Online degree BSc (Hons) Artificial Intelligence

• Introduction to artificial intelligence
  Dive into the exciting world of Artificial Intelligence (AI). You'll explore its history, gain insights into different AI frameworks, and get a handle on core technologies like reinforcement learning, natural language processing, and automated vision.

• 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 advanced 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.

• Collaborative work
  Build key interdisciplinary competency to develop connections and navigate networking opportunities. Learn about:

  • collaborative learning and working practices

  • constructive cooperation with others

  • creative thinking

  • empathy

  • emotional intelligence.

• Fundamentals of data protection and cyber security
  Develop a thorough knowledge of theoretical foundations, essential practices for securing networks, and the principles of incorporating security during software development. You'll also get to differentiate various user verification and identity validation mechanisms.

• 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 for IT and technology

  Develop an understanding of scientific thinking and academic work, with a focus on how to apply theories, methods, and models related to IT, and how to produce independent academic papers by analysing and classifying different sources of literature.

• Object oriented and functional programming in Python

  Build upon your knowledge of Python programming to understand advanced concepts, functions, and object-oriented programming notions like classes, objects, and design principles.

• 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.

• Introduction to NLP

  Develop your knowledge of NLP techniques while addressing relevant challenges, using common algorithms, and assessing different use-case scenarios.

• Project: AI excellence with creative prompting techniques

  Immerse yourself in generative AI as you explore and apply prompting techniques. Create AI-generated content and assess the effectiveness of your prompts. Refine those skills in real-world scenarios while considering the ethics of the design and use of AI for basic prompting techniques.

• 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.

• Intercultural and ethical decision-making
  Gain the skills to understand intercultural competencies, diversity, and ethics development. Plan and implement learning processes in these areas by creating a case study.

• Project: edge AI
  Whether it's for vehicles, mobile systems, or cyberphysical systems, you'll learn to assess requirements, make design choices, and check the performance of your AI system. You'll create a prototype of your Edge AI solution, reporting on your design and implementation choices, requirements and constraints.

• 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.

• User experience
  Get a solid understanding of the field of user experience by defining terms and concepts, charting customer journeys, designing personas, and applying suitable techniques for UX design.

• Introduction to robotics
  Embark on a journey through the ever-evolving field of robotics and how they are used in real applications. Critically analyse key developments, understand the mechanical structure of robots, and dive into specific characteristics and challenges of industrial and mobile robots.

• Introduction to computer vision
  Learn the foundational elements of computer vision, how to apply deep learning methods to high-level vision tasks and how to handle video processing effectively. Understand image acquisition from human and technical perspectives and the role of filtering in image processing.

• Self-arranged internship I (*)

  Gain practical and analytical skills by securing and completing an internship, enhancing your employability. In preparation tutorials, explore workplace dynamics and set personal goals for your placement.

• Self-arranged internship II (*)

  Building on your first experience, this self-arranged internship lets you apply academic skills in a real-world entrepreneurial setting. Focus on refining your communication, problem-solving, and time management skills.

*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.

Data analysis and business intelligence

• 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.

IT operations and project management

• IT service management
  Learn about the IT services that keep IT systems running. This module builds knowledge and expertise to provide IT services to organisations, mainly based on the IT Infrastructure Library (ITIL).

• Project: IT service management
  Take the opportunity to analyse and evaluate certain aspects of IT service management within a project framework. You can apply the theory you have learnt to propose practical solutions to company-specific situations.

International marketing and sales

• International marketing
  Learn about strategic marketing in an international context including cultural differences and how they influence international marketing management. Gain insight into:

  • international market research

  • strategic planning

  • and the ethics of international 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.

Supply chain management and industry 4.0

• Supply chain management I
  Gain a theoretical and a 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.

Cloud programming and computing and data engineering

• Cloud programming
  Make your mark in the cloud. As you plan, create, test, and document a scalable cloud service, you'll get to delve into how a cloud system's elements are formed and measured. This module also guides you to assess the risks, protective measures, and responsive actions of a cloud service and explore its various use dimensions.

• 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.

Production engineering, automation and robotics and autonomous driving

• Production engineering
  Understand the impacts of additive manufacturing and cyber-physical systems and classify manufacturing processes according to DIN 8580. Dive into rapid prototyping, tooling, and direct manufacturing applications along with exploring the elements and properties of cyber-physical production plants.

• Automation and robotics
  Unleash your potential in automation and robotics with an in-depth exploration of automation, measurement control, robot kinematics, and regulation technology. Learn to decipher measurement signals, the role of Boolean algebra in control technology and choose optimal sensors for automation and robotics applications.

Data analysis and business intelligence

• 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
  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.

IT operations and project management

• IT project management
  This module provides fundamental IT project management concepts. Learn about project management and organisation, develop cost-management skills, and solve IT project management problems.

• IT architecture management
  This module defines a future blueprint for particular IT developments, including service strategies and available technologies for IT service providers.

International marketing and sales

• 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

• 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.

Cloud programming and computing and data engineering

• 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.

Production engineering, automation and robotics and autonomous driving

• 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, philosophical issues, and how it’ll affect law, society and many industries. You’ll then apply your new knowledge in a research essay.

You can find more details about your BSc (Hons) Artificial Intelligence course in these PDF files:

• Online programme schedule: BSc (Hons) Artificial Intelligence

• Programme specification: BSc (Hons) Artificial Intelligence

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

• LIBF has Taught Degree Awarding Powers (TDAP).

In today's increasingly digital world, the demand for AI skills continues to grow. As AI transforms all industries, completing an online BSc Artificial Intelligence degree puts you at the forefront of a rapidly growing and evolving field.

Careers in AI also typically offer competitive salaries. So, studying AI is an investment in a future where you can make a significant impact - personally, professionally, and in society.

You’ll study your AI degree 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 up to date reports and case studies from industry into our courses.

Absolutely, an AI degree is increasingly valuable in today's tech-centric world. With industries rapidly adopting artificial intelligence across various sectors such as healthcare, finance, and cybersecurity, the demand for AI professionals is at an all-time high. An AI degree equips you with critical skills in machine learning, data analysis, and algorithm development, making you a competitive candidate in a lucrative job market. Additionally, the potential for innovation and entrepreneurial ventures in AI is immense, offering you numerous pathways for career advancement and personal growth.

An AI degree opens the door to a multitude of career opportunities. Graduates can pursue roles such as AI researchers, machine learning engineers, data scientists, and robotics engineers. In addition, there are positions in natural language processing, computer vision, and autonomous systems. Beyond technical roles, you can also apply AI expertise in consultancy, project management, and ethical AI governance. These diverse opportunities span industries like healthcare, finance, automotive, and retail, providing a dynamic and ever-evolving career landscape.

The scope of an AI degree is vast and ever-expanding. It encompasses foundational principles in computer science and mathematics, as well as specialised topics like neural networks, deep learning, and natural language processing. Beyond technical proficiency, an AI degree often includes ethical considerations, real-world applications, and interdisciplinary collaboration. This holistic approach ensures that graduates are not only technically proficient but also capable of addressing complex challenges and innovating new solutions. The broad applicability of AI skills means that you can influence various fields, from improving medical diagnostics to enhancing consumer experiences in retail.