CS 110 Computational Problem Solving

An introduction to computational problem solving using the Python programming language. Students will learn the basic elements of programming, modular program design and the basics of data abstraction.

COMP 360 Principles of Programming Languages

Gain a valuable understanding of how programming languages are organized, including semantics, language definition, data types and control structures.

COMP 421 Embedded Software Development

Students work on the development of "bare metal" embedded software, running on a microcontroller with no operating system support.

ENGR 101 Introduction to Engineering

Students work in small teams to solve open-ended interdisciplinary design problems.

ELEC 201 Electrical Circuits

Study electrical element physical behavior and component models; network laws and analysis techniques; laboratory circuit design, testing, and verification and more.

ELEC 472 Wireless and Digital Communications

Master the practical issues in designing and developing cellular, satellite-based and other wireless communication systems.

ISYE 310 Work Analysis and Design

Introduction to the fundamental methods for analyzing and designing procedures to perform operations in the workplace. Includes time and motion study, methods improvement and workplace design.

ISYE 335 Six Sigma — Process Improvement Methods

Application of statistics to improving quality and productivity. Introduction to Six Sigma quality methodology and the DMAIC (define, measure, analyze, improve and control) problem-solving strategy for continuous quality improvement.

ISYE 420 Simulation of Production and Service Systems

Modeling and analysis of systems using computer-based discrete event simulation. Principles of modeling, validation and output analysis are developed using high-level simulation languages.

GENG 360 Experimental Engineering

Students are introduced to fundamental principles of measurement and instrumentation through hands-on experiments.

GENG 350 Engineering and Social Justice

Develop the critical thinking skills to apply social justice issues to an engineering context in the real world.

GENG 420 Drones for Good

Students explore technical issues on drones and critically consider how this technology can be used for humanitarian purposes.

ENGR 101 Introduction to Engineering

Students work in small teams to solve open-ended interdisciplinary design problems.

MENG 300 Applied Thermodynamics

Laws of thermodynamics to gas and vapor power cycles, mixtures of gases and vapors, and refrigeration cycles.

MENG 380 Kinematics and Design of Machinery

Explore the mechanism synthesis techniques for function, motion, path generators and design applications.

CYBR 500 Foundations of Cyber Security

A prerequisite for all of the other courses in the program, students will understand the fundamental science of cybersecurity and its application to the engineering of secure systems.

CYBR 520 Applied Cryptography

Master cryptography's role in cyber security, covering everything from historic ciphers to the strength of cryptographic implementations.

CYBR 550 Secure Network Engineering

This course will introduce the principles of network security and discuss network topology, theory of network governance and control.

MADS 500A Probability and Statistics for Data Science

One of two prerequisite courses in USD’s Applied Data Science program, students will be introduced to probability and statistical concepts and their applications in solving real-world problems.

502 Applied Data Mining

Covers data exploration and data mining principles, techniques, and applications with a variety of integrated theoretical and practical examples in classification, association analysis, cluster analysis, and anomaly detection.

MADS 507 Practical Data Engineering

This course will cover database table structures, column data types, and the T-SQL language components that go into querying against a database. Reading data from a table, row filtering, and column based functions will be discussed.

AAI 502 Introduction to Artificial Intelligence

The goal of this course is to introduce students to the fundamental principles, techniques, challenges, and applications of AI, deep learning, and natural language processing.

AAI 520 Natural Language Processing

This course will include concepts central to machine learning (discrete classification, probability models) and to linguistics (morphology, syntax, semantics).

AAI 531 Ethics in Artificial Intelligence

This course will examine some of the issues and consequences of increasing use of artificial intelligence and related technologies, and study the challenges of ensuring that artificial intelligent systems and agents behave ethically, legally and safely.