Digital4Business - an online Master's Degree in Advanced Digital Technologies

This course will equip you with essential skills in AI and machine learning, focusing on innovative applications, ethical practices and business optimisation.

You’ll dive deep into the core concepts of artificial intelligence and machine learning. Through a blend of theoretical knowledge and practical application, you will learn to design, train and evaluate advanced ML models.

Our innovative curriculum includes real-world projects, strategic AI applications, and a strong emphasis on ethical and sustainable practices. By mastering these cutting-edge technologies, you’ll be empowered to drive efficiency, enhance decision-making, and gain a competitive edge in the business landscape. Join us and become a leader in the AI-driven future.

An indicative schedule of topics to be addressed each week is outlined below:

• Introduction to AI and its history: Overview of AI, significance in today’s world, historical development, key milestones.
• Foundational Knowledge for AI: Problem-solving, search algorithms, heuristics, adversarial search, optimisation.
• Automated Planning: Goal achievement, decision-making, resource allocation, simulation, prediction, learning, adaptation, autonomous systems.
• Introduction to Machine Learning: Overview of ML, supervised/unsupervised learning, reinforcement learning, introduction to deep learning.
• Deep Learning: Neural networks, CNNs, RNNs, deep learning applications.
• Data and Datasets: Importance of data, data types, data quality, pre-processing, quality datasets.
• Reinforcement Learning: Basics of Reinforcement Learning, exploration vs. exploitation, real-world applications.
• Natural Language Processing (NLP): NLP fundamentals, text processing, NLP models and techniques.
• Computer Vision: Basics of computer vision, image processing, object detection, challenges, and future trends.
• AI Tools and Platforms: Overview of AI tools/platforms, practical applications, deep learning frameworks.
• AI and Creativity: AI in creative industries, design, innovation, future prospects, industry speaker session.
• Ethical and Social Implications in AI: Ethical challenges, societal impacts, AI bias and fairness, privacy, security.

In this AI for Business course, you will gain comprehensive knowledge and practical skills in artificial intelligence and machine learning. Through hands-on projects and strategic applications, you will be prepared to drive innovation and ethical AI practices, driven by the following learning objectives:

• Analyse, synthesise, and innovate within artificial intelligence and machine learning, emphasising critical understanding and the capability to advance the field.
• Design, train, and critically evaluate advanced machine learning models, focusing on innovative data and optimisation strategies to boost performance in business applications.
• Employ innovative techniques for rigorous machine learning model performance assessment, interpret results, and effectively communicate implications across various business contexts and to diverse stakeholders.
• Apply strategic thinking in AI and ML for complex applications, assess effectiveness critically, propose innovative solutions or improvements, and improve problem-solving and decision-making skills.
• Teamwork to develop AI solutions, enhancing collaboration skills, team competences, and service orientation towards addressing business needs.
• Critically explore AI and machine learning’s ethical, societal, and environmental impacts, and propose ethical, sustainable development and implementation practices within business environments.

AI for Business is a 10 ECTS module delivered over 5 hours per week for 12 weeks.

The fully online course employs an innovative hybrid learning approach, alternating between synchronous and asynchronous activities. Expert tutors guide you through lectures, individual study, and hands-on laboratory work. We incorporate key strategies such as problem-based learning and the flipped classroom model to enhance engagement and understanding.

Emerging technologies, including AI, are utilised to enrich your learning experience. Formative assessments provide ongoing feedback to help refine your study approach. The course is assessed through a project (50%) and a proctored written final exam (50%), ensuring a comprehensive and practical understanding of the material.

Classroom and demonstrations: 24 hours
Practical work/tutorials: 36 hours
Independent learning: 190 hours
Total: 250 hours

Credit points: 10 ECTS

The course is a 10 ECTS module delivered over 5 hours per week for 12 weeks. The course is fully online and starts Monday 19 January 2026. It will be held Mondays 16.00-19.00 (CET).

Sanjay Chakraborty is a Postdoctoral Researcher at Linköping University, Sweden, working in the Reasoning and Learning Lab within the Division of Artificial Intelligence and Integrated Systems (AIICS). His research spans machine learning, applied AI, and quantum computing, with a particular interest in how advanced computational methods can address industry-specific challenges.

Sanjay’s recent work focuses on applying AI to real-world problems such as multivariate time-series analysis and materials science. His PhD research explored how quantum computing principles can enhance machine learning algorithms, including contributions to quantum clustering using one-dimensional discrete-time quantum walks, quantum feature selection, variational quantum eigensolvers (VQE), and the Quantum Approximate Optimization Algorithm (QAOA). He also has experience in ternary quantum image representation, edge extraction, image denoising, and segmentation.

Sanjay is committed to contributing to research, innovation, and education through continuous learning and collaboration. He is particularly enthusiastic about the future of quantum machine learning and its applications across research and industry.

Explore the dynamic world of cybersecurity with this comprehensive course.

Designed to empower you with the skills to safeguard personal and organisational data, this course focuses on mastering cutting-edge cybersecurity techniques. You’ll learn to identify and assess vulnerabilities in data systems, uncovering how they can lead to security breaches.

Develop robust protection strategies to keep data safe from potential threats. Explore the critical legal and ethical dimensions of cybersecurity, preparing you to navigate the complexities of this ever-evolving field. Join us and become a vital defender in the digital era, equipped to tackle tomorrow’s cyber challenges today.

The following schedule outlines the topics covered each week:

1. Introduction to Cybersecurity
   - Overview of cybersecurity, its importance, and the growing demand for professionals
   - Understanding online identity, data, and their significance to cybercriminals.
   - Seminar on real-world cybersecurity challenges
2. Risk Management and Compliance
   - Exploring the significance of safeguarding electronic information networks and data
   - Regulatory compliance requirements for business
   - Implementing risk assessments and developing risk mitigation strategies.
   - Lab on security breach case studies
3. Network Security for Business
   - Addressing software and hardware vulnerabilities, device, network, and cloud security
   - Implementing secure network infrastructure including best practices for securing wireless networks and remote access
   - Lab on securing the application landscape, incident response planning and security incidents management
4. Cyber Attacks: Concepts and Techniques
   - Analysis of cyberattacks, identifying and classifying security vulnerabilities.
   - Understanding endpoint security challenges in business environments
   - Securing IoT devices and other connected endpoints in business networks
   - Seminar on vulnerabilities and real-world use cases
5. Data and Privacy Protection
   - Best practices for protecting computer devices, wireless networks, and online accounts
   - Implementing cryptographic methods for business data
   - Exploration of ethical implications and considerations in using AI and cryptography for data privacy protection
   - Practical exercises on implementing cryptographic techniques for privacy-preserving data sharing and analysis
   - Lab on data encryption and backup strategies
6. Organisational protection and cloud security for business
   - Techniques for firewall configuration, port scanning, and certificate updates.
   - Securing cloud services and data storage in public, private, and hybrid cloud environments
   - Identity and access management in the cloud
   - Data backup and disaster recovery planning for cloud-based systems
   - Lab on using tools for security monitoring
7. Cyberattack Detection and Cyberdefense
   - Real-time attack detection, best security practices, and understanding botnets and the kill chain
   - Lab on behaviour-based security
8. Tools for incident prevention and detection
   - Overview of CSIRT, security playbooks, IDS, and IPS
9. Cybersecurity Legal Issues
   - Personal legal issues. Corporate Legal Issues.
   - International Law and Cybersecurity.
10. Ethical Issues in Cybersecurity
    - Overview of cybersecurity laws, regulations, and industry standards applicable to businesses.
    - Understanding ethical considerations in cybersecurity decision-making.
    - Addressing legal and ethical challenges related to incident response, data breaches, and privacy violations.
    - Discussion on ethical considerations and the role of professional organisations in cybersecurity ethics.
11. Cyberwarfare
    - Understanding cyberwarfare, its objectives, and impacts.
12. Emerging Topics and Careers in Cybersecurity
    - Exploration of AI in cyberattacks and defence, the geopolitical aspects of cyberspace, and blockchain technology.

This course teaches students to identify and address cybersecurity vulnerabilities, develop protection strategies, and understand the legal and ethical aspects of protecting personal and organisational data. Here’s what you’ll achieve:

• Analyse and critically evaluate vulnerabilities in personal and organisational data systems to identify potential security breaches and suggest mitigative strategies, fostering analytical thinking and attention to detail.
• Synthesise and apply advanced concepts and techniques of cyber-attacks to simulate potential security breaches, demonstrating a comprehensive understanding of cyber threat landscapes and training problem-solving abilities and decision-making skills.
• Design and implement robust strategies for the protection of personal and organisational data, utilising encryption techniques and security protocols to mitigate potential threats.
• Evaluate and integrate tools and methodologies for the prevention and detection of cyber-attack incidents, developing critical thinking skills and demonstrating an ability to anticipate and counteract emerging cyber threats.

Our fully online course employs an innovative teaching methodology that blends hybrid learning with expert tutorship. This approach alternates between live lectures, self-paced study, and hands-on lab sessions. Expert tutors not only teach the content but also guide students through their learning journey.

Key strategies include problem-based learning, gamification and the flipped classroom, all enhanced by emerging technologies like artificial intelligence, which keep students engaged and enrich the learning experience.

Assessments are ongoing and final, including exams, assignments, and projects. A significant project (50%) applies cybersecurity to real business problems, while a final test (50%) ensures a comprehensive understanding of the material.

Classroom and demonstrations: 36 hours
Practical work/tutorials: 24 hours
Independent learning: 190 hours
Total: 250 hours
Credit points: 10 ECTS

Cybersecurity for Business is a 10 ECTS course with 5 hours per week, over 12 weeks. The course is fully online and start 20 January 2026. It will be held Tuesdays 16.00-19.00 (CET).

Gurjot Singh is a cybersecurity researcher at Linköping University with a PhD and over a decade of teaching experience. Passionate about cybersecurity, he co-developed this 10 ECTS course with Associate Professor Mikael Asplund. It enables students to assess and mitigate cyber risks, analyse security vulnerabilities, and navigate the legal, ethical, and strategic dimensions of cybersecurity in business.