Computer Science (Top-Up)
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About this course
Passionate about tech? Want to make a change? Computer science is a priority skills area with a shortage of computer science professionals (WYCA, 2021), so now is the time to enter this exciting and thriving sector. The growth in employment in the technology sector in the Yorkshire region is significant. There are nearly 9000 tech companies in the Yorkshire region with a turnover of £3.67bn (Information Age, 2019).
With this top-up course, you will refine and develop your knowledge and skills across computer science, be ready to problem-solve and apply yourself to the many opportunities and roles in the sector. With the chance to make social, political, global change and more, you can look forward to being part of a sector making enormous contributions to society, and that's at the forefront of technology.
Computer Science is an ever-important subject and is useful in both the modern world and digital economy. An academic as well as a practical subject, this course will provide you with a taste of both aspects of Computer Science. It deals with the process of solving problems, and every part of our world has some sort of problem that needs solving. It’s also a field that offers many career opportunities.
As a computer scientist, you will be able to embrace the many opportunities available to you to make enormous contributions to society. A large and lucrative job market with a variety of jobs is available to graduates of this programme because the program was developed with your career aspirations and goals at the centre.
This course was created with the knowledge and recognition that today’s computer scientists have a range of expertise and are in high demand. This course will enable you to combine analytical knowledge and technical skills as you learn, research and develop solutions to real-world problems. This course will provide you with the technical as well as analytical skills to make you excel in a Computer Science career such as data scientist, data warehouse developer, data warehouse engineer, machine learning developer, machine learning engineer, data analyst and many more.
There is a strong emphasis on practical skills development in this course that will ensure you are ready to commence your career journey immediately after completing the course. In this course, you will obtain the knowledge and the skill of using data and algorithms to imitate the way that humans learn, gradually improving its accuracy in the machine learning module. Machine learning is a branch of AI and has become an important component of the growing field of data science. Another important module in the course is Data Warehouse. Data warehouse is a type of data management system that is designed to enable and support business intelligence (BI) activities, especially data analytics. Data warehousing is growing in importance because of the importance of Big Data. This module will enable you to learn and acquire skills in developing a data warehouse. Other modules in this course are research methods and digital entrepreneurship.
Modules
Modules may include:
Level 6
Data Warehousing (20 credits)
You will be introduced to the concepts and practicalities of Data Warehousing. Data warehouses are central repositories of information that can be analysed to make more informed decisions. This module will explore data warehouse architectures, decision making, data warehouse design & modelling, data quality, and data warehouse implementation in supporting decision making. You will learn and develop star and cube schemas while studying this module. The module will embrace how data and analytics have become indispensable to businesses to stay competitive. The module will also explore data mining. The content will encapsulate Data protection, GDPR, and Privacy.
Machine Learning (20 credits)
This unit provides you with the knowledge, understanding and exploration of the theory and practical application of common Machine Learning models and algorithms. The models/algorithms explored will include Supervised and Unsupervised models: Regression, decision trees, random forests; neural networks, clusters, and Principal Component Analysis.
Research Methods (20 Credits)
You will develop the necessary knowledge and skills to select and apply appropriate research methods to an independent study project. This module will enable you to acquire skills such as critical reading and critical thinking, analysis of data using appropriate statistical methods, and reflective practice.
Digital Entrepreneurship (20 Credits)
You will explore how entrepreneurial ventures using digital technology and e-marketing can be developed. The emphasis of the module is on practical aspects of digital entrepreneurship, including digital entrepreneurship skills, tools, practices and processes. You will look at how digital entrepreneurial ventures can be monetised to generate income, and marketing strategies incorporating social media.
Major Project (40 credits).
You will identify a problem and set about planning and delivering a solution to that problem within a strict time frame. You may choose to develop an online solution, develop a mobile app, or provide a business solution. You will utilise existing development methodologies and tools in order to successfully plan and manage their project. You will produce a proposal for their project, produce designs and practical elements, and write a report reviewing the research used and evaluating the development of the project.
Assessment methods
You will be assessed in a variety of ways including practical tasks, portfolios, essays, case studies and presentations.
Tuition fees
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Computer science
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