Data Science Certificate Program
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.
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
- Data Cleaning and Manipulation
- Descriptive Statistics
- Inferential Statistics
- Model Selection and Comparison
- Visualization of Models and Statistics
A fundamental understanding of what data is. Experience with Python or R is not required, but will be beneficial.
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.
People Data Science and Retail Analytics
Jake has been within data science in the retail industry as well as within people analytics. He is a contracted Industrial Organizational Psychologist specializing in employee engagement. He has helped multiple major companies with measuring people factors such as predicting turnover and segmentation. He has also leveraged data science within retail including assortment optimization and category space automation.