DipHE Data Science

In this module, you will be introduced to the Python programming language and will build your skills working with a range of Python libraries for analysing, manipulating and visualising data, including NumPy, Pandas, SciPy, Matplotlib and Seaborn. Based around practical exercises and challenges, this module will develop your problem-solving skills and proficiency in Python. This module will also focus on developing your computational thinking, challenging you to think like a computer scientist when tackling problems. 

This module will introduce you to relational databases and the fundamentals of Structured Query Language (SQL). In the first half of the module, practical workshops will introduce you to using SQL to query, extract and analyse data. In the second half, you will learn how to design a database and take into consideration issues such as data security, recovery and integrity.

R is a widely used programming language in statistics, used to assess the governing company's financial performance, as well as other performance indicators, for example, patient outcomes for the NHS. You will undertake practical assessments from companies, evaluating statistical performance.

In this module, you will consider the importance of good data visualisation for communicating with data. You will learn the principles and theory behind data visualisation, best practices when visualising data and how to avoid misleading visualisations. Practical workshops will introduce you to industry standard tools for building data dashboards and reports and, across the module, you will create your own portfolio of dashboards and data stories.

This module will introduce you to the core concepts of supervised and unsupervised machine learning, and how we can use machine learning to discover patterns in data and make predictions. 

The emphasis of the module is on practical application and you will use the Python programming language, and libraries such as Scikit Learn, to implement machine learning algorithms and build predictive models.

This module sheds light on the use of business intelligence (BI) systems in organisational scenarios. The module will provide you with a broad set of skills applicable to the origins and evolution of BI systems, as well as distinctions between characters, data, information and knowledge.

Students will also learn about BI Systems, Data and Information, Problems with data, Data Warehousing, OLAP and Data Mining.

Deep learning is at the heart of many of today's advances in Artificial Intelligence (AI). You will learn the theory behind neural networks and you will discover how deep learning is used within fields such as computer vision. Practical workshops will challenge you to build and train your own neural networks, working with a range of datasets of increasing complexity.

The Professional Practices module will equip you with the research and professional skills required within industry. You will undertake team working used in the workplace, on real-world mathematics problems for which you will be required to develop a solution. You will also learn about the professional body, reflect on your skills and future direction with continuing professional development, and also take library-led courses on CV writing and soft skills development.

In this module, you will learn the challenges and opportunities which characterise Big Data and will gain practical skills working with the tools and techniques used to process and analyse Big Data.

In this module, you will learn the text mining techniques and methods used to analyse unstructured text and the latest deep learning approaches to Natural Language Processing (NLP). You will consider a wide range of applications, including text classification, document clustering, sentiment analysis and chatbots.

In this module, you will use your data science and analysis skills to work with a complex dataset and solve a real-world business problem. You will synthesise the knowledge you have gained throughout the course to develop and justify your own solution. You will also develop your written and oral communication skills and learn how to communicate your results to both technical and non-technical stakeholders.

This module sheds light on the role of business leadership and management in digital business scenarios. The module will provide you with a broad set of skills applicable to leadership in contemporary digital business, including skills development in management styles in digital business scenarios, digital business strategy, digital innovation and digital analytics and customer insights.