University of Wisconsin–Milwaukee

How this program compares

Benchmark this program against our national recognition pages and use the key guides below to evaluate ROI, admissions difficulty, and outcomes.

Admission Snapshot

Typical admitted student: A bachelor's degree in computer science, engineering, mathematics, or a related field with a minimum GPA of 3.0 is required; relevant programming experience or coursework in data structures and algorithms is preferred.

About This Program

A smart upskilling credential for professionals and graduate students designed to provide advanced training in the global AI market.

Career Outcomes

Build machine learning skills to advance as AI Engineer in Cross-Industry AI

• 1. Machine Learning Engineer
• 2. AI Data Scientist
• 3. NLP Specialist
• 4. Computer Vision Engineer

What You'll Learn

• Design and implement machine learning models for predictive analytics
• Apply deep learning techniques to image and sequence data
• Develop natural language processing systems for text analysis
• Evaluate AI systems for bias, ethics, and real-world deployment

Curriculum Highlights

The 15-credit curriculum covers intro to AI, machine learning fundamentals, and applications such as natural language processing and computer vision.

Top Employers

Top employers include tech companies like Google, Amazon, Microsoft, and IBM, as well as industries adopting AI in healthcare, finance, and manufacturing.

Admissions

A bachelor's degree in computer science, engineering, mathematics, or a related field with a minimum GPA of 3.0 is required; relevant programming experience or coursework in data structures and algorithms is preferred.

Application Materials

• Statement of Purpose: Required
• Letters of Recommendation: 2–3
• 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+)