Eligibility Criteria and Requirement

The University of Bath Data Science offers the program which is perfect for those looking to delve into this dynamic field. But first, let's talk about what it takes to get there.





Eligibility Criteria
Requirements


Academic Qualification
First or strong second-class Bachelor’s honours degree or international equivalent.


Undergraduate Degree
Computer science with a strong mathematical focus


Experience
If you have experience in programming, it can be considered  advantageous


Lower Grade Consideration
May consider an offer based on a lower grade if evidence of suitability for the degree is provided


English Language Requirement (if applicable)
You may be accepted from our language requirements if your first language isn't English but within the last 2 years you completed your degree in the UK. 


No lower GPA

Bachelor's GPA Requirement

Related Discipline degree

UG Requirement

Test Scores Requirement

ExamRequirement
6.5
90
62

Program Eligibility URL:https://www.bath.ac.uk/courses/postgraduate-2024/taught-postgraduate-courses/msc-data-science/#application-information

University of Bath MSc in Data Science Rankings

University Ranking- THE (Times Higher Education) 2021

201-250

World University Ranking- QS 2021

100

About University of Bath

The University of Bath's MSc Data Science program aims to enhance employability in data science roles by imparting specialist knowledge in machine learning, statistics, and software technology. This one-year program, starting in September 2024, emphasizes a strong mathematical foundation and computational skills, essential for becoming an industry expert. It offers project work that spans various subjects, aiming to prepare graduates for careers in commercial enterprises to tech startups.


The course includes compulsory units in applied data science, statistics, machine learning, and software technologies, with options for further specialization. For more details, visit the official course page​

University of Bath MSc in Data Science Program Description

University of Bath Data Science plays a big role in the world economy, touching areas like healthcare, finance, and technology. It's also making a difference in scientific advancements in fields such as bioscience, energy, and telecommunications. This course equips you with the computer skills and tools, along with a solid math foundation, to become a pro in the industry. You'll learn how to effectively use a mix of science and technology for successful data science.


You'll learn strong statistical foundations of universal relevance and develop specialist knowledge of probabilistic machine learning techniques. You will gain expertise in the software technologies that are central to putting this knowledge into practice, addressing the challenges of small and large data sets.



You'll learn from a dedicated team of computer scientists who have a wealth of experience from their professional backgrounds.


After graduation you'll be well placed to progress into a wide variety of careers in data science, from large-scale established commercial enterprises to innovative technology start-ups. You will also have acquired the essential foundation for further postgraduate study and research within related fields.


Assessment



  • Coursework

  • Dissertation

  • Essay

  • Multiple choice examination

  • Online assessment

  • Oral assessment

  • Practical work

  • Thesis

  • Written examination

  • Other

    • Program URL:https://www.bath.ac.uk/courses/postgraduate-2024/taught-postgraduate-courses/msc-data-science/

    Curriculum Overview: University of Bath MSc in Data Science

    Program Curriculum URL:https://www.bath.ac.uk/courses/postgraduate-2024/taught-postgraduate-courses/msc-data-science/#course-structure

    Courses include:


    Semester 1


  • Applied data science

  • Statistics for data science

  • Machine learning 1

  • Software technologies for data science


    • Semester 2


  • Applied data science

  • Machine learning 2

  • Research project preparation

  • Plus optional units


  • Bayesian machine learning

  • Reinforcement learning



    • Core Courses

    Courses include:

    Semester 1
    • Applied data science
    • Statistics for data science
    • Machine learning 1
    • Software technologies for data science
    Semester 2
    • Applied data science
    • Machine learning 2
    • Research project preparation
    • Plus optional units
      • Bayesian machine learning
      • Reinforcement learning
    • Data Science & Big Data
    • Software Engineering
    • Machine Learning

    University of Bath Data Science students can discover lots of sports club, society, volunteering group or support group. These are all run by students, for students:

    • Bath Entrepreneurs: Bath Entrepreneurs (BE) is a student group welcoming and uniting all student entrepreneurs at Bath. We provide great networking, learning, and funding opportunities.
    • Bath Computer Science Society: We’re a social society for anyone with an interest in computers or technology! Whatever you’re studying, from Management to Mechanical Engineering, from Criminology to Computer Science, joining BCSS is a great opportunity to make friends and have fun!
    • Coffee Soc: The Coffee Society exists to introduce our members to the beautiful world of quality coffee. We aim to show our members the huge variety of different production and brewing methods for making coffee, with workshops and tastings to experience first hand the differences these make to the final cup.

    You can take part in different extracurricular a activities such as -

    1. Sports

    Students can participate in 10 performance sports, including athletics, badminton, football, hockey, judo, netball, rugby, swimming, tennis, and triathlon. Students also have access to a full-time coach and sport science support. The university also has a Sports Training Village (STV) that's open to the public and includes a gym, swimming pool, athletics track, and courts.

    2. Arts and creative societies

    Students can join arts societies like Backstage Technical Services, Bath University Student Theatre, and the Chamber Choir.

    3. Clubs and societies

    Students can join clubs and societies like Latin and Ballroom, Triathlon, and Archery.

    4. Groups

    Students can join groups like the African and Caribbean Society, American Football, and Amnesty.

    Program Fee & related expenses

    University of Bath MSc in Data Science Fee Structure


    The fee structure including all the expenses at their estimated cost for the University of Bath Data Science program is as follows:





    Expenses
    Estimated Cost(GBP)


    Tuition Fee
    £31,600


    Accommodation during Off-campus Visits
    £400 - £600


    Placement Costs (if applicable)
    £350 - £450


    Non-refundable Deposit
    £1,000


    Application Documents required

    Mandatory Application Documents

    • Passport

    • Graduation/Provisional Certificate

    • IELTS/TOEFL/DTE/PTE

      Program Application URL:https://www.bath.ac.uk/services/application-tracker-for-postgraduate-taught-courses/

      MSc in Data Science Deadlines

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      Employment, Salary & Career Statistics

      The MS in Data Science at the University of Bath offers comprehensive training in cutting-edge data analysis techniques, preparing graduates for lucrative careers in industries such as finance, healthcare, and technology. With a focus on practical skills and real-world applications, students gain hands-on experience to excel in the rapidly evolving field of data science.

      43,921

      Average Starting Salary

      Companies Recruiting University of Bath MSc in Data Science Graduates

      Top recruiters for MS in data science -



    • Amazon

    • Accenture

    • BAE Systems

    • EY

    • GlaxoSmithKline

    • IBM

    • JP Morgan

    • Microsoft

    • Morgan Stanley

      • Employment Overview URL: https://www.bath.ac.uk/campaigns/improve-your-employability-with-a-science-placement/

      University of Bath's Alumni Info

      Some notable alumni’s from the field of University of Bath Data Science are:



    • Dr. Raymond F. Schinazi: Scientist in HIV and hepatitis B research

    • Ash Atalla: TV Producer responsible for The Office, The IT Crowd, and Man Stroke Woman

    • Mark Hawkins: Former Chief Executive and Managing Director of The Moment

    • Nick Hynes: President and co-founder of Somo Global and Chairman of Reward

    • Air Chief Marshal Sir Stephen Dalton GCB: Former Chief of the Air Staff, Royal Air Force


      •  

      Letter of Recommendation for University of Bath MSc in Data Science

      A Letter of Recommendation (LOR) is a document written by someone who can provide insight into your academic or professional qualifications, character, and potential for success in a specific program. For admission into the University of Bath, LORs are important as they offer a third-party perspective on your abilities, helping the admissions committee assess your suitability for the chosen program.


      Here are the tips for obtaining the best Letter of Recommendation:


      1. Choose the Right Recommender:


      Select individuals who know you well and can speak to your academic abilities, work ethic, and character. Ideally, choose professors, employers, or supervisors who have had direct experience with your skills.


      2. Provide Guidance:


      When requesting a recommendation, provide clear guidelines about the program you are applying to, your career goals, and any specific points you'd like them to address in the letter.


      3. Give Ample Time:


      Request recommendations well in advance, providing recommenders with enough time to thoughtfully craft the letter. A rushed recommendation may not reflect your true strengths.


      4. Share Relevant Information:


      Share your academic and professional achievements, goals, and specific experiences you'd like the recommender to highlight. This information can help them tailor the letter to your application.


      5. Provide a Resume:


      Share your updated resume with the recommender, giving them additional context about your experiences, skills, and qualifications.


      6. Follow Up Politely:


      If your recommender agrees to write the letter, follow up politely as the deadline approaches to ensure they have the necessary details and are on track.


      7. Express Gratitude:


      Thank your recommenders for their time and effort. Let them know that you appreciate their support in helping you achieve your academic and career goals.


      8. Diversity in Recommenders:


      If possible, include recommendations from different sources, such as a professor, employer, or mentor. This can provide a more comprehensive view of your capabilities.


      9. Choose Quality over Quantity:


      It's better to have a few well-written, substantive letters than a larger number of generic ones. Quality recommendations can make a stronger impact on the admissions committee.


      10. Provide Clear Submission Instructions:


      Clearly communicate the submission process to your recommenders, including any online portals or specific email addresses.

      0

      Statement of Purpose for University of Bath MSc in Data Science

      A Statement of Purpose (SOP) is a crucial component of your application for admission into a university. It is a written document that allows you to express your academic and professional background, career goals, and reasons for pursuing a particular program. For the University of Bath Data Science, the SOP holds significance as it provides the admissions committee with insights into your motivations, qualifications, and suitability for the program.


      Here are some tips for writing a successful SOP:




      • Introduction with Purpose:


      Begin with a concise and impactful introduction, clearly stating your purpose for applying to the MSc in Data Science program at the University of Bath.

      • Academic Background:


      Discuss your academic journey, emphasizing relevant coursework, projects, or research that prepared you for advanced studies in data science.

      • Professional Experience:


      If applicable, highlight your professional experience, detailing how it aligns with your academic goals and contributes to your suitability for the program.

      • Research the Program:


      Demonstrate your knowledge of the University of Bath's MSc in Data Science. Specify how the program's features, faculty, and resources align with your career aspirations.

      • Career Goals:


      Clearly articulate your short-term and long-term career goals related to data science. Explain how the MSc program at the University of Bath will help you achieve these goals.

      • Connection to the University:


      Explain why you specifically chose the University of Bath for your MSc in Data Science. Mention faculty members, research centers, or unique aspects of the program that attract you.

      • Unique Contributions:


      Discuss how your unique skills, experiences, or perspectives will contribute to the diversity and vibrancy of the university community.

      • Language and Style:


      Write in a clear, concise, and engaging manner. Avoid unnecessary jargon and use simple language as per your preference.

      • Proofread and Revise:


      Thoroughly proofread your SOP to eliminate errors. Consider seeking feedback from professors, colleagues, or mentors to ensure clarity and coherence.

      • Honesty and Authenticity:


      Be genuine and honest in portraying your motivations and aspirations. Avoid exaggeration or providing information that may not be accurate.

      Scholarships for International Students

      The available scholarships for international students for the University of Bath MSc in Data Science include -



    • Data Science Scholarship

    • Global Leaders Scholarship

    • Commonwealth Scholarships

    • Vice Chancellor’s International Scholarships

      • What makes University of Bath MSc in Data Science unique?

      Course highlights



    • Work with a dedicated team of computer scientists who have a wealth of experience from their professional backgrounds.

    • Learn to understand and develop state-of-the-art machine learning techniques.

    • Gain expertise in when to apply the best technique for the best results, in small and large data sets.

    • Be part of our supportive postgraduate community.

    • Live and study in a beautiful world heritage city.


      • Project examples


      The research expertise in the department allows for a wide-range of subjects for your final project. Recent examples from University of Bath in Data Science students include:



    • Deep learning in high frequency financial trading.

    • Spatiotemporal timing predictions in areas with a low density of public transport.

    • The impact of mindfulness meditation on multisensory transfer learning.


      • Career prospects


      After graduating, you'll be well placed for a variety of careers in University of Bath data science - from large-scale commercial enterprises, to innovative tech start-ups. Alongside the specialist skills and knowledge you'll gain, our dedicated careers team offers individual guidance and help you decide between employment and further study.


      Recent graduate roles include: data scientist, machine learning developer, Python developer and software engineer.

      University of Bath Contact Information

      Whom should I contact in case of any doubts?

      Telephone number: +44(0)1225 385115


      E-mail: pgtadmissions@bath.ac.uk


      Address: University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom

      Useful Links

      University of Bath Ms in Data science

      Photos & Videos of University of Bath MSc in Data Science

      University of Bath DS
      university of bath

      Conclusion: Should you apply to University of Bath MSc in Data Science?

      In conclusion, considering the University of Bath Data Science presents a promising opportunity. The university's strong academic reputation, coupled with a range of international scholarships, underscores its commitment to fostering excellence in education.


      The program benefits from knowledgeable faculty members and modern facilities, providing a conducive learning environment. However, prospective applicants should carefully evaluate their personal preferences, ensuring the location aligns with their lifestyle and consider the specific admission criteria. Overall, the decision to apply should be guided by a thorough understanding of the program, the university's strengths, and how well they align with one's academic and career objectives.

      ‌

      Ask a Question

      Have Queries about University of Bath?

      Get Answers from Alums

      Is Master's in Data Science a good career option in Australia?Among the courses Data Science, Data Analytics and Business Analytics comparatively which is the best option for a B. TECH student?

      Australia is home to some of the greatest universities in the world for studying Data Science and Business Analytics. As a result, Australian universities have become a popular alternative among overseas students seeking a Master's degree in Data Science. These universities also give you the option of studying part-time or full-time. Aside from that, data scientists are in high demand in Australia. A data scientist's annual income in Australia is now AU $95000, but this figure could rise dramatically based on experience. After earning a master's degree in data science, job chances in Australia are great, with salaries of up to $200,000 per year. Data Scientist, Data Analyst, Data Engineer, BI Developer, Data Manager, and other job titles are available. Among the courses, Data Science, Data Analytics and Business Analytics comparatively, data science is the best option because of its usefulness in all disciplines of science, technology, and business is the best option for a B. TECH student. If you have any further questions just ask me.

      Best 5 colleges in UK for MS data science or data analytics?

      Data Science is a rapidly growing field that has achieved vital importance in today's data-driven world. It has become a requirement for businesses to keep a close eye on the data churned out of their respective fields to grow their businesses. This, in turn, has increased the need for data scientists worldwide. Owing to its popularity, several universities in the UK have started teaching the subject. Some of the best universities for Data Science in the UK cater to students' demands by providing them with various comprehensive courses.


       



      1. Best Universities for Data Science

      2. University of Oxford

      3. King's College London

      4. University of Manchester

      5. University of Bristol


        6. Eligibility Criteria


        A minimum of a 2.1 honors degree (60-70% score) with computer science as a major subject
        IELTS score: Between 6.5-7.0 overall with no less than 6.0-6.5 in all components.


        Documents Required for the Admission Process. 



        • Academic transcripts as proof of your academic achievements

        • Explanation of English Proficiency scores

        • Proof of funds as evidence to pay for the tuition fees and monthly living costs for the first year

        • Resume

        • Two academic reference letters

        • SAT scores

        • ACT scores

        • Statement of Purpose (SOP) for studying in the UK.

          • What are the career options for Data Science and Data Analytics differences?
          Well, they are not much different except that data analytics is a part of data science. You can consider them separate based on how significant data analytics is but the jobs and responsibilities all fall under data science. See, it is like a branch of the subject. Just like Mechanical and the Engineering itself.


          I think you would be more satisfied with knowing the basic difference between these two. Maybe you will find something you are looking for this way. So data science is basically finding meaningful correlations between large datasets. Here, it doesn't have to be any specific kind of result or relation. Like even if you find unwanted statistics from a database, it still falls under data science.


          On the other hand, data analytics is used to find specific information. For example, the goal can be finding correlations between different data or maybe just the average values. It basically means that you need data analytics to carry out set tasks and roles. It's a branch of data science that is focused on specific answers to data science questions.



          This must have given you an idea of how their career options differentiate. For example, a data scientist can work as a data analyst, and they will have a wider industry to play with. Whereas for a data analyst, the job roles are more specific. Like you will have directional areas to work with. Let me explain it in a different way. The main points you need to see for a data analyst career are:



          higher average salaries.
          fast-growing industry with skilled workers.
          nice career advancement options


          These are your career options as a data analyst. For data science, you will be free to join more sectors and work in different job roles. Any task and operation related to data fall under data scone. In a data science MS degree, your main concern will be your elective in your final year. They will decide which job you are going to join after graduation. For specifics, these are the points you need to know for a data science career:



          wider subjects to cover like Python, SQL, database etc.
          connected with many other sectors.
          one of the top subjects and professions in undeveloped countries.


          I hope this clears some of your doubts. The jobs in both areas can be the same given the job title. Data experts are very high in demand nowadays and the jobs in these fields are paid handsomely. If you are interested in any branch of data science, I suggest you start building a profile right now. Because most international students are targeting data science courses in universities abroad. Better to be safe than sorry.



          What is the meaning of data science and how is it different from data analytics?

          There are a lot of things that are often considered as same when they are not, such as MiM and MBA, Stock Market and gambling and many more. One of those things is data science and data analytics. Many students still consider these as the same thing and often say that they are going to become a data analyst when they are actually pursuing a data scientist course. 


          In order for you to not do these kinds of blunders, I have mentioned some key differences between a data analyst and a data scientist. So let’s get started with them: 


          In data science, you apply various algorithms, processes., and scientific methods from structured and unstructured data to derive meaningful insights from them. But in data analytics, you process raw data to arrive at the conclusions. 
          Data science is a much more broad scope with many branches and fields. Data analytics has a much narrower scope and is a subset of data analytics. 
          The knowledge and skills needed in data science are much more in-depth than in data analytics.
          Machine learning is used in data science and sometimes it is an essential part of various data science tasks. But data analytics has no relation to machine learning. 
          Some major fields where data science is used are Machine learning, AI, search engine engineering, and corporate analytics. Healthcare, gaming, and travel are some major fields where data analytics is used. 
          So, these were some major differences between data science and data analytics, there are others as well but for the time being, these are sufficient. But no matter what differences are there between the two fields, both data science and data analytics are two sides of the same coin. 


          Would you like to tell me how many of these were you already aware of and how many were new to you?


           


           

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