Overview Outcomes Courses Admission Instructors
Program overview
This certificate will provide students the technical expertise for data-driven analysis of complex engineering systems, which will enable optimal decision making for executing the processes and operations in such systems. Those with this certificate will be able to understand and apply machine learning and statistical inference techniques to model and predict the outcomes of the systems under varying operating conditions.
Through the Data Analytics for Systems Operations (DASO) certificate, students will gain expertise in the design and analysis of experiments, including discrete event simulation, which are typically not covered in other engineering certificate programs. Therefore, students will acquire the credentials to assume lead technical responsibilities for running large-scale product/process development and project operations.
Learning outcomes
- Conduct design of experiments, analyze the data, interpret the results, and draw sound conclusions.
- Apply the right optimization model to different industries such as health care, transportation and environmental ecology, and validate the models using formal procedures such as cross-validation.
- Use existing software and R/Python packages to implement statistical predictive models and analyze real-world data.
- Identify, formulate, and solve data analytics problems by applying benchmark machine learning models such as regression model, decision tree, support vector machine, and LASSO to analyze the data generated from a real-world system.
- Use toolboxes for state-of-the-art machine learning models (deep neural networks, large language models, vision-language models, etc.) to analyze datasets from the real-world.
- Apply different kinds of simulation models: discrete event-based simulation, Monte Carlo simulation, agent-based simulation, etc. with input specification, output analysis, and variance reduction.
- Communicate the results and outcomes effectively to a wide range of audiences with varying knowledge in data analytics.
- Function effectively on a team whose members together provide leadership, create a collaborative and inclusive environment, establish goals, plan tasks, and meet objectives.
Courses
Completion of the certificate requires earning 15 credits among our offered courses. You may be able to take individual courses without enrolling in the certificate program.
Admission requirements
Applicants will need to have a 3.0 cumulative grade-point-average on a 4 point scale. In addition, applicants need to submit a resume or curriculum vitae (CV), statement of purpose, and unofficial/electronic transcripts to be considered for admission.