Courses
The following are examples of courses taught by LINCD faculty. For the most up-to-date information on courses that will be offered in upcoming semesters, please access the department's course planning spreadsheet.
Undergraduate Courses
- ECEN 3300 Linear Systems
- ECEN 3810 Introduction to Probability
- ECEN 4242 Communication Theory
- ECEN 4632/5632 Introduction to Digital Filters
- ECEN 4752/5752 Communications Lab
- ECEN 4322/5322 Data and Network Science (AI/ML)
- ECEN 4672/5672 Digital Image Processing (AI/ML)
- ECEN 5002/4732/5732 Deep Learning and Its Connections to Information Theory (AI/ML)
Graduate Courses
- Fall (A bold font implies the course will be offered every year. Otherwise, it is offered every other year)
- ECEN 5612 Noise and Random Processes
- ECEN 5622 Information Theory and Coding
- ECEN 4632/5632 Introduction to Digital Filtering
- ECEN 4672/5672 Digital Image Processing (AI/ML)
- ECEN 5002/4732/5732 Deep Learning and Its Connections to Information Theory (AI/ML)
- Spring
- ECEN 5012 Modern Signal Processing
- ECEN 4322/5322 Data and Network Science (AI/ML)
- ECEN 5682 Theory and Practice of Error Control Codes
- ECEN 5692 Principles of Digital Communication
- ECEN 5712 Machine Learning for Engineers (AI/ML)
- ECEN 5022/5722 Artificial Intelligence: Reasoning and Overview (AI/ML)
- ECEN 4752/5752 Communication Laboratory
- ECEN 5002/5772 Digital Video (AI/ML)
- Tentative teaching schedule
- Introduction to the area
Suggested Supplemental Courses for MS Students
- MS students are required to take at least four graduate courses on this page.
- Courses related to Embedded Systems is a great supplement.
Suggested Supplemental Courses for PhD Students
- Optimization, Linear Programming, Matrix Analysis, Courses from Applied Math and Computer Science Departments
- Real Analysis and Probability Theory from Math or Applied Math Department
- CSCI 5254 Convex Optimization and Its Applications
- or APPM 5630 Advanced Convex Optimization
- CSCI7000-013 Learning and Sequential Decision Making
- ECEN 5008 Online Convex Optimization
- APPM 5560 Markov Processes, Queues, and Monte Carlo Simulations, APPM 6550 Introduction to Stochastic Processes
- Discrete Mathematics and Number Theory
- Matrix Analysis
- APPM 5520 Introduction to Mathematical Statistics I
- CSCI 5922 Neural Networks and Deep Learning
- Math 6310 Real Analysis I, Math 6320 Real Analysis II
- Or APPM 5440 Applied Analysis 1, APPM 5450 Applied Analysis 2