MasterOn-Campus, Online, HybridFull-Time

The University of Texas at Tyler

MS in Computer Science - Machine Learning Specialization

Tyler, Texas2 years$19K total tuition
Visit Program Website β†—

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.

Est. Salary$130,000 Data Scientist
Job Growth+36%
Top RoleMachine Learning Engineer
FormatOn-Campus, Online, Hybrid

Admission Snapshot

Degree Required
Bachelor's degree in computer science or related technical field
Duration
2 years
Est. Tuition
$19K total
Format
On-Campus, Online, Hybrid
Schedule
Full-Time
GRE / GMAT
Required
Concentrations
Machine Learning, AI Engineering / Applied AI

Typical admitted student: Applicants must hold a bachelor's degree in computer science, mathematics, engineering, or a related technical field with a minimum GPA of 3.0. Prior coursework in programming, linear algebra, calculus, and data structures is typically required; GRE scores are often optional for professional tracks.

About This Program

A graduate program providing broad competence in computer science along with the opportunity to specialize in machine learning and data analytics for a rapidly evolving industry.

The MS in Computer Science - Machine Learning Specialization is a Master program at The University of Texas at Tyler in Tyler, Texas offered in a on-campus, online, hybrid format over 2 years with a focus on Machine Learning and AI Engineering / Applied AI with an estimated total tuition of $19K. Graduates commonly pursue careers as Machine Learning Engineer, with typical salaries around $130,000. Thrive as Machine Learning Engineer in Cross-Industry AI with machine learning expertise

Career Outcomes

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

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

What You'll Learn

  • Design, train, and optimize machine learning models for real-world applications across industries
  • Apply deep learning architectures and neural networks to complex data problems
  • Implement statistical methods and evaluation techniques for model validation and performance assessment
  • Develop end-to-end machine learning pipelines from data preprocessing through deployment and interpretation

Curriculum Highlights

The curriculum consists of foundational core courses in operating systems and programming languages, combined with electives in machine learning and digital forensics.

Top Employers

Top employers include Google, Amazon, Microsoft, Meta, Apple, OpenAI, and major financial institutions like JPMorgan Chase and Goldman Sachs.

Admissions

Applicants must hold a bachelor's degree in computer science, mathematics, engineering, or a related technical field with a minimum GPA of 3.0. Prior coursework in programming, linear algebra, calculus, and data structures is typically required; GRE scores are often optional for professional tracks.

Application Materials

  • Statement of Purpose: Required
  • Letters of Recommendation: 2–3
  • Resume: Required
  • Transcripts: Official transcripts required

Academic Requirements

  • Degree Required: Bachelor's degree in computer science or related technical field
  • GRE/GMAT: Optional for most MS programs
  • TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)

Student Reviews

Loading reviews...

Ready to Apply?

Visit the official program page for the latest deadlines, tuition, and application requirements.