Georgia Institute of Technology

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, mathematics, engineering, or a related field with a strong GPA (typically 3.0+) is required, along with proficiency in programming and mathematics; GRE is optional for most applicants.

About This Program

This graduate specialization provides rigorous training in the algorithms and statistical models that allow systems to learn from data.

Career Outcomes

Thrive as Machine Learning Engineer in Cross-Industry AI with machine learning expertise

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

What You'll Learn

• Develop and implement machine learning models for real-world data analysis
• Apply deep learning techniques to complex datasets and applications
• Design algorithms for supervised, unsupervised, and reinforcement learning
• Evaluate and optimize ML systems using statistical and probabilistic methods

Curriculum Highlights

The program requires core algorithms and machine learning coursework, supplemented by electives in visual analytics, social computing, and modeling.

Top Employers

Top employers include Google, Amazon, Microsoft, Meta, and companies like Nvidia partnering on AI research.

Admissions

A bachelor's degree in computer science, mathematics, engineering, or a related field with a strong GPA (typically 3.0+) is required, along with proficiency in programming and mathematics; GRE is optional for most applicants.

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: Optional
• TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)