Explore the Master of Science in Data Science program at Drexel University. This program is offered in USA and provides an excellent learning opportunity in Masters studies.

Drexel University's online Master of Science in Data Science prepares students for one of the fastest growing fields in today's job market. The program combines computer science and information systems, focusing on the creation of machine learning algorithms to analyze and manipulate data. Students will learn to summarize data, perform data mining, and communicate their findings effectively. The curriculum includes core courses and offers three elective tracks: Analytics, Mining, and Algorithms; Visualization and Communication; and Management and Accountability. The program culminates in a capstone project, ensuring that graduates are workplace-ready with the skills needed to excel in various industries, including banking and healthcare. Designed for working professionals, this interdisciplinary degree emphasizes applied training and computational problem-solving, making it suitable for individuals from diverse academic backgrounds.

Required Courses

• Data Science Foundations
• Data Acquisition and Pre-Processing
• Data Analysis and Interpretation
• Applied Machine Learning for Data Science
• Applied Cloud Computing
• Data Science Capstone I
• Data Science Capstone II

Elective Courses

• Programming Foundations
• Introduction to Programming
• Data Structures and Algorithms
• Systems Basics
• Introduction to Software Design
• Quantitative Foundations of Data Science
• Foundations of Data and Information
• Database Management Systems
• Information Systems Analysis and Design
• Information Visualization
• Introduction to Data Analytics
• Information Policy and Ethics
• Recommender Systems for Data Science
• Machine Learning for Data Science
• Natural Language Processing with Deep Learning
• Social Network Analytics
• High Performance Computing
• Distributed Systems Software
• Data Analysis at Scale
• Cloud Technology
• Cloud Security and Virtual Environments
• Applied Artificial Intelligence
• Information Innovation through Design Thinking
• Designing with Data
• Understanding Users: User Experience Research Methods
• Prototyping the User Experience