Course overview
You gain expertise and transferable skills in event-driven programming, patterns, design, development and deployment using industry-standard tools. You also develop your ability to design and implement machine learning, database, big data and analytics applications.
Course details
Course structure
Core modules
You gain experience of application development utilising an agile development approach. You also take responsibility for determining project aims, objectives, roles, tasks, deliverables, schedules and documentation.
By learning agile principles and applying a specific agile approach (eg SCRUM) in a live simulation of the methodology, the module will help you to prepare for contemporary practice in industry, developing both knowledge and skills in the application of agile principles.
Artificial Intelligence Ethics and Applications
You gain a deep insight into the business applications of artificial intelligence (AI) and data science (DA). You 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
You 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. You develop a plausible application from inception to implementation for a real-world scenario.
You investigate the issues and technologies associated with implementing and supporting large scale databases and the services that are needed to maintain and access a repository of data. Investigations are undertaken in a number of areas including big data, data warehouses, integrating legacy data, data management and approaches that support the modelling and visualisation of data for a range of use views.
Machine learning is a subfield of computer science concerned with computational techniques rather than performing explicit programmed instructions. You 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.
You explore statistics and probability theory as the fundamental task is to make inferences from data samples. The contribution from other areas of computer science is also essential for efficient task representation, learning algorithms, and inferences procedures. You gain exposure to a breadth of tasks and techniques in machine learning.
Assessment is an in course assessment (100%).
Software for Digital Innovation
You 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. You form a solid foundation of producing software solutions to real-world problems.
You gain the underpinning knowledge and skills you need for user experience modelling and design. Study the theoretical foundations of human-computer interaction (HCI), interaction design, product design, and participatory design and development. Apply user experience modelling approaches to the design of software applications and services.?
Modules offered may vary.
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 in a professional and supportive space.
You learn through keynote lectures and tutorials using case studies and examples. Critical reflection is key to successful problem solving and essential to the creative process.
How you are assessed
You are assessed informally throughout the programme, which supports your formal 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 degree (2.2 minimum) or equivalent overseas qualification.
In addition, international students will require IELTS 6.0 or equivalent.
For general information please see our overview of entry requirements
Employability
Career opportunities
There are increasing career opportunities for data science specialists in sectors such as the defence industry, financial industry, telecommunications and health sector.
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.