MS in Applied Data Analytics

The Master of Science (MS) in Applied Data Analytics program provides students with solid knowledge of the foundations of data analytics and emphasizes the presentation and discussion of the latest industry tools and approaches within an academically rigorous framework. The curriculum provides a thorough immersion in concepts and techniques for organizing, cleaning, analyzing, and representing/visualizing large amounts of data. Students will be exposed to various database systems, data-mining tools, data visualization tools and packages, Python packages, R packages, and cloud services such as Amazon AWS, Google Cloud, and Mass Open Cloud. The knowledge of analytics tools combined with an understanding of data-mining and machine-learning approaches will enable students to critically analyze real-world problems and understand the possibilities and limitations of analytics applications.

Learning Outcomes

  • Knowledge of the foundations of applied probability and statistics and their relevance in day-to-day data analysis.
  • Comprehension of computing concepts and applications requirements involving massive computing needs and data storage.
  • The ability to apply various data visualization techniques using real-world data sets and analyze graphs and charts.
  • Understanding of web analytics and metrics, procuring and processing unstructured text/data, and the ability to investigate hidden patterns.
  • Knowledge-discovery skills using data-mining techniques and tools over large amounts of data.
  • The ability to implement machine-learning algorithms and their pertinence in real-world applications.
  • Comprehensive knowledge of data analytics techniques, skills, and critical thinking, and an understanding of the possibilities and limitations of their applications.

Admissions Information

For current admissions information, please visit the Metropolitan College website.

Prerequisites

Applicants to the program are required to have a bachelor’s degree from a regionally accredited institution. Before admission into the Master of Science in Applied Data Analytics program, applicants without prior background in Information Technology, Computer Science, and Mathematics are expected to take MET CS 300 Introduction to Software Development and the following prerequisite courses:

  • MET CS 520 Information Structures with Java
    or
    MET CS 521 Information Structures with Python
  • MET CS 526 Data Structures and Algorithms
  • MET CS 546 Introduction to Probability and Statistics
  • MET CS 579 Database Management
    or
    MET CS 669 Database Design and Implementation for Business

Degree Requirements

A total of eight courses (32 credits) is required:

Core Curriculum (six courses/24 credits)

  • MET CS 544 Foundations of Analytics with R
  • MET CS 555 Data Analysis and Visualization with R
  • MET CS 566 Analysis of Algorithms
  • MET CS 677 Data Science with Python
  • MET CS 688 Web Analytics and Mining
  • MET CS 699 Data Mining

General Electives (two courses/8 credits)

Choose two of the following:

  • MET CS 689 Designing and Implementing a Data Warehouse
  • MET CS 767 Machine Learning
  • MET CS 777 Big Data Analytics
  • MET CS 779 Advanced Database Management
  • MET MA 582 Mathematical Statistics