• You will learn to
  • Details
  • Course availability

You will learn to:

  • Understand the capabilities and limitations of AI, along with the opportunities it could create
  • Navigate discussions around the ethical, moral, and legal implications of AI technology
  • Describe the various components required in the delivery of AI systems
  • Identify data types and applications for the delivery of such systems
  • Identify software that can enable further insights by processing, analysing, and drawing meaning from natural language, images, and numerical data

See below for further course details and full programme information.

Ready to upskill your team with the IDM? Explore our Corporate Training option, here



Get in touch...

To discuss your options, please get in touch with one of our learning and development team:

Course availability

Start Study Mode Location Member Non-Member Exam Fee  
01/08/22 Online Online £1,500.00 £1,500.00 - More info
Book Until
18 Jul 22

NB: Prices above subject to VAT

Qualification Information

During your course, you will study a total of 6 core modules. These will be taught on a week-by-week basis:

Week 1: Introduction to AI

  • What AI is and its main classes of applications and capabilities
  • The differences between different types of AI technologies
  • Core technologies associated with AI
  • The relationship between AI and other technology trends such as big data, cloud computing, and the Internet of Things (IoT)
  • The role of data in AI
  • The challenges in applying AI within organisations
  • The limitations of AI

Week 2: Case study - Learning to know your customers

  • The difference between supervised and unsupervised machine-learning algorithms
  • Fundamental classes of machine-learning, including regression, classification and clustering
  • Types of business problems machine-learning can solve and machine-learning tasks that can be used to solve them
  • Activities and technologies used to build a Natural Language Processing (NLP) pipeline
  • Statistical processing and work distributions
  • Applying regression, classification, and clustering to extract information and recommend items to purchase
  • Analysis, assessment and interpretation of the results of machine-learning models

Week 3: Case study - Enhancing the customer experience

  • The Turing test and how it can be used to improve AI systems
  • Important methods and technologies in natural language generation
  • Deep-learning approaches to NLP and what they're used for
  • Important methods and tools in natural language understanding and speech recognition
  • Designing conversational agents (i.e. chatbots)

Week 4: Case study - Search and recommendation

  • Clustering algorithms
  • Topic modelling
  • Knowledge bases: How are they built? What purpose do they serve?
  • Using a knowledge base for Named Entity Recognition (NER)
  • Introduction to the semantic web
  • Using the knowledge base to extract relevant information (i.e. SPARQL and Google Knowledge Graph)

Week 5: Case study - Computer vision

  • Traditional approaches to image-processing and computer vision
  • Image classification and clustering
  • Feature extraction
  • Convolutional neural networks (CNNs)
  • Combining CNNs with conversational agents to generate textual descriptions
  • Systems for automatic surveillance

Week 6: Future directions for AI

  • Current limitations
  • Technological advances
  • Societal and cultural shifts
  • Ethical, moral and legal issues

In addition, 4 free untutored marketing modules have been devised in collaboration with IDM to provide marketers with further examples of how to apply machine learning for attention, persuasion and retention.

These can be studied in parallel with your other modules or after the first 6 weeks.

Additional modules

  • AI for Attention
  • AI for Persuasion
  • AI for Retention
  • Mini case study - remarketing and direct mail

This programme is specially built to offer working professionals the flexibility they need to study around demanding schedules.

At the same time, Southampton Data Science Academy's commitment to providing tutor-led courses ensures that you still receive the hands-on support needed to make the most out of your studies.

  • Study part-time and entirely online
  • Engage in group sessions and forum discussions
  • Network with peers in the marketing profession
  • Earn your qualification in 10 weeks

You will be assessed on 3 separate assignments. The first two are short. Your tutor will provide feedback on each of these.

You will need to invest approximately 40 hours of study time in total (around 4 hours a week) for the course, including the assignments and additional modules.

After successfully completing the course, you'll receive a downloadable electronic certificate from IDM and the Southampton Data Science Academy as proof of your qualification.

The IDM have joined forces with the Southampton Data Science Academy - led by Dame Wendy Hall, UK AI Skills Champion - to professionalise AI in the marketing sector and develop this unique programme for marketers.

This 10-week, online course is designed for professionals who are keen to understand and implement AI in their organisation. By cutting out jargon and focusing on practical solutions to actual business needs, the programme equips marketers with knowledge that can be directly translated to their workplace.

By following a problem-based learning approach, you will master a framework of core AI capabilities - examining each within the context of a business case study. You'll learn about machine learning and its uses, as well as how big data applies to your business problems.

Through your studies, you will understand how to identify what data needs to be collected to ensure your digital marketing process remains optimised. You'll be taught how to interpret your customers' interactions with your digital marketing efforts, helping you become a more effective digital marketer.

Dr Manuel León Urrutia, University of Southampton

Dr Manuel León Urrutia is Lecturer of Computer Science at the University of Southampton, based in the Web and Internet Science research group of the Electronics and Computer Science department.

Manuel holds an MSc & PhD in Web Science and an MA in Applied Linguistics. He also possesses significant experience in data science, learning technologies and online learning design.

As Head of Learning for the Academy, he will lead a team of tutors who will deliver online sessions, answer questions, and provide you with feedback at the end of the course.

Get in touch...

To discuss your options, please get in touch with one of our learning and development team:

Privacy Notice:

To learn how we look after your data please see our privacy notice.

Contact Us