Overview
The M.Sc. in Machine Learning at Columbia University provides students with a comprehensive foundation in the algorithms and mathematical models used to develop intelligent systems. This advanced degree is tailored for individuals aiming to master the technical complexities of data-driven prediction and automated decision-making across various industries. Students engage with a curriculum that balances theoretical depth with practical applications in modern computing environments.
Why Machine Learning at Columbia University?
Studying at this institution offers access to a premier Department of Computer Science known for its pioneering research and academic excellence. The programme is situated within a vibrant research ecosystem, allowing students to explore diverse applications in fields such as bioinformatics, finance, and robotics. With a focus on pushing the frontiers of knowledge, the university provides a collaborative environment where students can interact with world-class faculty and utilise extensive computing research facilities.
Tuition Fee Breakdown
- International fee: USD 64800 per year
- National fee: USD 64800 per year
- Local fee: USD 64800 per year
Visit the Fees and Funding section for a breakdown in your local currency.
Syllabus
Modules may include:
- Computational Learning Theory
- Machine Learning
- Neural Networks & Deep Learning
- Computer Vision
- Machine Learning Theory
- Unsupervised Learning
- Causal Inference
- Natural Language Processing
- Computational Aspects of Robotics
Careers with Machine Learning
Graduates are prepared for high-impact roles in a variety of expanding sectors where data analysis is critical. The skills acquired during the programme are highly sought after in industries such as finance for fraud detection and algorithmic trading, as well as in information retrieval and intelligent systems development. Alumni often find success in specialised areas including bioinformatics, perception, and large-scale data science, taking on roles that involve designing and implementing complex machine learning solutions for global organisations.
Programme Structure
Courses include:
- Computational Learning Theory
- Machine Learning
- Machine Learning for Data Science
- Advanced Machine Learning
- Neural Networks Deep Learning
- Machine Learning Theory
- Natural Language Processing
Key information
Duration
- Full-time
- 12 months
Start dates & application deadlines
- Starting
- Apply before
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- Starting
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Language
Credits
Delivered
Campus Location
- Manhattan, United States
Disciplines
Machine Learning View 104 other Masters in Machine Learning in United StatesWhat students do after studying Computer Science & IT
This information is based on LinkedIn alumni data for graduates from 2018 to 2024 and may not fully represent all career outcomes
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
Other requirements
General requirements
- Transcript
- Personal Statement
- Recommendation Letter
- Financial Support Document
Tuition Fees
-
International Applies to you
Applies to youNon-residents64800 USD / year≈ 64800 USD / year - Out-of-State64800 USD / year≈ 64800 USD / year
-
Domestic
Applies to youIn-State64800 USD / year≈ 64800 USD / year
Living costs
Manhattan
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Financing
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Funding
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Scholarships Information
Below you will find Master's scholarship opportunities for Machine Learning.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
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