Howard University
Accelerated 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 or related field with a minimum GPA of 3.0 is required, along with programming experience and coursework in algorithms, data structures, and linear algebra. GRE scores are often optional for accelerated MS programs.
About This Program
An accelerated graduate program (MCS) providing intensive preparation in the analysis and design of computing systems to solve complex issues in healthcare and transportation.
Career Outcomes
Position as Machine Learning Engineer in Engineering 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 large-scale computational problems.
- Implement and evaluate machine learning models for predictive analytics.
- Optimize algorithms using advanced data structures and complexity analysis.
- Apply probabilistic methods to real-world machine learning challenges.
Curriculum Highlights
The curriculum offers a fast-track structure with core courses in software engineering, operating systems, and computability, focusing on algorithmic and machine learning specializations.
Top Employers
Top employers include Google, Amazon, Microsoft, Meta, and tech firms specializing in AI and algorithms.
Admissions
A bachelor's degree in computer science or related field with a minimum GPA of 3.0 is required, along with programming experience and coursework in algorithms, data structures, and linear algebra. GRE scores are often optional for accelerated MS 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
- TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)
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