University of California, Berkeley

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 with a strong quantitative background, such as in computer science, statistics, or related fields, is required along with transcripts, a statement of purpose, resume, and two professional letters of recommendation; GRE/GMAT scores are optional.

About This Program

A multidisciplinary online program preparing data professionals to solve real-world problems using complex and unstructured data.

Career Outcomes

Position as Data Engineer in Cross-Industry AI with machine learning expertise

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

What You'll Learn

• Design research studies and clean large-scale datasets for analysis.
• Engineer data pipelines and apply machine learning models to real-world problems.
• Create effective data visualizations to communicate insights.
• Navigate ethical issues in data privacy and information systems.

Curriculum Highlights

The curriculum covers research design, applied machine learning, data engineering, information ethics, and a culminating capstone project.

Top Employers

Top employers include Google, Amazon, Meta, and consulting firms like McKinsey and Deloitte.

Admissions

A bachelor's degree with a strong quantitative background, such as in computer science, statistics, or related fields, is required along with transcripts, a statement of purpose, resume, and two professional letters of recommendation; GRE/GMAT scores are optional.

Application Materials

• Statement of Purpose: Required
• Letters of Recommendation: 2
• 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+)