collageIf you have been looking for reviews on Cardiff University Data Science, look no further as we shall discuss Cardiff University Data Science Review, cardiff university data science ranking, msc data science and analytics, data science and analytics courses and is cardiff a good place to study.
Cardiff University offers a wide range of courses including business, law, medicine and dentistry among others. There are also many courses that are specifically designed for international students such as those who want to study abroad or those who want to learn conversational English language skills. Read on to learn more about Cardiff University Data Science, look no further as we shall discuss Cardiff University Data Science Review, cardiff university data science ranking, msc data science and analytics, data science and analytics courses and is cardiff a good place to study.
The University of Cardiff is a public research university in Wales’ capital city of Cardiff. It is the third oldest university in Wales, having been founded by Royal Charter in 1883 as the University College of South Wales and Monmouthshire, Wales’ first civic university. The institution was renamed in 2005 to the University of South Wales; it gained its current name in 2013 when it became independent from the University of Wales network. The university’s main campus is located in Cathays Park near the centre of Cardiff; a secondary campus is located two miles away at Cyncoed. It offers degrees across all academic disciplines from bachelor degrees to doctoral degrees, postgraduate diplomas and certificates. There are two faculties: Arts and Humanities (including Social Sciences) and Science & Engineering (including Computer Science). The university also has a number of other campuses including Cardiff School of Creative & Cultural Industries (SCCI).
The course aims to introduce learners to cutting edge techniques such as machine learning algorithms (such as Support Vector Machines), data mining methods (such as Association Rule Mining) and statistical analysis tools (such as R). It also aims to provide students with knowledge about how these techniques can be used together in order to solve complex real-world problems such as fraud detection or classification of diseases based on medical records provided by patients etc.
Cardiff University Data Science Review
We begin with Cardiff University Data Science Review, cardiff university data science ranking, msc data science and analytics, data science and analytics courses and is cardiff a good place to study.
Why study this course
Acquire a range of in-demand skills for extracting and handling ‘big data’ and develop your practical skills through exposure to real-world problems and datasets.
Learn from our network of experts
We have a cross-disciplinary network of experts across the School of Mathematics, the School of Computer Science and Informatics andd other University research groups.
Industry experience
Gain valuable work experience on professional work placements and projects with leading data science practitioners in the UK and abroad.
Solve real-world problems
This course incorporates project-based learning using real-world datasets and problems.
New teaching facilities
Some of your modules will be taught in our newly-renovated Turing Suite.
Laptop provided
You will be provided with a laptop during induction week that will remain with you throughout the duration of the course.
This course will equip students with a theoretical understanding and practical experience of applying methods drawn from data science and analytics. You will develop a range of in-demand skills for extracting and handling ‘big data’ and applying modelling tools to help businesses and government organisations make better decisions.
On completion of the course, you will be well placed to progress into a variety of roles in data-intensive industries or a related research career.
This one-year degree falls under the umbrella of the Data Science Academy (DSA), run by the School of Computer Science and Informatics, in partnership with the School of Mathematics. You will benefit from the shared knowledge and skills of both Schools. However, your degree will still be run by the School of Mathematics.
Where you’ll study
School of Computer Science and Informatics
Our degree programmes are shaped by multidisciplinary research, making them relevant to today’s employers and well placed to take advantage of tomorrow’s developments.
- Research facilities
- Research at the School of Computer Science and Informatics
- Academic and research staff
- Get in touch
- +44 (0)29 2087 4812
- Senghennydd Road, Cathays, Cardiff, CF24 4AG
Admissions criteria
Academic requirements:
Typically, you will need to have either:
- a 2:2 honours degree in a relevant subject area such as engineering, mathematics or science, or an equivalent international degree
- a university-recognised equivalent academic qualification
English Language requirements:
IELTS with an overall score of 6.5 with 6.0 in all subskills, or an accepted equivalent.
Application deadline:
We allocate places on a first-come, first-served basis, so we recommend you apply as early as possible.
Selection process:
We will review your application and if you meet the entry requirements, we will make you an offer.
Applicants who require a Student visa to study in the UK must present an acceptable English language qualification in order to meet UKVI (UK Visas and Immigration) requirements.
Criminal convictions
You are not required to complete a DBS (Disclosure Barring Service) check or provide a Certificate of Good Conduct to study this course.
If you are currently subject to any licence condition or monitoring restriction that could affect your ability to successfully complete your studies, you will be required to disclose your criminal record. Conditions include, but are not limited to:
- access to computers or devices that can store images
- use of internet and communication tools/devices
- curfews
- freedom of movement, including the ability to travel to outside of the UK or to undertake a placement/studies outside of Cardiff University
- contact with people related to Cardiff University.
Course structure
This is a two-stage programme taught over one year for a total of 180 credits. The taught stage is 120 credits, followed by a 60-credit research project.
The modules shown are an example of the typical curriculum and will be reviewed prior to the 2022/23 academic year. The final modules will be published by September 2022.
You will undertake all 20-credit compulsory modules (100 credits in total) and choose a further 20 credits from a list of carefully selected optional modules. The 60-credit project undertaken in the summer will typically involve working with a company on a problem of real importance.
| Module title | Module code | Credits |
|---|---|---|
| Data Visualisation | CMT218 | 20 credits |
| Applied Machine Learning | CMT307 | 20 credits |
| Computational Data Science | CMT309 | 20 credits |
| Foundations of Operational Research and Analytics | MAT021 | 20 credits |
| Foundations of Statistics and Data Science | MAT022 | 20 credits |
| Dissertation | MAT099 | 60 credits |
The University is committed to providing a wide range of module options where possible, but please be aware that whilst every effort is made to offer choice this may be limited in certain circumstances. This is due to the fact that some modules have limited numbers of places available, which are allocated on a first-come, first-served basis, while others have minimum student numbers required before they will run, to ensure that an appropriate quality of education can be delivered; some modules require students to have already taken particular subjects, and others are core or required on the programme you are taking. Modules may also be limited due to timetable clashes, and although the University works to minimise disruption to choice, we advise you to seek advice from the relevant School on the module choices available.
Learning and assessment
How will I be taught?
The methods of teaching we employ will vary from module to module, as appropriate depending on the subject matter and the method of assessment. We teach using a mixture of lectures, seminars, computer workshops and tutorials.
Programming skills and the use of relevant software packages will be taught in our dedicated computer suites. We often invite industry experts to give presentations, which our students are welcome to attend.
We will allocate three supervisors to you for your dissertation project. Usually your supervisors will be two members of academic staff with an interest or specialism in your field of research and a sponsor supervisor from the organisation you will work with during your project. You should meet regularly with your supervisor throughout your project.
How will I be assessed?
We will assess your progress throughout the course. These assessments may take the form of written exam papers, in-module assignments, and the project dissertation, where knowledge and technical competence will be appraised. We may also use group work, oral presentations and poster displays to test communication, critical thinking and problem-solving skills.
How will I be supported?
All of our students are allocated a personal tutor within both the School of Mathematics, and the School of Computer Science and Informatics when they enrol on the course. A personal tutor is there to support you during your studies, and can advise you on academic and personal matters that may be affecting you.
You will have access to the Trevithick Library, which holds our collection of mathematical and computer science-related resources, as well as to the other Cardiff University Libraries.
What skills will I practise and develop?
Knowledge & Understanding:
On successful completion of the Programme you will be able to demonstrate:
- A systematic understanding of knowledge, and a critical awareness of current problems and/or new insights, much of which is at, or informed by, the forefront of our academic discipline.
Intellectual Skills:
On successful completion of the Programme you will be able to demonstrate:
- The ability to identify appropriate methods for the solution of problems in Data Science and Analytics.
- Initiative and personal responsibility in decision-making in complex and unpredictable situations.
- Systematic and creative methods for dealing with complex issues; sound judgement making in the absence of complete data.
Professional Practical Skills:
On successful completion of the Programme you will be able to demonstrate:
- Advanced scholarship and practical experience in programming skills, data handling and extraction skills, machine learning and informatics skills, and problem solving and modelling skills
- An ability to evaluate methodologies and develop critiques of them and, where appropriate, to propose new hypotheses.
Transferable/Key Skills:
On successful completion of the Programme you will be able to demonstrate:
- The ability to communicate ideas, principles and theories effectively by oral, written and practical means to both specialist and non-specialist audiences.
- Effective working in a team and as an individual.
- The ability to apply logical and analytic thinking to problems.
Tuition fees for 2022 entry
Your tuition fees and how you pay them will depend on your fee status. Your fee status could be home, island or overseas.
Fees for home status
| Year | Tuition fee | Deposit |
|---|---|---|
| Year one | £10,200 | None |
Students from the EU, EEA and Switzerland
If you are an EU, EEA or Swiss national, your tuition fees for 2022/23 be in line with the overseas fees for international students, unless you qualify for home fee status. UKCISA have provided information about Brexit and tuition fees.
Fees for island status
Fees for overseas status
| Year | Tuition fee | Deposit |
|---|---|---|
| Year one | £24,950 | £1,000 |
Financial support
Financial support may be available to individuals who meet certain criteria. For more information visit our funding section. Please note that these sources of financial support are limited and therefore not everyone who meets the criteria are guaranteed to receive the support.
Additional costs
The University considers that the following costs do not need to be covered by schools as they are either not essential or are basic costs that a student should be expected to cover themselves:
- Calculators
- General stationery
- Text books (assumed to be available in the library)
- Non-essential copying / printing.
If there are optional costs/fees to be covered by the student, these are not a requirement to pass the degree. The exception to this is the cost of printing and binding of the final dissertation for submission, which must be paid for by the student.
cardiff university data science ranking
Next, we consider cardiff university data science ranking, msc data science and analytics, data science and analytics courses and is cardiff a good place to study.
Cardiff University was ranked as one of the world’s top 154 Universities by the QS World University Rankings 2019/20. As a member of the Russell Group, Cardiff is one of Britain’s top 24 leading research universities.
The QS World University Rankings are based on six indicators: academic reputation (40%), employer reputation (10%), faculty-to-student ratio (20%), citations per faculty (20%), and international students (5%).
msc data science and analytics
More details coming up on msc data science and analytics, data science and analytics courses and is cardiff a good place to study.
Format: One year full-time or two year part-time (MRP option) and two year full-time (Thesis option)
Degree Earned: Master of Science
This unique Master of Science (MSc) degree program enables students to develop interdisciplinary skills, and gain a deep understanding of technical and applied knowledge in data science and analytics. Graduates are highly trained, qualified data scientists who can go on to pursue careers in industry, government or research. The program is offered as a one year full-time or two year part-time MRP option and two year full-time Thesis option.
The MSc in Data Science and Analytics is delivered in both lecture-based and hands-on lab learning environments where students can develop and apply their skills to complex, real-world datasets and data science and analytics problems.
Admissions Information
MSc
- Completion of a four-year undergraduate (or equivalent degree) from an accredited institution in engineering, science, business, economics or a related discipline
- Minimum grade point average (GPA) or equivalent of 3.00/4.33 (B) in the last two years of study
- Statement of interest
- Resumé/CV
- Transcripts
- Two letters of recommendation
- English language proficiency requirement
More information on admission requirements. Due to the competitive nature of our programs, it is not possible to offer admission to everyone who applies that meets the minimum entrance requirements for the program.
Check Application Deadline
Students are encouraged to submit applications prior to the first consideration date to increase their chances of securing financial support for their graduate studies. Applications received after the first consideration date will be accepted and reviewed based on spaces remaining in the program.
Financing Your Studies
For detailed graduate tuition and fees information please visit Fees by Program.
For information on scholarships, awards and financing your graduate studies visit Financing Your Studies.
Skills Developed
- Domain knowledge
- Machine learning
- Math
- Operations research
- Programming
- Statistics
Sample Courses
- Advanced Data Visualization
- Bayesian Statistics and Machine Learning
- Data Mining and Prescriptive Analysis
- Designs of Algorithms and Programming for Massive Data
- Interactive Learning in Decision Processes
- Machine Learning
- Management of Big Data and Big Data Tools
- NLP (Text Mining)
- Social Media Analytics
Resources
- Students can apply to participate in DMZ programming, where they have the opportunity to create their own startups or work with companies engaged in big data and data science.
- Students may have direct access to various international partners and/or exchange programs to enhance their learning experience.
- Toronto Metropolitan University’s Big Data Initiative (BDI) spans many academic units and research areas. The Data Science Laboratory, RC4 High Performance Computing Facility, and Privacy and Big Data Institute are part of Toronto Metropolitan University’s cross-university BDI agenda to develop new tools and apply them to advance organizational performance across sectors.
- The program engages with various industry and government partners from diverse domains.
Contact Us
Graduate Admissions
Graduate Studies Admissions Office
11th Floor, 1 Dundas Street West
Toronto, ON
Telephone: 416-979-5150
Email: grdadmit@ryerson.ca
For information specific to programs, please see the program contact information below.
Program Contacts
Dr. Ayse Bener
Graduate Program Director
PhD, Information Systems, London School of Economics
Research areas: machine learning, recommender systems and big data applications
Telephone: 416-979-5000 ext. 553155
Email: ayse.bener@ryerson.ca
Igor Rosic
Graduate Program Administrator
Telephone: 416-979-5000 ext. 553693
Email: datascigrad@ryerson.ca
data science and analytics courses
Data analytics and data science are both terms that are used to describe the process of analyzing data. However, they have very different focuses, and they’re often used interchangeably when they shouldn’t be.
Data analytics focuses more on viewing the historical data in context while data science focuses more on machine learning and predictive modeling. Data science is a multi-disciplinary blend that involves algorithm development, data inference, and predictive modeling to solve analytically complex business problems.
Data analytics is often thought of as “historical” because it looks at past datasets to inform future decisions. Data scientists use historical information to identify trends and patterns that can help predict future behavior for better decision-making.
Predictive modeling is one of the primary roles of a data scientist—they can use algorithms to find patterns in existing data and then forecast what might happen next based on those patterns.
is cardiff a good place to study
If you’re looking to study at university in Cardiff, then you’ve come to the right place!
Cardiff University is well renowned for its research centre, with loads of important academic research being carried out here. In fact, it ranks in the top five unis in the UK for its research efforts, and has have been awarded several higher-education awards – you never know, you could end up being the next Einstein.
As well as having a great reputation for teaching and research, Cardiff is also known amongst students as being one of the best cities to live in when studying at university. With plenty going on socially and culturally throughout the year, there’s no chance of getting bored here!
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