MSc Data Science at Northumbria University

DATA SCIENCE AT NORTHUMBRIA

Welcome to Data Science at Northumbria University Data Science MSc

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YOUR COURSE

Why Data Science at Northumbria?

▪ Designed through our own research and through consultation with Northumbria’s Institute of Coding (IoC) and data scientists from the industry, Data Science MSc provides you with the relevant skills needed to analyse, synthesise and manage different types and sizes of data efficiently.

▪ This course is suited to those who have an undergraduate degree in computing/ information sciences, or mathematical and statistical disciplines with applied computing components. Alternatively, those with a considerable computing background in an industrial / business setting are suitable applicants.

▪ Ideal for graduates who wish to advance their career by becoming a data scientist.

▪ Demand for those with specialist data science qualifications is high and this course can prepare you for a range of careers in the modern digital world .

Data Science at Northumbria ▪ Our Data Science MSc will provide you with the ability to explore data insights to ensure organisations are making the most out of their data.

▪ You will develop knowledge insight from a variety of structured and unstructured data, using a range of data analysis methods, processes, algorithms and systems.

▪ The course provides a greater understanding of Big Data and Cloud computing and will equip you with skills needed to tackle realistic Big Data problems.

▪ You will use principal machine learning methods, advanced database technologies, data visualisation techniques and statistical approaches to apply modern, analytical and statistical techniques to business data - combining both theoretical and practical approaches.

▪ You develop programming skills in Python and R for effective, efficient, statistical data analysis.

Data Science at Northumbria What is unique about it?

▪ A multi-disciplinary programme, it combines computing and information sciences, statistics, mathematics, and Artificial Intelligence through machine learning.

▪ Developed by our staff who have a wealth of experience in a range of subjects in data science in collaboration with nationwide Institute of Coding (IoC) and in consultation with data scientists from the industry, wider academic community as well as present and past students – to ensure students learn up-to-date knowledge and practical skills in data science.

▪ Covers the entire breadth and depth of the data science discipline.

Data Science at Northumbria Specialist Modules and Topics

DISCLAIMER: Please note that information, advice and guidance received at the Open Day is accurate as of today, and is subject to change as we review our courses and our offers to ensure that you are receiving the best possible educational experience. The University continues to monitor guidance in relation to Covid-19 to ensure compliance with government requirements and to ensure the health and safety of our students and staff.

Our website is the most up to date place to review our information.

Data Science MSc

Generic Module

Specialist Module

Examples of Current Modules Research Methods and Project Management

MSc Computer Science & Digital Technologies Project

Principles of Data Science

Advanced Databases

Academic Language Skills for Computer and Information Sciences (Optional)

Statistical Programming

Big Data and Cloud Computing

Machine Learning

DISCLAIMER: Please note that information, advice and guidance received at the Open Day is accurate as of today, and is subject to change as we review our courses and our offers to ensure that you are receiving the best possible educational experience. The University continues to monitor guidance in relation to Covid-19 to ensure compliance with government requirements and to ensure the health and safety of our students and staff.

Our website is the most up to date place to review our information.

Three Ways to Study Standard (12 months)

Semester 1 (Sept – Jan)

Semester 2 (Feb - May)

Semester 3 (June - Aug)

Principles of Data Science

Statistical Programming

Masters Project

Big Data and Cloud Computing

Machine Learning

Advanced Databases

Research Methods and Project Management

Academic Language and Information (option) Semester 1 (Sept – Jan) Skills for Computer Semester 2 (Feb -Sciences May)

Standard (16 months)

Principles of Data Science

Statistical Programming

Big Data and Cloud Computing

Machine Learning

Advanced Databases

Research Methods and Project Management

Summer break (June - Aug)

Semester 1 (Sept - Jan)

Masters Project

Academic Language Skills for Computer and Information Sciences(option)

With Advanced Practice* (2 Years)

Semester 1 (Sept – Jan)

Semester 2 (Feb - May)

Principles of Data Science

Statistical Programming

Big Data and Cloud Computing

Machine Learning

Advanced Databases

Research Methods and Project Management

Academic Language Skills for Computer and Information Sciences (option)

Summer break Semester 1 (Sept – (June - Aug) Jan) Engineering and Environment Advanced Practice (60 Credits) either: - Study abroad** - Internship** - Research**

Semester 2 (Feb - May)

Masters Project

Advanced Practice provides an opportunity to apply skills and knowledge acquired during the taught part of the programme and to acquire new skills and knowledge in an alternative learning environment. *Please note that we are no longer accepting new applications for Advanced Practice or Study Abroad courses starting in September 2020. **Subject to availability and government guidance during Covid-19.

Teaching and Assessment Teaching ▪ Courses are split into modules worth 20 or 60 credits. You study for 180 credits.

▪ You will take six taught modules covering principles of: ▪ data science

▪ Big Data in a cloud computing setting

▪ advanced databases

▪ machine learning

▪ computational and statistical methods and techniques

▪ transferable skills in project management and research

▪ programming in Python and R

▪ You will learn through lectures, practical sessions in workshops, computer-based seminars and guided learning.

▪ On average 12 hours of self-directed study is required per module per week during a semester of 12 weeks.

▪ Students receive 4 hours of contact time per taught module per week.

Teaching and Assessment Assessment ▪ Assessments reflect professional practice and include: ▪ Project proposal ▪ Professional reflection ▪ Written Assignments ▪ Research reports ▪ Group work ▪ You will also undertake a major data science project, allowing you to specialise in a subject of interest to you (e.g. Business Analytics, Health Analytics and Game Analytics). The summative assessments for this module are a written dissertation (typically 10-12000 words) and project viva.

If you are joining us in September 2020 ▪ Your health and wellbeing are our priority – but so is your education, and we will work tirelessly to deliver our quality learning experience safely.

▪ If you can travel safely to us, we will welcome you from 21st September 2020 for your induction programmes; teaching will start from 28th September. If you can’t travel to us safely, you will start online and join us when you can.

▪ Learn on campus with fellow students, as appropriate, through small group teaching, with access to digital hubs, classrooms, laboratories, studios and clinics, and with full access to the University Library – one of the best academic libraries in the UK. ▪ On-campus learning will be combined with flexible online study; with online lectures (both live and prerecorded), interactive activities, webcasts, seminars, workshops, discussion groups and more. You will experience a truly blended learning experience.

▪ Online learning will be collaborative and engaging – designed for a virtual experience and tailored to you and your subject and delivered through our user friendly learning environment – Blackboard Ultra – providing access to virtual classrooms, laboratories, studios, clinics and our library online.

▪ Taught, directed and independent learning activities will be clearly communicated week by week, developing your critical thinking and enabling you to challenge yourself and each other, and apply your learning.

Our Staff â–Ş Our teaching staff include cuttingedge researchers, whose areas of specialisms include topics covered on this course, helping ensure that teaching is right up-to-date. â–Ş Specialisms include big data, data mining, machine learning, digital literacy, information behaviour, information retrieval systems, recommender systems, and the link between information science and cognitive psychology.

Dr Akhtar Ali Programme Leader and Leads Advanced Databases

Dr Naveed Anwar Leads Statistical Programming

Dr Jeremy Ellman Leads Big Data and Cloud Computing

Dr David Hastings Leads Principles of Data Science

Research Rich Learning ▪ We are living in an age where all of our lives are impacted and challenged by digital technologies and information sciences, from cyber security and AI, to social media, games and visual effects, to digital libraries, archives and records.

▪ Our research addresses and explores this through our research groups in Computational Intelligence and Visual Computing (CIVC); Information Management and Data Analytics (IMDA); Network Systems and Security (NetSyS), our Digital Learning Laboratory and the Northumbria Social Computing (NorSC) Lab. ▪ The majority of our research in Computer Science ranked world-leading or internationally excellent according to the latest UK wide research assessment exercise (Research Excellence Framework (REF) 2014).

Entry Requirements for 2020 ▪ Applicants should normally have a minimum of a 2:2 honours degree (or equivalent) in a quantitative subject such as computer / information science, engineering, maths, statistics, or a related discipline (e.g. IT, software engineering). Other subject qualifications, equivalent professional qualifications and/or relevant work experience will be considered on an individual basis.

▪ International qualifications - if you have studied a non-UK qualification, you can see how your qualifications compare to the standard entry criteria, by selecting the country that you received the qualification in from our country pages at www.northumbria.ac.uk/yourcountry.

▪ English language requirements - International applicants are required to have a minimum overall IELTS (Academic) score of 6.5 with 5.5 in each component (or approved equivalent*). * The university accepts many UK and International Qualifications in place of IELTS. You can find more details at www.northumbria.ac.uk/englishqualifications.

YOUR CAMPUS

Our Facilities ▪ Northumbria are 11th in the UK for Facilities.*

▪ Major campus investment in recent years – Sport Central, Student Central, Digital Commons, Architecture Studios, Computer and Information Sciences Building.

▪ One of the best academic libraries in the UK, held Customer Service Excellence (CSE) accreditation since 2010, and with 24/7 access.*** ▪ Our IT, library and course resources are all ahead of sector for satisfaction.** *Times Higher Education Student Experience Survey 2018 ** National Student Survey 2019 *** Digital library is currently 24/7, access to library learning spaces reviewed in line with Covid-19 guidance.

Data Science Facilities ▪ Taught in our new Computer and Information Sciences building at City Campus, in the centre of Newcastle.

▪ Our new state-of-the-art £7m Computer and Information Sciences building, provides a world-leading learning and teaching environment for students and staff.

▪ This gives you access to dedicated IT systems and is available evenings and weekends.

▪ Specialist software includes Python anaconda, R studio, Weka, Oracle database, Oracle Big Data, Oracle NoSQL, Mathlab, Wolfram Mathematica.

YOUR EXPERIENCE

On-course Experience ▪ Guest data scientists from the industry ▪ Fujitsu ▪ IBM ▪ Access to academic-industry partnerships for research projects ▪ Institute of Coding (IoC) ▪ http://newsroom.northumbria.ac.uk/pressreleases/ethicalhackers-help-boost-businesses-digital-resilience2967987 ▪ https://instituteofcoding.org/events/teach-the-nation-tocode-python/ ▪ Access to seminars of research groups within the CIS department ▪ https://www.northumbria.ac.uk/about-us/academicdepartments/computer-and-informationsciences/research/

YOUR FUTURE

Career Success at Northumbria ▪ Boost your earning potential: according to the Department for Education’s Graduate Labour Market Statistics 2017, postgraduates earn on average £6,000 a year more than their undergraduate counterparts.

▪ Which? University Student Survey 2018 ranked us as one of the top rated universities for ‘job readiness’ in the UK. ▪ Northumbria is ranked 2nd in the UK for graduate start-ups based on turnover, according to the HEBCIS Survey 2018/19.

▪ Graduate Futures - our Careers and Employment service will help at every stage, from finding part-time jobs that fit alongside your studies and volunteering opportunities, through to finding your first full-time job after graduation.

Where do our Graduates Go? â–Ş Demand for those with specialist data science qualifications is high and this course can prepare you for a range of careers in the modern digital world. â–Ş You will be well-placed to take up a range of roles available in the IT based business world including, but not limited to, Information and Data Manager, Business Systems Analyst, Enterprise Data Analyst, Data Scientist, Data Engineer, and Data Specialist. These roles are in a variety of industries including investment management, healthcare and banking, amongst many others.

THANKS FOR WATCHING. What’s Next?

▪ Have any questions? Why not speak to our academics who are live right now, using our LIVE CHAT feature on the bottom right?

▪ To explore our other live events, presentations and live talks go back to the main event menu or view ‘My Itinerary’ ▪ For Application queries email bc.applicantservices@northumbria.ac.uk ▪ For Course queries email akhtar.ali@northumbria.ac.uk

DISCLAIMER: Please note that information, advice and guidance received at the Open Day is accurate as of today, and is subject to change as we review our courses and our offers to ensure that you are receiving the best possible educational experience. The University continues to monitor guidance in relation to Covid-19 to ensure compliance with government requirements and to ensure the health and safety of our students and staff. Our website is the most up to date place to review our information.