Online degree MSc Data Science

• Programming with Python
  One of the most versatile scripting languages, Python is widely used in web development to scientific computing. Develop your knowledge of Python, including uncovering its key features and applications. 

• Advanced mathematics
  Did you know that modern techniques used to analyse data and make predictions for the future are rooted in advanced mathematics? You’ll explore concepts behind advanced algorithms used to process data. As well as growing your knowledge of vector algebra, vector calculus and information theory. 

• Advanced statistics
  Nearly all processes in nature, including most technical and scientific scenarios, are not deterministic but stochastic. This means the processes are described in terms of probabilities. Learning the concepts of statistics, you’ll be able to apply your new knowledge to various application situations. 

• Machine learning
  Machine learning is a scientific field that teaches machines to perform tasks by finding patterns in data. Explore how you can combine statistics and computing power, as well as a variety of approaches and methods, to achieve this.

• Advanced research methods
  Master the art of empirical research with a focus on business contexts. Learn to develop comprehensive research proposals, handle various data collection strategies, and analyse both quantitative and qualitative data efficiently.

• Deep learning
  Neural networks and deep learning approaches have revolutionised the field of artificial intelligence in recent years. Applications built on these techniques have even surpassed human performance. Discover common neural network architectures and methods to train AI in a range of application scenarios. 

• Use case and evaluation
  What makes a project successful? Evaluating and defining use cases is essential in defining a project, from its scope and technical requirements to its ultimate value. Learn the factors involved, including the monitoring tools needed to evaluate the status quo, and the problems you might encounter along the way.

• Case study: Model engineering
  Discover the main data science methodologies. Learn how to detect data quality issues. Build new features from raw data. And understand the processes and techniques for creating data science models to solve real-world problems.

• Elective (see Electives section below)

• Master thesis
  With the guidance of a supervisor, prepare a written dissertation focused on a major field of study. Scientifically evaluate and critically discuss a chosen issue and suggest possible solutions.   

• Big data technologies
  Database types from relational to NewSQL. Storage formats from CSV to Parquet. Computing environments from local clusters to containers. Gain the technical knowledge you need to harness the power of data.

• Software engineering for data intensive sciences
  Learn how to write high-quality code that runs in a professional production environment. You’ll cover the agile approaches of Scrum and Kanban, specialist techniques like integration testing and pair programming, and concepts of API design.

• Industrial automation
  With industry 4.0, companies need to model, analyse, design and control their production environments. Explore the modelling approaches for the event systems that make up modern manufacturing.

• Architectures of self-driving vehicles
  Delve into the architectural aspects of self-driving cars: from hardware and software platforms to sensor and motion control solutions for braking and steering. You’ll also discuss the ways a self-driving car exchanges information with the outside world, including the ethical and safety considerations.  

• Self-arranged internship (*)

  Gain practical experience by securing and completing an internship, applying your knowledge in a real-world setting and developing hands-on skills in data science.

*You'll be responsible for arranging a suitable internship for your field of study. Once arranged, please complete an application to the internship module via myCampus, to make sure your internship can be recognised and credited towards your course requirements.

You can find more details about your MSc Data Science course in these PDF files:

• Online programme schedule: MSc Data Science

• Programme specification: MSc Data Science

• Once enrolled, you will be expected to meet LIBF's policies and standards.

• LIBF has Taught Degree Awarding Powers (TDAP).

Pursuing a Master's in Data Science online is a good idea for anyone looking to pursue a career in this field. With the increasing importance of data-driven decision making, companies are actively seeking professionals with advanced data science skills.

By completing an MSc in Data Science, you can gain expertise in areas such as statistical analysis, data analysis, programming, machine learning, data science and artificial intelligence making you a highly desirable candidate for a variety of roles in lots of different sectors.

MSc Data Science is a postgraduate online degree programme that focuses on the study of data science, which involves extracting insights and knowledge from large and complex data sets. It is an interdisciplinary field that combines elements of computer science, mathematics, and statistics to analyse and interpret data.

Our programme covers topics such as programming with python, machine learning, statistical analysis, deep learning, and mathematics. Upon completion of an MSc in Data Science, you will possess the skills and knowledge to work in a variety of roles such as data scientist, data analyst, business intelligence analyst, and more, in lots of different sectors.

While pursuing a postgraduate degree in Data Science may require effort and dedication, rest assured that we offer a variety of resources to support you throughout your studies.

You can benefit from extra support around the content of your course, live consultation hours, and by interacting with tutors via email and MS Teams.

Additionally, interactive live lectures via video conference allow you to engage with course material and ask questions in real-time, providing further opportunities for learning and support.

These resources will help make the MSc Data Science programme manageable for you, ultimately contributing to a successful and rewarding experience.

The MSc Data Science online UK programme offers flexible learning in its duration. You can choose between a 1-year full-time option or part-time studies over 1.5 or 2 years.

Graduates of our programme develop key employability skills, including:

• digital, technical, and statistical literacy

• high numeracy

• effective communication

• creative problem-solving

• critical analysis

• adaptability.

These skills prepare you for careers in data engineering, analytics, and consulting across various sectors with real world applications. 

You'll study in a virtual learning environment that uses the latest learning technology and benefit from innovative multimedia tools and study materials including:

• lecture notes

• learning videos

• revision courses

• online consultations, and

• live sessions with lecturers.

We also incorporate reports and case studies from everyday professional life into our courses.

If you find the leap to master's-level maths daunting, you can sign up for an additional support module on this course, that will ensure maths becomes a valued skill, rather than a hurdle to progress.

Our extra-curricular maths module is designed to help you overcome challenges, boost your confidence and achieve your academic goals. You won't earn any additional credits, but the skills you learn will help you confidently thrive in your course. And the best part? It's absolutely free. Once you're enrolled in your studies, you just need to enrol for the module and then you can start whenever it suits you. There's no need to submit any additional application or paperwork.