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Why study this course?

On our Data Analytics MSc you'll be introduced to subjects including data mining, statistical modelling, business intelligence and data visualisation. The course has been developed with direct input from industry experts who’ll present you with real-life business cases as part of your work-related learning. By the end of the MSc degree, you’ll be ready to apply for rewarding roles in the data science and big data industries, as well as the many sectors and organisations that increasingly require data analysts.

In the most recent Destinations of Leavers from Higher Education (DLHE) survey, 100% of all 2017 graduates from this course were in work or further study within six months.

More about this course

This postgraduate course will equip you with the theoretical, technical and practical skills required to become a data analyst. With an expert teaching team, access to specialist software and work on real-life business cases, you’ll be well prepared for a career in data analytics upon graduation.

The modules on this course have been developed with the help of industry professionals, some of whom will be present to teach you in specific classes. These experts will help you explore advanced techniques in data science. You'll study specialist subjects including financial mathematics, statistical modelling and forecasting, as well as having the chance to develop your own unique piece of work in the MSc Project module.

You’ll also be trained to use specialist software tools and environments currently used by professionals in industry. For example, you’ll have access to R and Python programming, IBM SPSS, SAS®, Tableau, Oracle and Hadoop. Familiarity with these tools will greatly enhance your employability upon graduation.

Our skilled professionals will expose you to real-life business case scenarios. For example, past students have worked on data warehouse projects with Lloyds Bank. This ensures you’ll develop practical skills and become familiar with the kind of challenges you could face in data analyst roles.

Assessment

The course is assessed in a number of ways including written reports, practical and research assignments, demonstrations, presentations, group work and examinations.

Modular structure

The modules listed below are for the academic year 2018/19 and represent the course modules at this time. Modules and module details (including, but not limited to, location and time) are subject to change over time.

Year 1 modules include:

  • Data Analysis and Visualization (core, 20 credits)
  • Data Mining for Business Intelligence (core, 20 credits)
  • Data Modelling and OLAP Techniques for Data Analytics (core, 20 credits)
  • MSc Project (core, 60 credits)
  • Programming for Data Analytics (core, 20 credits)
  • Statistical Modelling and Forecasting (core, 20 credits)
  • Financial Mathematics (option, 20 credits)
  • Work Related Learning (option, 20 credits)

After the course

Upon completion of the course, you’ll be well equipped to work in some of the fastest growing sectors of the data science and big data industries. A wide range of career opportunities will be open to you in the commercial, public and financial sectors, especially in areas requiring big data analysis such as consumer, healthcare, scientific, financial, security intelligence, business and social sciences.

Job roles you could apply for include data scientist, data analyst, digital analyst, big data consultant, statistical analyst and data modeller. You’ll be eligible to work in a multitude of areas where skills such as R or Python programming, machine learning and statistical modelling, SAS® and SPSS experience, data visualisation and data-driven decision-making are required.

The course also provides you with an excellent basis for further study if you want to pursue a higher-level research degree or embark on an industry-based research career.

Additional costs

Please note, in addition to the tuition fee there may be additional costs for things like equipment, materials, printing, textbooks, trips or professional body fees.

Additionally, there may be other activities that are not formally part of your course and not required to complete your course, but which you may find helpful (for example, optional field trips). The costs of these are additional to your tuition fee and the fees set out above and will be notified when the activity is being arranged.

How to apply

Use the apply online button to begin your application.

When to apply

You are advised to apply as early as possible as applications will only be considered if there are places available on the course.


Visit the Data Analytics MSc page on the London Metropolitan University website for more details!

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