Carnegie Mellon University

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 with a strong background in computer science, mathematics, probability, statistics, and programming skills is required. International applicants need TOEFL, IELTS, or Duolingo scores.

About This Program

This foundational program introduces the core principles of data science and machine learning for technically-savvy professionals.

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/ML Analyst
• 4. Data Science Consultant

What You'll Learn

• Fundamental machine learning algorithms and model evaluation techniques.
• Data preprocessing, cleaning, and feature engineering for analysis.
• Statistical inference and probability models for data-driven decisions.
• Practical implementation of ML models using Python and related tools.

Curriculum Highlights

The structure focuses on computing systems, analytics, and human-centered data science through rigorous, credit-bearing graduate coursework.

Top Employers

Top employers include tech leaders like Google, Amazon, Microsoft, and Meta, as well as financial firms and research organizations leveraging AI and data science.

Admissions

A bachelor's degree with a strong background in computer science, mathematics, probability, statistics, and programming skills is required. International applicants need TOEFL, IELTS, or Duolingo scores.

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+)