Certificate in Applied Machine Learning

Electrical and Computer Engineering program will be offering a Certificate of Undergraduate Studies (CUGS) in Applied Machine Learning in Engineering. This CUGS will consist of 12-13 credits and is designed to provide a breadth and depth to students who want to specialize in one of the fastest growing fields in all of sciences and engineering.

The ECE Department has significant expertise in machine learning, and has been regularly teaching related courses since 2001. This CUGS puts the existing expertise and the courses together in one package allowing students to gain meaningful background that will prepare them for a career in machine learning and/or graduate programs. A unique aspect of this CUGS is the practical hands-on experience that it provides: the CUGS feature four classes, all of which has their own project components. This CUGS also provides access – primarily for non Engineering students – to Rowan Engineering’s signature hallmark, Senior Engineering Clinic (to be taken twice over two semesters), where students work on projects addressing real-world unsolved problems, many of which are externally funded. Hence, through this four-class sequence, the Applied Machine Learning in Engineering CUGS will provide breath and depth in theoretical foundations of machine learning, as well as a year-long practical hands-on real-world project experience.

The completion of this CUGS will provide students with the necessary tools to start a career in machine learning as it applied to engineering, and/or continue their education through graduate programs. Due to rapid growth of machine learning as a well-established field of science and engineering, we expect the graduates of this program to find high-paying jobs and/or admission to renown graduate programs. In fact, the highest paid graduates of our program are typically hired for machine learning related positions.

Requires Courses (two courses)

• ECE 09.455 Machine Learning
  
  
• ECE 09.458 Introduction to Reinforcement Learning 
  or
• ECE 09.495 Emerging Topics in Computational Intelligence, Machine Learning and Data Mining

Electives (choose any two of the following)

• ECE 09.454 Introduction to Artificial Neural Networks
• ECE 09.466 Systems, Devices and Algorithms in Bioinformatics
• ENGR 01.403 Senior Engineering Clinic^♦– WI
  (must be taken twice over two semesters, to count as one elective)
• ENGR 01.411 Introduction to Engineering Optimization
• ECE 09.458 Introduction to Reinforcement Learning^◊
• ECE 09.495 Emerging Topics in Computational Intelligence, Machine Learning and Data Mining^◊
• ECE 09.4XX Deep Learning (coming soon)

^♦ Must be enrolled in one of the specific sections of Senior Engineering Clinic that focuses on machine learning topics. Those sections will be announced every semester.

^◊ If not already taken as one of the required classes.

IMPORTANT: 

Double counting policy: For all CUGS offered by the ECE Department, at most two courses can be double counted to satisfy the CUGS and the B.S. in ECE degree requirements. Therefore, ECE students pursuing this or any other CUGS must take at least two courses above and beyond their BS in ECE degree requirements. Clinics may not be used to satisfy the elective requirements of more than one CUGS. Generally speaking, each CUGS requires at least two courses exclusively counted towards that CUGS and nothing else. Non-ECE students who pursue this CUGS should follow the course double-counting policies of the department in which their major resides.