Data Analytics with Machine Learning

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Available - On Campus
Program Credits
12

The Analytics with Machine Learning undergraduate certificate provides students with advanced knowledge of data analytics techniques including data mining and machine learning.  Students learn foundational database and data management concepts, statistical analysis techniques, and then data mining techniques that also incorporate machine learning.  Students will be able to mine data in a variety of formats and analyze data using these techniques.  Students will also learn about various data integration options that involve both the analysis of on-premises data repositories, and the analysis of cloud-based data (i.e., Big Data and Cloud Analytics).

Upon completion of this certificate, graduates will be able to:

  • Utilize basic statistical analysis techniques (e.g., probabilities, correlation, and regression) for analyzing data
  • Demonstrate the use of various data mining algorithms, techniques, and concepts
  • Perform predictive analytics with supervised data mining algorithms (e.g., Bayesian classifiers and neural networks)
  • Perform predictive analytics with unsupervised data mining algorithms (e.g., clustering and association rules)
  • Design and implement databases, data warehouses, and data lakes
  • Demonstrate simple and advanced SQL for queries including PL/SQL & triggers
  • Analyze data from databases, data marts, data warehouses, and data lakes using the latest analytics tools and applications
  • Construct cloud-based data lake repositories (with structured, semi-structured, and unstructured data) and perform cloud-based analytics

The 12-credit undergraduate certificate is designed as a standalone stackable credential. Credits can also be applied to the 120-credit B.S. in Data Analytics, or as electives in another B.S. program.

Certificate Requirements and Courses
  • STAT 2110 Intro to Statistics or ASCI 2010 Fundamentals of Actuarial Science
  • INFS 4220 Data Mining
  • INFS 4240 Database Management Systems
  • INFS 4260 Data Integration for Analytics
Contact Us

Wu, Peter Y. Dr. Jamie Pinchot

Department Head, Computer and Information Systems
Professor of Computer and Information Systems

Email: pinchot@rmu.edu
Phone: 412-397-6050

Sample Courses:

These are some of the classes for students in this academic program:

STAT 2110 Intro to Statistics
ASCI 2010 Fundamentals of Actuarial Science
INFS 4220 Data Mining
INFS 4240 Database Management Systems
INFS 4260 Data Integration for Analytics
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Call us at:
1-800-762-0097