ELE 3807 AI in Marketing
ELE 3807 AI in Marketing
In a digital age, artificial intelligence (AI) offers marketers unique opportunities to understand and engage customers in new and more effective ways. By using AI, marketers can create customized customer experiences, strengthen the basis for decisions in campaigns and analysis, as well as automate and streamline processes that previously required a lot of manual work. The course aims to provide practical insight into how AI can be used as a strategic tool to increase the effect and value of marketing work.
After completing the course, students must:
- have knowledge of how artificial intelligence and machine learning are used in marketing.
- know key AI tools and methods used for data analysis, segmentation, personalization, customer communication and decision support in marketing.
- have insight into ethical and legal challenges related to AI use in marketing, including privacy and responsible AI use.
After completing the course, students should be able to:
- apply artificial intelligence and machine learning in marketing efforts by using AI-driven techniques for data analysis, customer segmentation and personalization of marketing efforts.
- use and evaluate central AI tools for automated customer communication, content production and decision support, as well as adjust their use based on analytical results.
- identify and handle ethical and legal issues related to AI in marketing, including assessment of privacy, GDPR and responsible use of AI technologies.
After completing the course, students should be able to:
- be able to convey and discuss how AI affects marketing strategies and decision-making processes, both in writing and orally, as well as reflect critically on the role of technology in society.
- know innovation processes related to AI and how the technology can be used to create new marketing opportunities and competitive advantages.
- Basic concepts: what AI is and how machine learning works. Provide an overview of common AI tools used in marketing.
- Customer insights and segmentation: how marketers can use AI to analyze customer data and identify patterns based on behavior, preferences and demographics.
- Automated customer communication: how AI can be used to personalize the customer journey and handle customer questions, support and sales in real time, as well as how they are integrated into a customer strategy.
- AI in content production: how AI can be used to generate content and optimize advertising to the right audiences at the right time, improving the effectiveness of marketing efforts.
- AI in analytics and decision support: how AI tools can analyze the results of marketing campaigns in real time, giving marketers insight into what works and what doesn't.
- Ethics and privacy: how businesses need to balance personalization with privacy requirements and GDPR when using AI to collect and analyze data.
This course is a 100% digital online course where all teaching material is completed in advance and is published weekly on the learning platform ITs Learning. The course is designed to give students the flexibility to learn at their own pace, while also facilitating reflection and active participation.
The learning activities include:
• Video lectures and podcasts that introduce and deepen key topics within AI in marketing.
• Interactive learning resources such as demonstrations of AI tools, case studies and digital simulations.
• Weekly reflection tasks where students apply theory in practice and develop a critical understanding of AI in marketing.
• Discussion forum where students share experiences, discuss issues and reflect on academic topics.
• Digital tasks and quizzes to test understanding and application of the course content.
Computer tools
The course uses various computer tools and AI platforms to give students practical experience with artificial intelligence in marketing.
For valgkurs tilbys normal kontinuasjonseksamen ved neste gjennomføring av kurset. Dersom et valgkurs utgår eller ikke blir satt i gang i det semesteret det tilbys, vil det bli tilbudt kontinuasjonseksamen i kursets normalsemester.
Higher Education Entrance Qualification
Disclaimer
Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.
There are no special requirements for prior knowledge.
| Assessments |
|---|
Exam category: Submission Form of assessment: Submission PDF Exam/hand-in semester: First Semester Weight: 100 Grouping: Individual Duration: 72 Hour(s) Exam code: ELE 38071 Grading scale: ECTS Resit: Examination when next scheduled course |
| Activity | Duration | Comment |
|---|---|---|
Digital resources
| 40 Hour(s) | |
Prepare for teaching | 80 Hour(s) | |
Group work / Assignments | 40 Hour(s) | |
Student's own work with learning resources | 40 Hour(s) |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.
