Applied Data Science (Online)

Program Overview

Applied Data Science (Online) MSc

Overview

Data scientists are responsible for the handling of raw data, analysing it, identifying patterns and presenting insights for forecasting and predicting business problems. Data science uses maths, statistics, machine learning, a range of computer science disciplines and a common toolset such as Python, SQL, and R.

Course Details

Core Modules

• Artificial Intelligence Ethics and Applications
  • Gain a deep insight into the business applications of artificial intelligence (AI) and data science (DA).
  • Explore a range of AI and DS applications such as chatbots, virtual assistants, medical diagnosis, biometric recognition, personalisation, fraud detection and autonomous machines, and analyse both the risks and opportunities of applying AI and DS techniques in these areas.
• Big Data and Business Intelligence
  • Develop your ability to design and implement database, big data and analytics applications to meet business needs.
  • A case study is used to follow the system development lifecycle.
  • Develop a plausible application from inception to implementation for a real-world scenario.
• Computing Masters Project
  • Undertake a major, in-depth, individual study in an aspect of your course.
  • Normally computing master’s projects are drawn from commercial, industrial or research-based problem areas.
  • The project involves you in researching and investigating aspects of your area of study and then producing a major deliverable, for example software package or tool, design, web-site and research findings.
  • Critically evaluate your major deliverable, including obtaining third party evaluation where appropriate.
• Data Science Foundations
  • Gain an introduction to core data science concepts and tools, focusing on real-life data science problems with practical exposure to relevant software.
  • Topics such as preparing and working with data, data visualisation and databases are covered.
• Interactive Visualisation
  • Dynamic, interactive visualisations enable the reader to explore the data for themselves through a variety of perspectives.
  • Static visualisations are excellent for print medium but are restricted to showing a single perspective and do not handle multidimensional datasets well.
  • Using an interactive graphic the reader can zoom in on sections of the data which are of interest, explore more than one dimension at a time, and sort and filter to discover new patterns and themes within the data.
• Machine Learning
  • Machine learning is a subfield of computer science concerned with computational techniques rather than performing explicit programmed instructions.
  • Build a model from a task based on observations in order to make predictions about unseen data.
  • Such techniques are useful when the desired output is known but an algorithm is unknown, or when a system needs to adapt to unforeseen circumstances.
• Software for Digital Innovation
  • Gain an introduction to the Python programming language and its application to solving problems in digital innovation.
  • This involves the principles of programming, the syntax and structure of Python, its relevant libraries and modules, and how it is incorporated in existing software tools.

How You Learn

• Your learning is supported through our online learning environment, where our experienced staff can provide advice and guidance.
• Opportunities to network with staff and other students enable you to work collaboratively, developing your technical skills and knowledge.
• You learn through keynote lectures and tutorials using case studies and examples.

How You Are Assessed

• You are assessed informally throughout the programme to help you prepare for your formal course assessments.
• You are assessed on your subject specific knowledge, cognitive and intellectual skills and transferable skills applicable to the workplace.

Entry Requirements

• A UK bachelor’s honours degree (2.2 minimum) or equivalent overseas qualification in any subject.
• International students will require IELTS 6.0 or equivalent.

Employability

Career Opportunities

• Companies hiring data science professionals include American Express, AstraZeneca, BBC, IBM, Mastercard, Rolls Royce, Space Ape Games, Warner Bros. Entertainment, WhatsApp, plus many more.
• Graduates can expect to find employment in one of the increasing number of sectors needing specialists equipped with the cutting-edge expertise in financial and digital technologies.
• According to itjobswatch.co.uk, the median salary in the UK for data science professionals is £65k but the top 10% can earn upwards of £100k.

Learning Platform

Our Virtual Learning Environment (VLE) is the Platform You Use to Access Your Online Course

• Teesside University online learning courses are delivered through the Brightspace Learning Environment.
• Here are some of the benefits:
  • You can use it on your smartphone, tablet and computer.
  • And you can use it anytime, so that you can plan your learning to fit your own schedule.
  • It's easy to use and navigate.
  • Modules are set out by topics and themes.
  • You can use the progress bar to understand where you are in your modules, and appreciate your achievements.
  • We support you to become familiar with your VLE, helping you to start learning quickly.
  • You get feedback, help and guidance from tutors throughout your course through the VLE, and you can ask questions at any time.
  • Our tutors use a live activity feed to keep you updated about your course.
  • You can create a student profile, collaborate with other students and take part in online discussion forums.

Full-time

Fee for All Applicants

• £12,150
• £1,350 for each 20 credits

Length

• 1 year

Attendance

• 100% online

Start Date

• September

Semester Dates

• Available on request

Part-time

Fee for All Applicants

• £930 for each 20 credits
• £8,370 in total

Length

• 2 years

Attendance

• 100% online

Start Date

• September

Semester Dates

• Available on request