2023-2024 Course Catalog

Applied Machine Learning

The Applied Machine Learning Minor allows students to develop theoretical and mathematical understanding of data analytics and machine learning and translate theory into practice through hands-on applications.



CMP120 Introduction to Programming

An introduction to the theory and practice of computer programming with an emphasis on problem solving. No previous programming experience is required.

DSA250 Fundamentals of Data Science

In this course students learn the fundamentals of the data science process, including data acquisition, data cleaning and manipulation to prepare for analysis, common machine learning models for classification and regression, unsupervised machine learning models, and principles of model evaluation.

Pre-requisites Complete all 2 of the following courses:
  • CMP120 Introduction to Programming
  • MTH110 Elementary Statistics
  • 3
    DSA411 Machine Learning and AI

    An introduction to machine learning and artificial intelligence. Topics include classification, regression, clustering, planning, and scheduling. Includes current issues relevant to big data problems.

    Pre-requisites Complete the following course:
  • DSA250 Fundamentals of Data Science
  • 3
    MTH110 Elementary Statistics

    Topics include statistical measures and distributions, decision making under uncertainty, application of probability to statistical inference, linear correlation, introduction to nonparametric statistical methods, and application to problems drawn from the natural and social sciences. Three hours of class per week. Three hours of class per week.

    MTH151 Calculus I

    This is the first course in the calculus sequence. Topics include differential and integral calculus for algebraic and trigonometric functions with applications. Four hours of class per week.

    MTH244 Discrete Mathematics

    This course is an introduction to the fundamental logic and mathematical concepts of discrete quantities, as employed in digital computers. Emphasis will be on the careful and precise expression of ideas. Topics include sets and logic, relations and functions, proof techniques, algorithms, combinatorics, discrete probability, graphs, and trees. Three hours of class per week.