The curriculum includes mathematics through calculus III, computational linear algebra with differential equations and probability and statistics; a programming sequence, coursework in mechanical engineering, computer science, and electrical engineering, and specialized core analysis and systems engineering courses. Tracks will include additional courses in Data Analytics and/or Systems Engineering.

Explore the Advising Guide for a sample listing of credits.
Example Course of Study

Degree Core Required Courses
  • Provides an introduction to quantitative modeling methods that have broad application. The course focuses on computer implementation of the models, and the application of these models to practical decision-making scenarios. The course covers OR tools, such as optimization, queuing, simulation, and decision analysis.

  • Design methodologies; divide-and-conquer, exhaustive search, dynamic programming. Time and space complexity measures, analysis of algorithms. Survey of important algorithms for searching, sorting, graph manipulation. Tractability: class P and NP, NP complete problems.

  • Introduction to the systems engineering process, project management, and engineering management to include systems engineering methods, lifecycle models, risk management, and tradeoff analysis. Focus is on the role of the systems engineer throughout a project with emphasis on both technical and project management roles.

  • Economic decision-making, professional ethics, business records, net worth and profit and loss calculation, engineering law and contract agreements.

  • Scientific visualization: overview, foundation techniques, and applications. Use of software, data structures, mathematical modeling, user interface and manipulation of graphical objects.

  • The application and study of experimentation and statistical design. Topics include design and analysis of single-factor and multi-factor experiments.

  • Optimization methods: parameter optimization, interior point methods, quadratic programming, constrained optimization, optimization for dynamic systems and numerical methods. Engineering applications. Topics selected from linear and nonlinear programming, the simplex algorithm and other approaches to linear optimization, minimax theorems, and convex functions.

  • Data Mining- This course covers data warehousing, OLAP, association rules, cluster analysis, classification and prediction, complex data mining applications and trends in data mining.

    Machine Learning- Introduction to machine learning followed by a selection of machine learning topics such as regression, Bayesian learning, Hidden Markov Models, support vector machine, clustering and reinforcement learning.

  • Fundamental areas of modern raster computer graphics: hardware, software, data structures, mathematical modeling, user interface and manipulation of graphical objects. a subset of the two dimensional GKS is examined and implemented with emphasis placed upon segmented display files and instance modeling. Basic to all graphic programs written are the ergonomic requirements of the user. Required programs are in the areas of animation, paint systems, polygon filling and clipping, and curve generation.

  • Design principles with the realistic constraints of economy, safety, reliability, aesthetics, ethics and social impact. Project and team organization to meet design goals. Professional oral and written communication of the design through presentations, memos, reports, and e-mail.

  • Project laboratory for the senior or graduate student for the design of a mechanical or electromechanical component, with emphasis on the identification, selection, design, and simulation or fabrication of the component. a successful project is required for completion of the course.

Other Required Courses
  • Development of techniques for moral analysis and their application to ethical problems encountered by engineers, such as professional employee rights and whistle blowing, environmental issues, ethical aspects of safety, risk, and liability, and conflicts of interest. Business applications also included.

  • This class will discuss selected topics in ethical, social, political, legal and economic aspects of the application of computers. Each student is expected to research one or more topics, actively participate in discussions, and give a presentation. Written papers may be required. Prer., CS 2080; College of Engineering students only.

  • Earn college credit while attending high school classes.

  • Earn UCCS dual college credit while attending a PLTW high school for a reduced rate of $102/credit hour. Preferred admittance is also given to PLTW students.

    For more information, visit Project Lead The Way.

  • CU Succeed courses are taught in the high school during the regular school day by University-qualified high school teachers who hold an Honorarium Faculty Appointment in their appropriate discipline department at UCCS.

    $50 per credit hour plus a $2 per credit hour SIS administrative fee (i.e. 3-credit course $156).

    For more information, visit CU Succeed.