crash Course

This program will serve as an introduction to data science, while covering the various stages in its life cycle including data manipulation, data analysis, statistical concepts, and an introduction to the concepts of machine learning. Understanding these stages provides the knowledge necessary to tackle real-world, data rich problems in business and academia. This program is designed to drive your ability to visualize and derive insights thus making difficult business decisions more affordable and optimal.

This course is intended for anyone interested in data manipulation and analysis, specifically those who might wish to pursue it professionally.


8 weeks / 32 hours

Tuesdays / Thursdays
5:30pm - 7:30pm

The next offering is not yet scheduled, but we can notify you when it is.

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Benefits and Outcomes

Stay Empowered by Making Informed Decisions

  • Ability to dissect and understand Data
  • Utilize data science in your career
  • Determine if data science is right for you
  • Extract meaningful insights from data
  • Career advancement
  • Become data science fluent

Learning Objectives

  • Data Cleaning and Manipulation
  • Descriptive Statistics
  • Inferential Statistics
  • Model Selection and Comparison
  • Visualization of Models and Statistics

Suggested Prerequisite

A fundamental understanding of what data is. Experience with Python or R is not required, but will be beneficial.


View Technology Requirements

Jacob Wells

Jacob Wells

QA Data Analyst

Jacob started his career in data by entering the retail world. Forecasting inventory, project analysis, and employee evaluations were the focus of his time there. After completing his Masters in Science, he moved over to Bossa Nova Robotics. There he was involved with the analysis of the data received from robots placed in retail stores that scanned shelves. His focus has been working on image recognition and neural network models.