Typical admitted student: A bachelor's degree in engineering, computer science, or a related quantitative field with a minimum GPA of 3.0 is required, along with demonstrated proficiency in programming (e.g., Python) and basic linear algebra.

About This Program

This graduate certificate program develops the capabilities required to apply machine learning tools to solve complex problems across a variety of application domains.

Career Outcomes

Gain deep learning skills to advance as Machine Learning Engineer in Engineering AI

1. ML Engineer for Engineering Systems
2. Data Scientist in Manufacturing
3. Predictive Analytics Specialist
4. AI Systems Engineer

What You'll Learn

Implement supervised and unsupervised ML models for engineering datasets
Apply deep learning techniques to optimize engineering systems
Develop predictive models for failure analysis and resource allocation
Integrate ML algorithms into real-world engineering applications

Curriculum Highlights

The program requires 12 credit hours, including a core machine learning course and electives such as data mining, visual analytics, or algorithms.

Top Employers

Top employers include engineering firms like Boeing, General Electric, Siemens, and tech companies such as Google and Amazon applying ML to industrial solutions.

Admissions

A bachelor's degree in engineering, computer science, or a related quantitative field with a minimum GPA of 3.0 is required, along with demonstrated proficiency in programming (e.g., Python) and basic linear algebra.

Application Materials

Statement of Purpose: Required
Letters of Recommendation: 2
Resume: Required
Transcripts: Official transcripts required

Academic Requirements

Degree Required: Bachelor's degree
GRE/GMAT: Not Required
TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)

Student Reviews

Loading reviews...

Ready to Apply?

Visit the official program page for the latest deadlines, tuition, and application requirements.

Visit Official Program Page ↗Compare Programs