Current offerings are as follows at Lipscomb University are as follows:

Freshman Engineering Lab (EECE 1113L)

This course introduces freshmen to the human-centered engineering design process through a semester-long humanitarian project-based approach. Students will devise an electronic component to help communities in need. For example, any alert system can protect communities (fire, water levels, animal intrusion, gunshots). Students will learn Fundamental electrical and computer engineering concepts, including basic analog circuits and circuit design; sensors, actuators, and microcontrollers; and computer programming using Arduino. Students will present their work at three-semester milestones: storyboards, prototypes, and presentations. These milestones will also be used to train students in technical communication skills and product development cycles.

Signals and Systems (EECE 3833)

Time, sequence, and frequency domain analysis of linear continuous-time and discrete-time systems. Impulse response and convolutions. Laplace and Fourier. Signal energy and power, continuous Fourier series, and Fourier transform.

Digital Signal Processing (EECE 3843)

This course studies methods and tools of Digital Signal Processing (DSP). In particular, this course provides a basic overview of digital signals and their representations and explores the theory and application of discrete-time signal processing in greater detail. This course is taught with audio and images in mind. Main topics include sinusoids, complex exponentials, phasors, LTI systems, Discrete-Time Systems, Aliasing, Filters, Finite and Infinite Impulse Response, Convolutions, Frequency domain filters, and z-Domain filters and transforms.

Mechatronics (EECE 4523)

Students will learn fundamental robotic manipulation concepts like pose, trajectories, kinematics, dynamics, and control via Python-based toolkits and how to deploy them in real robots via ROS and deep visual object recognition techniques. The course is practical and prepares students to program algorithms in both simulated and real robots. The final project requires students to implement a pick and place various challenging objects that require detection, control, and trajectory generation.

Intro to AI (EECE 395V)

Intelligence is increasingly becoming part of everything we do. Better-than-human players, natural language processing, the discovery of new molecular compounds, art/music/video generation, and intelligent robots are a few examples of a growing list of life aspects that AI touches. This course will teach you foundational principles in supervised and unsupervised Machine Learning, Search, Markov Decision Processes, and Reinforcement Learning. You will learn theory and programming in parallel; in the process, learn to think algorithmically and apply concepts to solve new problems and challenges. The final project entails using reinforcement learning in robots to learn pick skills.

Advanced Robotics (EECE 395V)

Advanced Robotics builds on Mechatronics and Intro to AI to guide students through the theoretical and application of deep learning techniques for robot manipulation. The course is conducted as a part of Lipscomb’s Course-Based Undergraduate Research Experiences (CURE). We will start with a SOTA paper and guide students in building a foundational understanding of AI, Deep Neural Networks, and Robotics. Students can aspire to reproduce the original work and be ready to have a rich participation in Summer Research, where they can begin to pose some research questions and pursue their solutions.