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Course overview
Kickstart your career in the exciting and fast-moving field of data science with our online BSc (Hons) Data Science programme. This undergraduate degree has been designed by data science experts to equip you with the theoretical expertise and practical skills that are currently in high demand across several industries.
By studying this flexible, online degree course, you’ll develop specialist analytical and problem-solving skills, that can quickly be applied in real-world situations. As the world continues to progress towards increased digitalisation, our BSc (Hons) Data Science programme can open a host of exciting new career paths worldwide.
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This program is subject to validation*
Job outcomes
- Data scientist
- Data engineer or analyst
- Business intelligence analyst
What you'll learn
When you enrol in a BSc (Hons) Data Science degree programme with us, you will learn the fundamentals of data science, including data wrangling and programming with Python. You’ll also gain practical skills and knowledge in analysing trends, identifying patterns, and making data-driven decisions that can increase profits for organisations worldwide. These skills will prepare you for work as a data analyst, data scientist, or any other role that requires expertise in data science.
Study method
- Online
- Blended
- In-class
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Duration study load
36 months (full-time), 48 months (part-time option 1) and 72 months (part-time option 2)
Entry requirements
- 2 subjects at A-Level or equivalent. GCSE Maths and English Grade C (4) or above. Work experience considered.
- English language: IELTS Level 6 or above with no element below 5.5 (or equivalent).
Pathways
- MSc Data Science
Course features
- Flexible online learning: Fit learning around your life but study in a structured way, using a flexible online approach with full support from your lecturers and tutors. Learn part-time or full-time – at your own pace, fully online, anywhere.
- Over 140 years of expertise: Upgrade your expertise with the skills of the future. To help you succeed and progress your career, we’re combining our long history of education in finance, business, and technology with an up-to-the-minute online learning platform.
- Innovative personalised learning: Learn on your own terms. Gain the skills you need to reach your full potential and achieve your ambitions. You’ll have support, as well as access to advanced digital learning tools and practical real-life expertise.
- Rewarding your ambition: Distance learning is an affordable, tailored option that fits your lifestyle. Fees for our online degree are spread over the length of your chosen programme, making it easier for you to manage your finances.
Testimonials
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Alexandru D"In my opinion, LIBF is a great institution for pursuing an undergraduate degree online. Its flexibility fits perfectly with my work schedule, allowing me to fully utilise my off-days for studying. Overall, I am absolutely pleased with my experience."
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Muhammed Saif U"Studying with LIBF has been amazing. The website and course modules are easy to navigate, and I feel fully supported. The flexibility makes it easy for me to combine studies and work."
Subjects
Introduction to data science
- Learn how to integrate and use data-driven approaches in business to make effective operational decisions and create value from data. Gain insight into statistics and machine learning, including an overview of relevant methods and approaches.
Introduction to programming with Python
- Develop a foundational understanding of the Python programming language. Learn about Python’s role in data science-related programming and programming concepts like variables, data types, and statements.
Mathematics: analysis
- Learn the fundamentals of differential and integral calculus and understand their related concepts. This module builds skills to formulate and solve various science and technology-related problems.
Statistics – probability and descriptive statistics
- Learn the essentials of probability and descriptive statistics. Explore random variables, probability density distributions and key statistical concepts. Understand inequalities and limit theorems.
Object-oriented and functional programming with Python
- Build upon your knowledge of Python programming to understand advanced concepts, functions, and object-oriented programming notions like classes, objects, and design principles.
Data quality and data wrangling
- Explore techniques for acquiring, formatting, and tidying data to make it suitable for subsequent analysis to unlock business value. Learn about data quality and key methods for data quality management.
Mathematics: linear algebra
- Numerous scientific and engineering challenges can be solved with linear algebra. This module introduces the subject and basic notions like vectors and matrices. Learn about solutions for problems in analytical geometry and develop problem-solving skills.
Statistics – inferential statistics
- An introduction to statistical analysis and Bayesian techniques. Learn to estimate and optimise parameters. Understand statistical and systematic uncertainties, statistical testing, and decision theory.
Introduction to academic work
- The application of good scientific practice is an academic fundamental. Develop the skills required to write strong scientific papers and get an overview of different examination formats and requirements.
Database modelling and database systems
- Develop knowledge of relational database systems, data schemas and modern DB systems (NoSQL) for storing and accessing data. Learn how to store data in relational data models and access stored data with SQL.
Explorative data analysis and visualisation
- This module introduces useful approaches, tools, and techniques to explore data sets. Examine detailed visualisation principles and techniques to develop skills and present analytical outcomes.
Data science software engineering
- This module gives a detailed overview of data science methods and paradigms to develop enterprise-grade models and bring them into production. This module explores traditional and agile project management techniques and software development paradigms, including pair, mob, and extreme programming.
Machine learning – supervised learning
- Develop knowledge of large-margin classifier concepts and tree-structured models. Gain an understanding of machine learning, with a focus on supervised learning, like labelled data.
Machine learning – unsupervised learning and feature engineering
- This module provides tools and techniques for unsupervised learning, like machine learning approaches, and feature engineering. Learn relevant methods to find robust and meaningful features.
Elective A (see “Electives A” section below)
Elective A (see “Electives A” section below)
Neural nets and deep learning
- Learn how feed-forward networks are set up and trained, and how to avoid overtraining. This module also covers common network architectures and highlights design choices and data collection impacts.
Seminar: ethical considerations in data science
- This module explores ethical issues in relation to data science methodologies and techniques which are an everyday part of contemporary life. Develop skills, knowledge and understand how to practice ethical data science.
Elective B (see Electives B section below)
Elective B (see Electives B section below)
Elective C (see Electives C section below)
Elective C (see Electives C section below)
Undergraduate (bachelor) thesis
- Apply the subject-specific and methodological competencies learned throughout your course to present an academic dissertation. You’ll also learn how to tackle a practical-empirical or theoretical-scientific problem.
Project: from model to production
- Gain hands-on experience with integrating predictive models into enterprise-grade applications or services. In this project-based module, consider aspects like data storage, processing, and service availability.
Project: build a data mart in SQL
- In this module, apply database theoretical knowledge, methods, and approaches to solve a real-world scenario. In this case study, implement your design and architectural choices in a functioning database.
Agile project management
- Gain a practical introduction to agile project management and learn to distinguish it from a plan-driven approach. Learn the values, activities, and roles of typical agile procedures and practice with an example project.
Business intelligence and data analytics
- Business intelligence
This module introduces the procedures and models for data provision, information generation and analysis. Build skills in data warehousing and develop techniques to optimise business activities. - Project: business intelligence
In this module, develop your business intelligence (BI) knowledge. Use well-known BI techniques to design and prototype BI applications based on specific requirements.
Sales and marketing
- Applied sales I
Globalised demand and intense competition mean that winning customers is increasingly difficult. So, effective sales thinking is vital. Examine key concepts like sales organisation and alternative channels – plus, fine-tune your negotiation skills. - Applied sales II
Deepen your knowledge of fundamental sales principles. Explore how customer satisfaction and loyalty contribute to successful sales management and apply your skills in a real-world case study.
Supply chain management and industry 4.0
- Supply chain management I
Gain a theoretical and practical view of supply chain management (SCM). You’ll consider logistical and modern processes, flows and network standards for SCM. - Supply chain management II
Learn how to build and maintain a competitive advantage through robust SCM. Analyse strategic activities and instruments in the Plan, Source, Make, Deliver, and Return process categories.
Data engineering and big data technologies
- Big data technologies
This module introduces the four ‘Vs’ of data – and data sources and types. Learn about the most common data storage formats and the challenges large amounts of data pose for the underlying infrastructure. - Cloud computing
An introduction to cloud computing, its enabling technologies, and analytics capabilities. Learn about cutting-edge advances like serverless computing, storage, and popular cloud offerings.
Artificial Intelligence
- Artificial Intelligence
Artificial intelligence has captured our attention for decades. Explore the successes and setbacks of AI over the years, learn about modern systems and find out how you can be a part of AI’s rapid development. - Project: Artificial Intelligence
Take on the challenge of designing and developing your own AI system. You’ll consider the application requirements, practical constraints and desired output as you put your knowledge into practice.
Banking and Finance
- Crypto and blockchain
This module considers the growth of crypto and blockchain, the evolution of money, from coins to fiat currencies, plastic, and crypto assets. You’ll develop an understanding of the current state of the market and its principles. - Fintech
There has been a huge increase in the number of technological finance solutions in recent years. Uncover the main sectors targeted by Fintech companies. Learn about the current state of the market, technological solutions, and its future direction.
Internship
- Internship I (*)
Develop your practical and analytical skills by doing an internship and improving your employability. In several preparation tutorials, you’ll consider the working environment and the overall goal of your placement. - Internship II (*)
As with the first internship, this is an opportunity to apply your skills and knowledge in an entrepreneurial environment. Develop your communication style, problem-solving ability and time management.
* Check eligibility before booking the module.
Business intelligence and data analytics
- Advanced data analysis
Get up to speed with the many analytics platforms widely used in business today. This module looks at everything from measuring business performance to text mining, from social media analytics to the current trends in experimental design and setup. - Project: data analysis
It’s time to put your data analysis techniques and knowledge to the test in the real world. Develop a report as you apply advanced data analysis to simulate work in a professional data science environment.
Sales and marketing
- Online Marketing
Examine different types of online marketing such as advertising campaigns and email marketing. You’ll compare channels, consider legal aspects like GDPR and evaluate campaigns with web analytics. - Social media marketing
Social media has evolved from a private means of communication to a commercial advertising tool. Explore how to integrate channels like Facebook, Instagram and Pinterest into a company’s marketing mix.
Supply chain management and industry 4.0
- Product development in Industry 4.0
In the context of the fourth industrial revolution, you’ll look at the impact of new trends on product development. Consider how alternative approaches to design put the consumer at the centre. - Project: smart product solutions
In a practical project framework, showcase how you’ve applied agile engineering methods to smart product solutions. And demonstrate you can choose the right tools to analyse different business models.
Data engineering and big data technologies
- Data Engineering
Explore the important foundational concepts in data engineering: storage infrastructure, data security, systems architecture, developments in storage technology, and the logic of data pipelines. - Project: data engineering
Create your own portfolio by working on a real data engineering project. Perhaps you’ll want to set up a Docker container environment. Or how about building a data pipeline according to DataOps principles? The choice is yours.
Artificial intelligence
- Self-driving vehicles
Focus on the safety standards and IT security of autonomous vehicles. There’s a lot to explore – sensor fusion, feature detection, calibration, localisation, satellite-based systems, and motion planning are just a few areas to get you started. - Seminar: current topics and trends in self-driving technology
Uncover the most recent developments of autonomous vehicles. Discover the technical advances, and philosophical issues, and how they’ll affect law, society and many industries. You’ll then apply your new knowledge in a research essay.
Once enrolled, you will be expected to meet LIBF’s policies and standards.
About LIBF
We are LIBF – a professional body that has been providing industry-leading education for more than 140 years.
Throughout our history, we’ve been helping people build successful careers in business, finance and technology – working to make the industry accessible to all.
Our focus is on life-long learning. We equip our students with real-world skills and globally recognised qualifications that allow them to achieve their career ambitions. This emphasis on practical skills means our students can quickly apply the knowledge gained in our courses in their working lives.
Our engaging webinars offer a unique opportunity to delve into the distinct benefits of online learning with us, crafted to ignite your ambitions.
Why join a webinar?
- Obtain a thorough understanding of our online learning methodology directly from our Study Advisors.
- Receive a step-by-step guide on the application process, funding options, entry requirements, and more.
- Get instant answers and personalized advice from our Study Advisors to navigate your online learning pathway.
Register for a webinar that fits your schedule. Let’s begin this educational journey together, unlocking your potential and beyond. All webinars are conducted on Zoom and commence at 6.00 pm UK time.
The LIBF faculty itself is comprised of business, banking, finance and technology experts with extensive experience in the industry. We embrace innovation in education and our courses are flexible and delivered through a variety of media, to provide a rich learning experience.