The Applied Machine Learning for Chemists and Engineers certificate is housed in the Department of Chemical and Petroleum Engineering (C&PE) and is focused on interdisciplinary coursework and research. The core departments are C&PE, Chemistry, and EECS (Electrical Engineering and Computer Science) but students from other departments may apply. The certificate trains graduate students on interdisciplinary skills and competencies in machine learning to pursue a wide range of careers. Students will learn to work on collaborative and interdisciplinary machine learning projects through research and coursework which will provide a competitive edge when applying to jobs after graduation. Students complete four courses: two core courses, one research course, and one data science course (10 total credits) which can align with their M.S./Ph.D. electives to minimize additional coursework requirements.
Standard Admission Requirements for all Graduate Programs
- All applicants must meet the requirements outlined in the Admission to Graduate Study policy.
- Bachelor’s degree: A copy of official transcripts showing proof of a bachelor's degree (and any post-bachelor’s coursework or degrees) from a regionally accredited institution, or a foreign university with equivalent bachelor's degree requirements is required.
- English proficiency: Proof of English proficiency for non-native or non-native-like English speakers is required. There are two bands of English proficiency, including Admission and Full proficiency. For applicants to online programs, Full proficiency is required.
Additional Program Admission Requirements
Students must be eligible for graduate standing at the University of Kansas (certificate, degree, or non-degree seeking). At application, we require:
- Resume or CV
- Brief, one-page statement of purpose
Currently enrolled Department of Chemical and Petroleum Engineering graduate students: email the Graduate Program Coordinator cpeGrad@ku.edu and nrt@ku.edu with the above documents to be enrolled in the certificate.
Current KU graduate students: apply at https://gograd.ku.edu/register/current_ku_certificate. The application should be no cost.
Certificate-seeking only applicants (not currently enrolled at KU): apply at https://gradapply.ku.edu/apply with the above documents and contact information for one professional reference.
Deadlines
This program admits students on a rolling basis. Applications can be accepted two-week in advance of semester start in Spring, Summer, and Fall.
Students complete four courses: two core courses, one research course, and one data science course.
Core Courses
Course List | Code | Title | Hours |
| C&PE 715 | Topics in Chemical and Petroleum Engineering: _____ (Applied Machine Learning for Scientists and Engineers) | 3 |
| C&PE 802 | CEBC Colloquium | 1 |
| Total Hours | 4 |
Choose One (3 cr hour) Research Course:
Choose One (3 cr hour) Data Science Course:
Course List | Code | Title | Hours |
| C&PE 778 | Applied Optimization Methods | 3 |
| CHEM 914 | Computational Methods in Physical Sciences | 3 |
| EECS 649 | Introduction to Artificial Intelligence | 3 |
| EECS 835 | Advanced Data Science | 3 |
| EECS 836 | Machine Learning | 3 |
| EECS 767 | Information Retrieval | 3 |
At the completion of this program, students will be able to:
- Apply machine learning techniques to solve chemistry/engineering questions.
- Affectively communicate data to a mixed audience of scientists, engineers, and the public.
- Critically interpret machine learning outputs and summarize for publication.
- Understand how exclusion has limited advancements in chemistry and engineering. Students will also have a greater understanding of other cultures and identities.
- Identify their transferable skillsets and communicate the environmental and community implications of their research.
- Collaborate on research projects across disciplines and areas of expertise.
