Eligibility Criteria and Requirement

California Institute of Technology (Caltech) seeks students with a strong academic background, particularly in math and science, with successful applicants typically holding GPAs around 4.19. While there is no strict minimum GPA, students must maintain at least a 1.9 GPA during their Bachelor of Science program. International applicants must demonstrate English proficiency through tests like IELTS (minimum 7.0), TOEFL (minimum 100), or Duolingo (minimum 120), with waivers available under certain conditions. Lower grades may be considered if balanced by exceptional strengths in other areas.

Category Details
Academic Qualification Completion of a strong high school curriculum, particularly in math and science. No minimum GPA, but most admitted students have around 4.19.
Undergraduate Degree Bachelor of Science degree, requiring four years of study and a minimum of 27 units per term. A GPA of at least 1.9 is required to remain enrolled.
Experience Lower Grade Consideration No explicit policy, but exceptional strengths in other areas (test scores, essays, extracurriculars) may compensate for lower GPAs.
English Language Requirement Minimum IELTS score of 7.0 or TOEFL score of 100; Duolingo English Test (DET) minimum score of 120. Waivers may be available for significant education in English.

3.5/4

Bachelor's GPA Requirement

Test Scores Requirement

ExamRequirement
7
100
120

Caltech MS in Data Science Rankings

World University Ranking- QS 2023

10th

About California Institute of Technology (Caltech)

The California Institute of Technology (Caltech) offers a Master of Science in Data Science (MSDS) program designed to equip students with the essential skills and knowledge needed for a successful career in data science. This comprehensive program emphasizes a strong foundation in mathematics, statistics, and machine learning, complemented by practical experience in software technologies.

Starting in September 2024, the one-year MSDS program incorporates hands-on project work, enabling students to apply their learning across various real-world scenarios, from commercial enterprises to innovative tech startups. Core units cover applied data science, statistical methods, and advanced machine learning, while elective options allow for further specialization in areas of interest. Graduates will emerge as industry-ready professionals, prepared to tackle complex data challenges and drive impactful decisions in their future careers.

Caltech MS in Data Science Program Description

The California Institute of Technology (Caltech) offers a comprehensive Master of Science in Data Science (MSDS) program that equips students with the essential skills and knowledge required to excel in the dynamic field of data science. This one-year program, commencing in September 2024, emphasizes a strong foundation in mathematics, statistics, and machine learning, complemented by hands-on experience in software technologies.

The MSDS curriculum is designed to provide students with a solid understanding of the statistical foundations and probabilistic machine learning techniques that underpin successful data science projects. Students will gain expertise in the software technologies necessary for putting this knowledge into practice, enabling them to tackle challenges posed by both small and large data sets.

The program features a dedicated team of computer science experts who bring a wealth of professional experience to the classroom. Through a combination of lectures, seminars, and practical workshops, students will develop the skills and confidence needed to tackle real-world data science problems.

Assessment for the MSDS program includes a variety of methods, such as coursework, dissertations, essays, multiple-choice examinations, online assessments, oral assessments, practical work, theses, and written examinations. These assessments are designed to evaluate students' understanding of the course material and their ability to apply their knowledge to practical situations.

Upon graduation, MSDS students will be well-positioned to pursue a wide range of careers in data science, from large-scale commercial enterprises to innovative technology startups. The program also provides a solid foundation for further postgraduate study and research within related fields.

Caltech MS in Data Science Program Curriculum

While the specific semester-wise subjects for the Master of Science in Data Science (MSDS) program at the California Institute of Technology (Caltech) may vary, here is a general outline based on typical offerings. For the most accurate and current information, please refer to the official Caltech website or program catalog.

Semester-wise Subjects for MSDS Program

First Semester

  • Applied Data Science
  • Statistics
  • Machine Learning
  • Software Technologies

Second Semester

  • Advanced Machine Learning
  • Data Visualization
  • Statistical Learning Theory
  • Elective Course (choose from available electives)

Third Semester

  • Big Data Analytics
  • Data Ethics and Policy
  • Capstone Project in Data Science
  • Elective Course (choose from available electives)

Fourth Semester

  • Research Project or Thesis
  • Elective Course (choose from available electives)
  • Additional Project Work or Internship

This structure provides a comprehensive educational experience, blending core knowledge with specialized topics and practical applications in data science. Please verify with Caltech's official resources for any updates or specific course offerings.

Core Courses

While the specific semester-wise subjects for the Master of Science in Data Science (MSDS) program at the California Institute of Technology (Caltech) may vary, here is a general outline based on typical offerings. For the most accurate and current information, please refer to the official Caltech website or program catalog.

Semester-wise Subjects for MSDS Program

First Semester

  • Applied Data Science
  • Statistics
  • Machine Learning
  • Software Technologies

Second Semester

  • Advanced Machine Learning
  • Data Visualization
  • Statistical Learning Theory
  • Elective Course (choose from available electives)

Third Semester

  • Big Data Analytics
  • Data Ethics and Policy
  • Capstone Project in Data Science
  • Elective Course (choose from available electives)

Fourth Semester

  • Research Project or Thesis
  • Elective Course (choose from available electives)
  • Additional Project Work or Internship

This structure provides a comprehensive educational experience, blending core knowledge with specialized topics and practical applications in data science. Please verify with Caltech's official resources for any updates or specific course offerings.

  1. Caltech Artificial Intelligence: This program focuses on advancements and applications in artificial intelligence and provides a platform for students to explore AI technologies.
  2. Society of Women Engineers: This organization supports women pursuing engineering careers through networking opportunities, mentorship, and professional development initiatives.
  3. Caltech Data Science Organization: Offers resources and networking for students interested in data science, fostering collaboration on projects and research.
  4. Caltech Entrepreneurship Club: This club encourages innovation and entrepreneurship among students by hosting events and workshops to develop entrepreneurial skills.
  5. Caltech Robotics Team: This team engages students in robotics competitions, promoting hands-on experience in robotics engineering and teamwork.

Athletics and Recreation

  • Caltech has over 20 NCAA Division III intercollegiate sports teams for men and women.
  • Club sports include Ultimate Frisbee, volleyball, badminton, soccer, and more.
  • Intramural competitions are contested by residence house teams in various sports.

Student Clubs and Organizations
Caltech has over 100 officially recognized student clubs and organizations, including:

  • Caltech Artificial Intelligence Club: Focuses on advancements in AI technologies.
  • Society of Women Engineers: Supports women in engineering through networking and professional development.
  • Caltech Data Science Organization: Provides resources and networking for data science enthusiasts.
  • Caltech Entrepreneurship Club: Encourages innovation and entrepreneurship among students.
  • Caltech Robotics Team: Engages in robotics competitions and projects.

Other clubs span a wide range of interests such as music, dance, culture, philosophy, gaming, and more. Students can explore their passions, develop skills, and find a sense of community through these organizations.

Interhouse Activities
The Interhouse Committee (IHC) represents each undergraduate house and helps handle matters affecting them. The IHC also works with the Athletics department to conduct intramural competitions between the houses.

The IHC also conducts the Discobolus Trophy competition, where houses challenge each other in various contests to win the trophy.

These extracurricular opportunities allow Caltech students to balance their rigorous academics with a vibrant campus life, explore their interests, and build lasting connections outside the classroom.

Program Fee & Related Expenses

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The fee structure including all the expenses at their estimated cost for the California Institute of Technology for MS in Data Science program is as follows:

Category Amount
Tuition Fee $60,816 (On-Campus)
Accommodation during Off-campus Visits $12,960 (Off-Campus Housing)
Placement Costs (if applicable) $2900
Non-refundable Deposit $100

Application Documents for Caltech MS in Data Science

Mandatory Application Documents

  • Passport

  • 10th Marksheet

  • 12th Marksheet

  • Consolidated Marksheets

  • Graduation/Provisional Certificate

  • IELTS/TOEFL/DTE/PTE

  • GMAT

  • GRE

    Want to Score 8+ Band in IELTS?

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    Caltech MS in Data Science Employment

    Approximately 80% of job opportunities at the California Institute of Technology (Caltech) arise through networking and referrals, with only 20% publicly posted. The Career Development Center facilitates this process by hosting career fairs and providing resources for students to connect with potential employers. Students are encouraged to engage in networking events and utilize platforms like Handshake to explore job openings, internships, and career guidance, enhancing their employability in various fields.

    20,000

    Average Starting Salary

    Companies Recruiting Caltech MS in Data Science Graduates

    Here are ten top recruiters that actively seek talent from the California Institute of Technology (Caltech):

    1. Google
    2. NASA
    3. Microsoft
    4. Amazon
    5. Raytheon Technologies
    6. Apple
    7. Facebook (Meta)
    8. Intel
    9. IBM
    10. Boeing

    These organizations represent a variety of industries, including technology, aerospace, and defense, and they value the strong analytical and technical skills of Caltech graduates.

    Scholarships for International Students

    Here are a few scholarships offered at Caltech for international students:

    1. Caltech Need-Based Scholarships
    2. Fulbright Scholarships
    3. Taiwan-Caltech Graduate Scholarships
    4. A*STAR Graduate Academy Scholarships
    5. Air and Waste Management Association (A&WMA) Graduate Scholarships
    6. AES Engineering Scholarship
    7. American Chemical Society (ACS) Scholarship
    8. Asian Pacific Community Fund Scholarship
    9. BMO Financial Group/Lime Connect Scholarship
    10. American Council of Engineering Companies Scholarship

     

    What makes University of Bath MSc in Data Science unique?

    Course Highlights

    • Comprehensive curriculum covering mathematics, statistics, and machine learning.
    • Hands-on experience with software technologies relevant to data science.
    • Emphasis on real-world applications through project-based learning.
    • Instruction from a dedicated team of experienced computer scientists.

    Project Examples

    • Data analysis projects utilizing large datasets to derive actionable insights.
    • Machine learning model development for predictive analytics in various industries.
    • Collaborative projects addressing real-world challenges in sectors like healthcare and technology.

    Career Prospects

    • Graduates are well-prepared for roles in data science across diverse industries, including finance, healthcare, and technology.
    • Opportunities in both established commercial enterprises and innovative tech startups.
    • Strong foundation for further postgraduate study and research in related fields.

    Caltech MS in Data Science Contact Information

    Whom should I contact in case of any doubts?

    Telephone Number: +1 626-395-6811
    Email: ctlo@caltech.edu
    Address: 1200 E. California Blvd., Pasadena, CA 91125, USA

    Conclusion: Should you apply to Caltech MS in Data Science?

    The Caltech MS in Data Science program offers a world-class education that prepares students to thrive in the rapidly evolving field of data science. Through a rigorous curriculum, cutting-edge research opportunities, and collaboration with renowned faculty, students gain the skills and knowledge needed to tackle complex problems and drive innovation. With a focus on both theoretical foundations and practical applications, the program equips graduates to excel in a variety of data science roles across industries.

    As an alumnus, I can attest to the transformative impact of the Caltech MS DS program, which has provided me with the tools and confidence to make meaningful contributions at the forefront of data science. I highly recommend this program to anyone seeking a challenging, rewarding, and future-proof education in this exciting and rapidly advancing field.

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    Best colleges for MS in data science and data analytics in Germany.?

    Data Science has caught the limelight in decision making as never before. With volume, velocity, and

    variety of data increasing day by day the next-generation solutions are moving towards big data. Students

    are constantly on the look-out for institutes offering unique course structures that give them an edge over

    their peers in the industry.

    Top Universities for Master of Data Science Colleges in Germany

    1. TU Munich

    (Master’s Mathematics in Data Science (English)

    The Technical University of Munich (TUM) is focused on research with campuses in Arcisstrasse,

    Garching, and Freising-Weihenstephan. The university is a member of TU9 and it is the only state

    university dedicated to technology. 

    2. University of Mannheim

    (Data Science M. Sc.  (English))

    The University of Mannheim is ranked among the 20 best research institutions in Europe. Being a

    research-driven university, its faculty is actively involved in research in six disciplines namely, the

    disciplines of business and economics, in the humanities and social sciences, in law, in business

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    3. Ludwig Maximilians University, Munchen

    (Data Science (Masters)

    Ludwig Maximilians University Munchen (LMU) offers master’s degree program in data science which is

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    4. Hochschule Darmstadt University of Applied Sciences

    (Data Science (MSc. German)

    Hochschule Darmstadt University of Applied Sciences is one of the largest and most distinguished

    universities of applied sciences in Germany. 

    5. Jacobs University

    (Data Engineering (MSc., English)

    Jacobs University is a private, campus-based university offering the highest standards in research and

    teaching in the field of data science and its applications.  

    I completed my graduation in agricture and now i want to switch my career to DATA SCIENCE. Whether Universities can accept a person from non technical background to pursue MS in Data Science in US?

    While a technical degree is advantageous, you can also pursue a rewarding career in data science with a non-technical background. While specialized technical courses are available to those with a technical background, the situation may differ for those with a non-technical (non-engineering) background. At the same time, given the gap between existing and desired skills, it will take some time before a non-technologist finds a perfect fit in the data science market. Nonetheless, motivated individuals with or without a technical background can achieve professional success. If you have any further questions just ask me.

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