Data Analytics

Entry requirements

You will be required to have:

• a 2:2 UK degree (or equivalent) in any discipline that involves an element of data analysis (applicants with relevant professional experience will also be considered)
• a 2:1 UK degree (or equivalent) in a non-mathematics or computing discipline where an element of data analysis can be demonstrated

All applicants must be able to demonstrate proficiency in the English language.

Months of entry

January, May, September

Course content

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.

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

Core modules include:

· Data Analysis and Visualisation (core, 20 credits)

· Data Mining for Business Intelligence (core, 20 credits)

· Data Modelling and OLAP Techniques for Data Analytics (core, 20 credits)

Please refer to the course page on the London Met website for the full list of modules.

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.