Eligibility Requirements for Columbia University M.S. in Data Science

To be eligible for the Columbia University MS in Data Science program, applicants must meet specific criteria and submit several required documents. Below is a detailed table showing the admission requirements for the program.

Requirements Details
Undergraduate Degree A bachelor's degree from an accredited institution.
Quantitative Coursework Prior coursework in calculus, linear algebra, and related quantitative subjects.
Computer Programming Coursework Introductory coursework in computer programming.
Online Application Complete and submit the online application form.
Personal Statement A statement outlining your interest in the program and career goals.
Transcripts Uploaded transcripts from all post-secondary institutions attended.
Recommendation Letters Three letters of recommendation from academic or professional references.
Curriculum Vitae / Résumé An updated CV or résumé detailing academic and professional experience.
GRE Scores Optional for 2023 applications.
Application Fee $85 non-refundable application fee.
English Proficiency Test TOEFL, IELTS, or PTE Academic scores required for international applicants.

Any Any Discipline degree

UG Requirement

Test Scores Requirement

ExamRequirement

Program Eligibility URL:https://datascience.columbia.edu/education/programs/m-s-in-data-science/admissions/

Columbia University M.S. in Data Science Rankings

QS World University Rankings by Subject 2023: Data Science

3

About Columbia University

Columbia University, located in the heart of New York City, is one of the most prestigious institutions of higher education in the world. Founded in 1754 as King’s College, Columbia is recognized for its rigorous academic programs, distinguished faculty, and vibrant campus life. As a member of the Ivy League, Columbia offers a diverse range of undergraduate and graduate programs, attracting students from around the globe.

The university's total enrollment exceeds 33,000 students, including approximately 8,300 undergraduates, fostering an intellectually stimulating environment that encourages innovation and critical thinking. For those pursuing the Columbia University MS in Data Science, the combination of world-class education, a vibrant urban setting, and a strong global network makes Columbia an exceptional choice for advancing their careers and broadening their horizons.

Columbia University M.S. in Data Science Program Description

The Columbia University M.S. in Data Science program equips students with essential skills and knowledge to excel in the evolving field of data science. This interdisciplinary program integrates courses from computer science, statistics, and engineering, offering a comprehensive education that covers the technical and ethical aspects of data analysis. Students engage in hands-on learning through real-world projects and industry collaboration.

Columbia's M.S. in Data Science program emphasizes research and innovation, encouraging exploration in areas like machine learning and big data analytics. With access to world-class faculty and New York City's vibrant entrepreneurial ecosystem, students have ample networking and career opportunities. The program's focus on practical applications and ethical considerations prepares graduates to make impactful contributions in various sectors.

Program URL:https://datascience.columbia.edu/education/programs/m-s-in-data-science/

Columbia University M.S. in Data Science Program Curriculum

Program Curriculum URL:https://datascience.columbia.edu/education/programs/m-s-in-data-science/

  • Applied Machine Learning
  • Applied Deep Learning
  • Causal Inference for Data Science
  • Data Analytics Pipeline
  • Elements of Data Science
  • Machine Learning with Probabilistic Programming
  • Computational Models of Social Meaning
  • Deep Learning for Computer Vision, Speech, and Language
  • Personalization Theory & Application
  • Big Data in Finance
  • Applied Machine Learning for Financial Modeling and Forecasting
  • Applied Machine Learning for Image Analysis

Electives

  • Applied Machine Learning
  • Applied Deep Learning
  • Causal Inference for Data Science
  • Data Analytics Pipeline
  • Elements of Data Science
  • Machine Learning with Probabilistic Programming
  • Computational Models of Social Meaning
  • Deep Learning for Computer Vision, Speech, and Language
  • Personalization Theory & Application
  • Big Data in Finance
  • Applied Machine Learning for Financial Modeling and Forecasting
  • Applied Machine Learning for Image Analysis
  • Computer Systems for Data Science
  • Machine Learning for Data Science
  • Algorithms for Data Science
  • Data Science Capstone and Ethics
  • Probability and Statistics for Data Science
  • Exploratory Data Analysis and Visualization
  • Statistical Inference and Modeling

Columbia University also offers various clubs and associations for students in the MS in Data Science program, providing opportunities for involvement, learning, and networking:

  • Data Science Central
  • Digital Analytics Association
  • Columbia Data Science Society
  • Columbia Association for Women in Mathematics

Columbia University M.S. in Data Science Acceptance Rate

The acceptance rate for the Columbia University MS in Data Science (M.S. in Data Science) program is highly competitive,  around 10-15%.

Program Fee & Related Expenses

Understanding the financial commitment for the Columbia University MS in Data Science program is crucial for prospective students. The tuition fee for the academic year 2024-2025 is set at approximately $33,932. Additionally, students should plan for other expenses such as living costs, health insurance, books, and supplies. These additional costs can significantly impact the overall budget.

Below is a detailed breakdown of the program fees and related expenses for the M.S. in Data Science at Columbia University.

Fees Component Amount (USD)
Tuition Fees $33,932
Application Fee $85
Estimated Living Expenses $18,958
Health Insurance (Annual) $2,000 (approx.)
Books and Supplies $1,000 (approx.)
Total Estimated Cost $56,975 (approx.)

Application Documents for Columbia University M.S. in Data Science

Mandatory Application Documents

  • Passport

  • 10th Marksheet

  • 12th Marksheet

  • College Transcript

  • Semester Marksheets

  • Consolidated Marksheets

  • Graduation/Provisional Certificate

  • IELTS/TOEFL/DTE/PTE

  • GRE

    Columbia University M.S. in Data Science Deadlines

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    Employment, Salary & Career Statistics

    The Master of Science in Data Science program at Columbia University is recognized for producing highly skilled graduates who excel in various industries. The program’s rigorous curriculum covers key areas such as machine learning, statistical modeling, and data analysis, making its graduates attractive to top employers.

    Strong Employment Outcomes

    Graduates from the Columbia MS in Data Science program enjoy high employment rates, with most securing jobs within six months of graduation. The average starting salary is competitive, often exceeding $120,000, reflecting the high demand for their skills. The program’s reputation and the robust support from Columbia’s career services significantly contribute to these successful outcomes.

    Diverse Career Paths

    The program equips students with versatile skills, leading to roles such as Data Scientist, Machine Learning Engineer, and Data Analyst. Graduates find opportunities across various industries, including technology, finance, healthcare, and consulting.

    Career Support

    Columbia University offers extensive career services, including personalized coaching, resume reviews, and networking events. These resources, along with strong industry connections and a vast alumni network, provide a significant advantage in the job market.

    Employment Data by Industry

    Industry Common Roles Employers Average Starting Salary
    Technology Data Scientist, Machine Learning Engineer Google, Amazon, IBM $120,000 - $140,000
    Finance Quantitative Analyst, Data Scientist Goldman Sachs, JPMorgan Chase $110,000 - $130,000
    Healthcare Data Analyst, Bioinformatics Specialist Pfizer, Johnson & Johnson $100,000 - $120,000
    Consulting Data Science Consultant, Strategy Analyst McKinsey & Company, Deloitte $115,000 - $135,000
    Retail & E-commerce Data Analyst, Business Intelligence Analyst Amazon, Walmart $100,000 - $125,000

    The Columbia University MS in Data Science program offers exceptional career prospects, with high employment rates and competitive salaries across various industries. The program's comprehensive curriculum and strong career support services ensure graduates are well-prepared for success in their chosen fields.

    135,000

    Average Starting Salary

    Companies Recruiting Columbia University M.S. in Data Science Graduates

    Some of the top companies that hire graduates from this program include:

    • Alibaba
    • Amazon
    • Aptly Technology
    • BCG Gamma
    • CIBC
    • Citibank
    • Egan-Jones
    • Ernst & Young
    • General Electric
    • Goldman Sachs
    • Google
    • Hello Fresh
    • Huawei
    • IBM
    • J.P. Morgan
    • LinkedIn
    • McKinsey & Company
    • Meta
    • MetLife
    • Microsoft

    Columbia University's Alumni Info

    Columbia University has a distinguished history of producing influential alumni who have made significant contributions across various fields, including politics, arts, science, and business. Some of the notable alumni names are:

    • Tushar Agarwal
    • Rahul Agarwal
    • Shaurya Malik
    • Tomislav Galjanic
    • Carmem Domingues

    Letter of Recommendation for Columbia University M.S. in Data Science

    A Letter of Recommendation (LOR) is important for your application to the Columbia University MS in Data Science. It’s written by someone who can assess your skills and potential, like a professor or employer.

    Tips for Writing a Strong LOR:

    • Choose the Right Recommenders: Choose professors or employers who know your work well and can speak about your computer science skills.
    • Build Relationships: Engage in class, seek guidance, join research projects, or excel in your job to form strong connections with potential recommenders.
    • Provide Information: Share your resume, transcripts, and statement of purpose to give your recommenders a full picture of your achievements and goals.
    • Communicate Your Goals: Discuss your career aspirations and how the M.S. program will help you, so recommenders can tailor their letters accordingly.
    • Give Enough Time: Request the letters well before the deadline. Provide clear instructions on how and when to submit them.
    • Remind of Achievements: Remind your recommenders of specific projects or accomplishments you want them to highlight.
    • Show Gratitude: Thank your recommenders after receiving the letters. A simple thank-you note can maintain positive relationships.

    Statement of Purpose for Columbia University M.S. in Data Science

    An SOP (Statement of Purpose) is an important essay required for Columbia University's MS in Data Science program. It helps you showcase your academic background, professional goals, and motivation for pursuing a graduate degree.

    Tips for Writing a Strong SOP

    • Research the Program: Learn about the University of Cincinnati's MS in CS program, including its courses, faculty, and research areas. Mention how these align with your goals.
    • Highlight Academic Background: Talk about your academic achievements, relevant coursework, and projects in computer science. Mention any research, internships, or awards.
    • Clarify Your Goals: Explain your career goals and how the MS in CS program will help you achieve them. Be specific about how the program’s resources and opportunities fit your plans.
    • Connect with Faculty and Research: Show interest in specific faculty members and their research. Mention any related research projects you've been involved in.
    • Show Passion and Motivation: Share your enthusiasm for computer science. Include personal experiences or challenges that inspired you to pursue this field.
    • Be Authentic: Be honest about your motivations and goals. Reflect on how your past experiences shaped your interest in computer science.
    • Structure and Clarity: Organize your SOP with a clear introduction, body, and conclusion. Use simple language and proofread to avoid errors.

    Scholarships available for International Students

    The average annual cost of study, including tuition fees and living expenses is around USD$35,000 per year. However, this can rise dramatically as your day-to-day living expenses will vary depending on what state or city you live in.Below are some scholarships you can avail to reduce your study abroad expenses drastically.

    1. The Global Study Awards

      The Global Study Awards is a competition for successful IELTS test takers who have shown exceptional promise. You can enter the competition if you plan to use your IELTS results to apply for an undergraduate or postgraduate degree in an English-speaking country.

    2. Gary Saitowitz Scholarship

      Gary Saitowitz founded the Gary Saitowitz Scholarship with the objective of assisting one deserving student in reducing the stress and also the overall financial burden of costly higher education.

    3. Form Swift Scholarships Program

      The scholarship program is for driven, up-and-coming, entrepreneurs who are ready to commit to building a better world through their business ideas.

    What Columbia University's MS in Data Science values in Applicants?

    Columbia University's M.S. in Data Science program values applicants who have a strong academic background, solid quantitative skills, and a passion for using data to solve real-world problems. The admissions committee looks for candidates who are not just academically prepared but also eager to explore the ethical and practical applications of data science in today's world.

    Below are some key qualities that Columbia University’s M.S. in Data Science program looks for in applicants:

    1. Strong Academic Background: A bachelor's degree in a related field with a minimum GPA of 3.8 is preferred, highlighting academic excellence.
    2. Quantitative Skills: Prior coursework in calculus, linear algebra, and statistics is essential, showing the program's focus on analytical rigor.
    3. Programming Proficiency: Experience with programming languages, particularly Python or R, is highly valued as it is crucial for data analysis and manipulation.
    4. Research Experience: Involvement in research projects or relevant work experience in data science or analytics strengthens an applicant's profile.

    Columbia University M.S. in Data Science Contact Information

    Whom should I contact in case of any doubts?

    Telephone: (212) 854-5660

    Address: Northwest Corner, 550 W 120th St #1401, New York, NY 10027

    Useful Links

    Conclusion: Should you apply to Columbia University M.S. in Data Science?

    In conclusion, applying to the Columbia University MS in Data Science program is a smart choice for anyone serious about a career in data science. The program is one of the best in the world, offering a strong mix of theory and practical experience. With opportunities like industry partnerships, hands-on projects, and a strong alumni network, Columbia provides a great environment to grow your skills and career.

    If you're passionate about data science and ready to take on the challenges of a top-tier program, the Columbia University MS in Data Science could be a key step in your professional journey.

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    Is GRE required for MS DS?

    Your question about the GRE and its necessity for pursuing an MS in Data Science. It's great you're considering this path; Data Science is a fantastic field with lots of opportunities .A lot of universities are focusing more on your experiences and what you can do rather than just your GRE scores.

    Either you can check the Eligibility & requirements : MS in DS in USA

    or here's what you should do: Look up the programs you're interested in and see what their requirements are. If they say the GRE is optional and you're already confident in your application, maybe you can skip it. But if your dream program values the GRE, then prepping for it could be a good move.

    Remember, your application is your chance to shine. Need help navigating? I'm here to guide you every step of the way or you can book free end-to-end session wiht our study abroad consultant.

    I have got 7 bands in my IELTS. I want to do MS in Data Science in USA. How to shortlist universities there according to my score and which provides scholarships as well.?

    Glassdoor has ranked data scientists as one of the top three jobs in the United States for the past six years. It was only in 2020 that it fell to second place after ranking first from 2017 to 2021. The average salary for a Data Scientist is around $113,736. Given these circumstances, the industry is thriving. Many prestigious universities now offer undergraduate and postgraduate degrees in data science. MS in Data Science is a more popular and sought-after programme in the United States than a bachelor's degree. Individuals with related Bachelor's degrees choose MS in Data Science programmes because Data Science is a discipline that combines Statistics, Mathematics, Programming Language, and Computer Science. Here is a list of colleges that you can target:

    Massachusetts Institute of Technology (MIT)
    University of California Berkley 
    The George Washington University – School of Engineering and Applied Science | Data Science Universities in USA
    Harvard University, Cambridge
    Stanford University 
    Yale University
    Columbia University, New York City | Data Science Universities in USA
    University of Pennsylvania 
    University of Michigan, Ann Arbor | Data Science Universities in USA
    Duke University, Durham | Data Science Universities in USA
    If you have any further questions just ask me.

     

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