Texas Tech University

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, engineering, mathematics, or a related field with a minimum GPA of 3.0 is required, along with relevant programming experience or coursework in data structures and algorithms.

About This Program

A 12-credit graduate credential designed for working professionals to gain essential skills in modern artificial intelligence and machine learning without enrolling in a full degree.

Career Outcomes

Build machine learning skills to advance as Machine Learning Engineer in Cross-Industry AI

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

What You'll Learn

• Core principles of artificial intelligence and search algorithms
• Supervised and unsupervised machine learning techniques
• Implementation of neural networks and deep learning models
• Processing and analysis of natural language and visual data

Curriculum Highlights

The curriculum consists of four courses covering core AI principles, machine learning algorithms, deep learning, and specialized topics like deep reinforcement learning or robotics.

Top Employers

Top employers include tech companies like Google, Microsoft, Amazon, and IBM, as well as research institutions and defense contractors.

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 relevant programming experience or coursework in data structures and algorithms.

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: Not Required
• TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)