Overview
The B.Sc. in Statistics and Machine Learning at Carnegie Mellon University is an interdisciplinary programme jointly administered by the Department of Statistics and Data Science and the Department of Machine Learning. This rigorous course of study is specifically designed for students who wish to master the complexities of statistical computation and the interpretation of massive datasets. By combining mathematical foundations with cutting-edge computer science, the curriculum ensures that graduates are equipped to handle the evolving demands of the global data landscape.
Why Statistics and Machine Learning at Carnegie Mellon University?
Carnegie Mellon University is world-renowned for its pioneering contributions to statistical theory and the development of machine learning. Students benefit from a friendly yet energetic environment where they interact regularly with faculty members who are global experts in their fields. The programme provides access to exceptional computing resources and involves undergraduates in research that spans from pure mathematics to applied frontiers like neuroscience, finance, and genetics. This collaborative atmosphere ensures that students learn to apply abstract tools to real-world problems alongside leading researchers.
Tuition Fee Breakdown
- International fee: USD 67020 per year
- National fee: USD 67020 per year
- Local fee: USD 67020 per year
Visit the Fees and Funding section for a breakdown in your local currency.
Syllabus
Modules may include:
- Reasoning with Data
- Methods for Statistics & Data Science
- Probability and Statistical Inference
- Statistical Computing
- Modern Regression
- Advanced Methods for Data Analysis
- Imperative Computation
- Algorithms and Advanced Data Structures
- Machine Learning
Careers with Statistics and Machine Learning
Graduates from the Department of Statistics and Data Science are highly sought after in the marketplace due to their mastery of core analytical concepts and collaborative experience. Recent alumni have secured positions at leading global organisations, including Google, Goldman Sachs, Deloitte, and Morgan Stanley. Others have pursued research roles at the U.S. Census Bureau or the National Security Agency. Furthermore, many students progress to prestigious postgraduate programmes at institutions such as Harvard, MIT, Stanford, and Oxford to continue their specialised training in data science and econometrics.
Programme Structure
Courses Include:
- Multivariate Analysis
- Calculus in Three Dimensions
- Multidimensional Calculus
- Experimental Design for Behavioral and Social Sciences
- Statistics of Inequality and Discrimination
Key information
Duration
- Full-time
- 48 months
Start dates & application deadlines
- Starting
- Apply before
-
Language
Prepare for Your English Test
AI-powered IELTS feedback. Clear, actionable, and tailored to boost your writing & speaking score. No credit card or upfront payment required.
- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Credits
Carnegie Mellon has adopted the method of assigning a number of “units” for each course to represent the quantity of work required of students.
Delivered
Campus Location
- Pittsburgh, United States
Disciplines
Statistics Machine Learning View 72 other Bachelors in Machine Learning in United StatesWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
Prepare for Your English Test
AI-powered IELTS feedback. Clear, actionable, and tailored to boost your writing & speaking score. No credit card or upfront payment required.
- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Other requirements
General requirements
- Common Application
- $75 Application Fee
- Official High School Transcript
- Standardized Testing Scores
- Secondary School Counselor Evaluation
- Teacher Recommendation
- Common Application Essay
- Common Application Writing Supplement
Tuition Fees
-
International Applies to you
Applies to youNon-residents67020 USD / year≈ 67020 USD / year - Out-of-State67020 USD / year≈ 67020 USD / year
-
Domestic
Applies to youIn-State67020 USD / year≈ 67020 USD / year
Living costs
Pittsburgh
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
Need help with your student visa?
Get personalized guidance from a certified VFS Global advisor and save 20% through Studyportals.
- Avoid common visa mistakes and delays
- Know exactly what documents you need
- Get a clear checklist tailored to your situation
In order for us to give you accurate scholarship information, we ask that you please confirm a few details and create an account with us.
Scholarships Information
Below you will find Bachelor's scholarship opportunities for Statistics and Machine Learning.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility