Howard University
Traditional MS in Computer Science - Algorithms and Machine Learning
How this program compares
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Admission Snapshot
Typical admitted student: A bachelor's degree in computer science, mathematics, or a related field with a minimum GPA of 3.0 is required, along with programming experience and coursework in algorithms or data structures. GRE scores are often optional or not required for many programs.
About This Program
A graduate program (MCS) providing intensive preparation in the analysis and design of computing systems to solve complex issues in healthcare, transportation, and data science.
Career Outcomes
Excel as Machine Learning Engineer in Cross-Industry AI with machine learning expertise
- 1. Machine Learning Engineer
- 2. Algorithms Researcher
- 3. Data Scientist
- 4. AI Software Developer
What You'll Learn
- Design and analyze efficient algorithms for complex computational problems
- Build and evaluate machine learning models using supervised and unsupervised techniques
- Implement deep learning architectures for pattern recognition and prediction
- Apply statistical methods to large datasets for informed decision-making
Curriculum Highlights
Offers thesis and non-thesis tracks with core courses in software engineering, operating systems, and computability, specializing in algorithms and machine learning.
Top Employers
Top employers include Google, Microsoft, Amazon, and Meta.
Admissions
A bachelor's degree in computer science, mathematics, or a related field with a minimum GPA of 3.0 is required, along with programming experience and coursework in algorithms or data structures. GRE scores are often optional or not required for many programs.
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 or Not Required
- TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)
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