Applied Data Science
Offered in Partnership with Mason's DataLab
The Applied Data Science program offers insights into the latest data analytics methods and tools using real-world examples. Utilizing the capstone project as an overarching activity across the data science development phases, the program will prepare you to build and lead applied data science tasks through data-driven decision-making and visualization.
Delivered by Mason professors with extensive experience in data intensive environments, this non-credit executive development program provides a unique combination of theory and practice to help you accelerate your career and improve the data-driven performance of the organization.
Upon successful completion of the program, participants will be able to:
- Comprehend and communicate the data-related tasks of a complex problem
- Identify the phases of a project lifecycle
- Identify the right analytics questions that lead to problem solving
- Develop efficient data management techniques
- Comprehend and use advanced machine learning techniques to predict outcomes
- Develop a strategy and build programs for analytics and storytelling for decision making
- Recommend actions and strategies based on data-driven decisions and communicate using efficient visuals
Program Cost: $4,500
Program costs includes materials, light breakfast, lunch, coffee breaks, parking validation, CPEs, and Certificate of Completion.
Program Delivery: Three 2-day in-person modules and an online capstone project
Dates: Fridays and Saturdays, April 24-25, May 22-23, June 12-13, 2020
Time: 8:30 a.m.-4:30 p.m.
Meet Your Instructors:
- Nektaria Tryfona, PhD, Director, DataLab
- Dieter Pfoser, PhD, Professor, College Of Science
- Olga Gkountouna, PhD, Assistant Professor, College of Science
- Data Management - storage; indexing; big data; relational vs. NoSQL databases; preprocessing; feature transformation; dimensionality reduction.
- Machine Learning – Clustering; frequent item-sets; association rule mining supervised/unsupervised learning, classification; regression; predictive models, factorization, deep learning.
- Digital Storytelling and Decision-Making
- The program also includes a Capstone Project and Discussion Boards, both facilitated online.
Who Should Attend?
- Managers seeking data science knowledge to increase job performance and expand career opportunities
- Career changers (math, physics, economics)
- Data Scientists who seek to advance their knowledge and stay on top of new trends
- Graduate students who seek practical experience
- Participants should be comfortable with programming and tools