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 statistics and linear algebra is preferred.

About This Program

This program offers a focused credential in the mathematical and computational foundations of machine learning and its industrial applications.

Career Outcomes

Gain machine learning skills to advance as Machine Learning Engineer in Cross-Industry AI

1. Machine Learning Engineer
2. Data Scientist
3. AI Specialist
4. ML Operations Engineer

What You'll Learn

Implement supervised and unsupervised machine learning algorithms for predictive modeling.
Apply deep learning techniques to image recognition and sequence data.
Develop natural language processing models for text analysis and generation.
Optimize machine learning pipelines using statistical methods and computational tools.

Curriculum Highlights

The curriculum includes core courses in statistical learning, deep learning, and advanced data-driven algorithmic design.

Top Employers

Top employers include tech firms like Google, Amazon, Microsoft, and Meta, as well as finance, healthcare, and consulting companies applying machine learning solutions.

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 statistics and linear algebra 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+)

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