BachelorOn-CampusFull-Time

University of California, Davis

BS in Statistics: Machine Learning Track

Davis, California4 years$56K total tuition
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Last reviewed June 2026 by the AI Graduate editorial team. Program data is compiled and verified from official university sources β€” see our methodology.

How this program compares

At an estimated $56.0K in total tuition, the BS in Statistics: Machine Learning Track sits roughly 35% below the $86.6K average for AI bachelor's programs in our database β€” placing it in the 48th percentile on cost among the 232 we track at this level.

Est. Salary$105,000
Job Growth+30%
Top RoleData Scientist
FormatOn-Campus

Admission Snapshot

Degree Required
High School Diploma
Duration
4 years
Est. Tuition
$56K total
Format
On-Campus
Schedule
Full-Time
GRE / GMAT
Not Required
Concentrations
Machine Learning, AI Engineering / Applied AI

Typical admitted student: High school diploma or equivalent with a competitive GPA (typically 3.5+), SAT/ACT scores optional, and strong preparation in mathematics including calculus and linear algebra.

About This Program

This undergraduate track focuses on the algorithmic and theoretical foundations of statistical learning to build predictive and explanatory models for large-scale, complex data. Coursework concentrates on Machine Learning and AI Engineering / Applied AI. Most students complete it in about 4 years.

Estimated total tuition is $56.0K, below the $86.6K average for AI bachelor's programs in our database and in the 48th percentile on cost at this level. That puts it in the mid-range on price among comparable programs.

Launch Data Scientist career in Cross-Industry AI with data science focus Graduates frequently move into roles such as Data Scientist, with reported salaries around $105,000.

Career Outcomes

Launch Data Scientist career in Cross-Industry AI with data science focus

  • 1. Machine Learning Engineer
  • 2. Data Scientist
  • 3. Statistical Modeler
  • 4. Predictive Analytics Specialist

What You'll Learn

  • Apply statistical learning methodologies to predictive modeling for complex datasets.
  • Analyze high-dimensional data using algorithmic and theoretical approaches.
  • Build and evaluate machine learning models for explanatory and predictive purposes.
  • Interpret statistical models and communicate findings effectively.

Curriculum Highlights

The curriculum includes core subjects such as regression analysis and mathematical statistics, alongside specialized courses in statistical learning, multivariate data analysis, and Bayesian inference.

Top Employers

Top employers include tech companies like Google, Amazon, and Microsoft, as well as research institutions, financial firms, and government agencies.

Admissions

High school diploma or equivalent with a competitive GPA (typically 3.5+), SAT/ACT scores optional, and strong preparation in mathematics including calculus and linear algebra.

Application Materials

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

Academic Requirements

  • Degree Required: High School Diploma
  • GRE/GMAT: Not Required
  • TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)

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