AI and Machine Learning for Marketers (Virtual Classroom)Institute of Data & Marketing
AI and Machine Learning for Marketers (Virtual Classroom)
In conjunction with IDM's strategic partner Southampton Data Science Academy (SDSA) learn how to leverage leading-edge technologies for your organisation. Gain the specialist knowledge and skills needed to harness the power of Artificial Intelligence (AI), including the use of machine learning tools for marketing.
Suitability - Who should attend?
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 6 weeks
You will be assessed on 3 separate assignments. The first two are short. Your tutor will provide feedback on each of these at the end of week 6.
You will need to invest approximately 50 hours of study time in total (around 8 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.
Outcome / Qualification etc.
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
Training Course Content
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, 2 free untutored marketing modules have been devised in collaboration with IDM to provide marketers with an in-depth understanding of how to implement machine learning to enhance processes and boost efficiency.
Both ‘Machine learning’ and ‘Application of machine learning in marketing’ can be studied in conjunction with your other modules, to further supplement those lessons.
Alternatively, you can study both the untutored marketing modules at the end of week 6, if preferred.
Additional module: Machine learning
- Definitions of data science
- What is machine learning?
- Different types of machine learning methods and models for marketers
- Decision trees
- Cluster analysis
- How machine learning can be applied to website data
- How to choose training data and evaluate the effectiveness of machine learning
Additional module: Application of machine learning in marketing
- Using machine learning for attention, persuasion and retention
- Your strategic role in applying machine learning to your work
- Limitations of Artificial Intelligence (AI) and ethical considerations
Course delivery details
Why choose Institute of Data & Marketing
Over 30 years experience as a leading awarding body for qualifications in data & digital marketing
Over 100,000 people have attended our courses
Over 15,000 marketers have earned a professional certification with us
£1500 + VAT
Institute of Data and Marketing
IDM is the trusted training partner for hundreds of leading brands, from over 30 countries. For more than 30 years they’ve trained over 100,000 delegates, helping them improve their marketing performance, from their first steps on the career ladder to...
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