In an era where data-driven decision-making is integral to the world's most influential industries, the Department of Electrical and Computer Engineering (ECE) at Rutgers University-New Brunswick is proud to present a timely and crucial offering: a 12-credit graduate certificate program in Machine Learning.
The applications of Machine Learning are vast and rapidly evolving, powering innovations in sectors such as technology, healthcare, finance, transportation, manufacturing, agriculture, telecommunications, education, energy, and even creative industries like music and film, among others. The ability to interpret complex datasets and forecast trends is not just a highly sought-after skill, but a necessity in today's data-centric world.
At Rutgers ECE, we recognize this seismic shift and have meticulously curated a certificate program that goes beyond mere theory. Our mission is to equip our students with a robust understanding of machine learning techniques, enabling them to address real-world engineering problems and navigate various software packages used across numerous electrical and computer engineering applications. In essence, we aim to transform learners into practitioners.
Our department boasts an exceptional faculty with both academic and industry experience, a diverse and comprehensive range of courses, and a learning environment that fosters collaboration, innovation, and excellence. Our program emphasizes both statistical learning theory and deep learning, integral courses in our renowned ECE graduate program, providing students with a distinct edge in their professional pursuits.
Eligibility: This opportunity isn't confined to just Rutgers students or those enrolled in the ECE department. We have extended the scope of this program to benefit learners across various disciplines such as Computer Science, Mechanical Engineering, Biomedical Engineering, Data Science, Mathematics, Physics, Information Technology, Statistics, and even non-traditional fields where data analysis is crucial, like Business, Economics, and Social Sciences. Whether you're pursuing a PhD, MS, or simply aiming to secure a certificate, our Machine Learning program provides an enriching and versatile learning path. Moreover, some requirements for the certificate may also fulfill your existing graduate degree requirements, providing further academic flexibility.
Current ECE Students: Graduate students (non-matriculated, MS. or PhD) from the ECE department interested in the Machine Learning certificate do not need to apply separately. Interested students should simply notify the ECE Graduate Program Office at firstname.lastname@example.org of their intention to pursue the certificate, along with their intended course selection.
Current non-ECE Rutgers Students: Graduate students (MS or PhD) from departments other than ECE should submit a copy of their Rutgers transcripts, a letter of recommendation, and the intended course selection to ECE Graduate Program Office at email@example.com. Once notified by the ECE Graduate Program Office of the approval of their application, the students can start earning credits towards the certificate.
Prospective Students: Prospective students interested in our Machine Learning certificate program must meet the minimum requirement of having completed a bachelor's degree. Once this eligibility criterion is confirmed, you are invited to proceed with the application process via the Rutgers Graduate and Professional Admissions application portal. This application portal will guide you through the necessary steps, which include uploading your official transcripts and at least one letter of recommendation. Prospective students can also reach out to the ECE Graduate Program Office at firstname.lastname@example.org for further information about the application process.
Curriculum: In order to receive the certificate, students must complete four courses, equivalent to 12 credits, maintaining a GPA of at least 3.0. This coursework must include a minimum of two courses from List A, and a maximum of two courses from List B:
14:332:443 – Machine Learning for Engineers (or its graduate-level equivalent course)
16:332:515 – Reinforcement Learning for Engineers
16:332:530 – Introduction to Deep Learning
16:332:549 – Detection & Estimation Theory: Inference & Machine Learning for Engineers
16:332:561 – Machine Vision
16:332:509 – Convex Optimization
16:332:518 – Mobile Embedded Systems and On-Device AI
16:332:525 – Optimum Signal Processing
16:332:531 – Probabilistic Methods for Large Scale Signal Processing and Learning
16:332:532 – Multimodal Machine Learning for Sensing Systems
16:332:533 – Machine Learning for Inverse Problems
We understand that the landscape of Machine Learning is dynamic, and therefore our graduate curriculum is updated regularly to keep pace with the latest advancements. In light of this, additional courses beyond those mentioned above could be accepted towards the completion of this certificate, subject to the sole discretion of the ECE Graduate Program Director and subsequent approval from the School of Graduate Studies. This ensures our program remains flexible, current, and responsive to the evolving needs of the field.