Drexel University
MS in Artificial Intelligence and Machine Learning
Last reviewed June 2026 by the AI Graduate editorial team. Program data is compiled and verified from official university sources — see our methodology.
How this program compares
At an estimated $66.0K in total tuition, the MS in Artificial Intelligence and Machine Learning sits about 56% above the $42.4K average for AI master's programs in our database — placing it in the 82nd percentile on cost among the 531 we track at this level. It is one of the 57% of programs in our database offered fully or partly online.
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, along with programming experience and knowledge of probability and statistics. GRE is recommended for international students or those with GPA below 3.0.
About This Program
Drexel University's MS in Artificial Intelligence and Machine Learning is anchored by Drexel's signature co-op model, which integrates real industry experience into the degree. The curriculum spans machine learning, deep learning, and applied AI.
Located in Philadelphia, Drexel offers strong employer ties across the Northeast corridor, making the program attractive to students who value paid, hands-on experience alongside coursework.
Why students choose it: Drexel's co-op model delivers real industry AI experience inside the degree.
Career Outcomes
Advance as Data Scientist in Cross-Industry AI with software engineering expertise
- 1. Machine Learning Engineer
- 2. AI Research Scientist
- 3. Data Scientist
- 4. Computer Vision Engineer
What You'll Learn
- Develop and implement machine learning models for supervised and unsupervised learning tasks.
- Design deep neural networks for complex pattern recognition in data.
- Apply natural language processing techniques to analyze and generate human language.
- Build computer vision systems for image and video processing.
- Optimize AI systems using reinforcement learning and probabilistic methods.
Curriculum Highlights
The curriculum is organized around three focus areas: data science and analytics, theory of computation, and AI applications, culminating in a two-term capstone project.
Top Employers
Top employers include Google, Amazon, Microsoft, and Meta.
Admissions
A bachelor's degree in computer science, engineering, mathematics, or a related field with a minimum GPA of 3.0 is required, along with programming experience and knowledge of probability and statistics. GRE is recommended for international students or those with GPA below 3.0.
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: Recommended (for GPA below 3.0 or international students)
- TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)
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