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University of Derby: Advanced Data Science
| Institution | University of Derby View institution profile |
|---|---|
| Department | Department of Computing and Mathematics |
| Web | www.derby.ac.uk/postgraduate |
| askadmissions@derby.ac.uk | |
| Telephone | 01332 591167 |
| Study type | Taught |
Summary
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Join a course that focuses on the extraction, analysis and management of information from big data using a variety of scientific techniques and software tools
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Gain in-depth knowledge and critical understanding of a range of issues and concepts in Advanced Data Science
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Learn to incorporate the latest techniques and approaches thar are delivered by research-active academic tutors
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Develop the ability to effectively apply a variety of scientific techniques to real-world problems arising in diverse fields.
Future focused content Big data is all around us and the ability to identify and obtain intelligence from this requires a set of skills which is increasingly in demand. This programme provides a robust grounding in the key principles and tools of data science, together with a strong focus on industrial applications.
This master’s programme has been designed in conjunction with SAS (Data and AI Solutions), a leading provider of software platforms for data mining and business intelligence, widely used in both industry and academia. You will develop a critical and deep understanding of the relevant theoretical aspects related to big data that is integrated with SAS, as well as other up-to-date software applications, to gain a comprehensive knowledge relevant to both prospective and well-established IT professionals and entrepreneurs, who want to make an impact in the field of Advanced Data Science.
In addition, you will be able to complement your studies with an appropriate SAS qualification, upon successful completion of the relevant examinations. You can also meet the criteria for Chartered Information Technology Professional status, upon completion of satisfactory post programme industrial experience.
MSc
| Level | RQF Level 7 |
|---|---|
| Entry requirements | Applicants for the MSc Advanced Data Science programme will normally hold a 2.2 or higher Bachelor’s degree in a Science, Technology, Engineering, Mathematics (STEM) or a closely related discipline with significant mathematical content at an appropriate level, or an equivalent international degree. Applicants who do not meet these criteria may still be eligible if they can demonstrate relevant work experience in a management or supervisory position, supported by employers’ references, and can demonstrate effective communication and learning skills and the motivation to succeed during an interview. Where required, interviews will be conducted by the Programme Leader and may be undertaken by telephone where access to campus may be prohibitive. |
| Location | Markeaton Street Markeaton Street Derby DE22 3AW |
| Level | RQF Level 7 |
|---|---|
| Entry requirements | Applicants for the MSc Advanced Data Science programme will normally hold a 2.2 or higher Bachelor’s degree in a Science, Technology, Engineering, Mathematics (STEM) or a closely related discipline with significant mathematical content at an appropriate level, or an equivalent international degree. Applicants who do not meet these criteria may still be eligible if they can demonstrate relevant work experience in a management or supervisory position, supported by employers’ references, and can demonstrate effective communication and learning skills and the motivation to succeed during an interview. Where required, interviews will be conducted by the Programme Leader and may be undertaken by telephone where access to campus may be prohibitive. |
| Location | Markeaton Street Markeaton Street Derby DE22 3AW |
| Level | RQF Level 7 |
|---|---|
| Entry requirements | Applicants for the MSc Advanced Data Science programme will normally hold a 2.2 or higher Bachelor’s degree in a Science, Technology, Engineering, Mathematics (STEM) or a closely related discipline with significant mathematical content at an appropriate level, or an equivalent international degree. Applicants who do not meet these criteria may still be eligible if they can demonstrate relevant work experience in a management or supervisory position, supported by employers’ references, and can demonstrate effective communication and learning skills and the motivation to succeed during an interview. Where required, interviews will be conducted by the Programme Leader and may be undertaken by telephone where access to campus may be prohibitive. |
| Location | Markeaton Street Markeaton Street Derby DE22 3AW |
| Level | RQF Level 7 |
|---|---|
| Entry requirements | Applicants for the MSc Advanced Data Science programme will normally hold a 2.2 or higher Bachelor’s degree in a Science, Technology, Engineering, Mathematics (STEM) or a closely related discipline with significant mathematical content at an appropriate level, or an equivalent international degree. Applicants who do not meet these criteria may still be eligible if they can demonstrate relevant work experience in a management or supervisory position, supported by employers’ references, and can demonstrate effective communication and learning skills and the motivation to succeed during an interview. Where required, interviews will be conducted by the Programme Leader and may be undertaken by telephone where access to campus may be prohibitive. |
| Location | Markeaton Street Markeaton Street Derby DE22 3AW |
Be the next game-changer at the University of Derby
Take your career to the next level, or in a new direction, with postgraduate study at the University of Derby. With expert teaching, research innovation and industry engagement underpinning your studies, you are set to receive a high-quality learning experience in which you can pursue your passion.
Derby is nestled in the heart of England and benefits from fantastic transport links, meaning popular UK cities such as Manchester, Birmingham and London are within easy reach. With East Midlands airport on the doorstep offering a gateway to exciting global …
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