Packt

Generative AI for Marketing: Advanced & Responsible

Packt

Generative AI for Marketing: Advanced & Responsible

Access provided by Special Competitive Studies Project

Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Apply zero-shot and few-shot learning to generate targeted marketing content

  • Implement retrieval-augmented generation for micro-targeted customer engagement

  • Evaluate ethical considerations and governance frameworks in AI-driven marketing

Details to know

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Assessments

5 assignments

Taught in English
Recently updated!

June 2026

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This course is part of the Machine Learning and Generative AI for Marketing Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 5 modules in this course

This module explores advanced techniques in AI-driven content creation, including zero-shot learning, generative adversarial networks, and long short-term memory networks. Learners will discover how these models enhance data augmentation, semantic understanding, and personalized content generation across various domains. Practical examples, such as generating product descriptions, illustrate the real-world impact of these technologies.

What's included

1 video8 readings1 assignment

This module explores how few-shot learning and transfer learning can be leveraged to enhance brand presence through data-efficient marketing strategies. Learners will discover practical frameworks for implementing these AI techniques, analyze their challenges, and apply them to real-world marketing scenarios such as email campaigns and image classification. The module also covers the use of API services and iterative refinement based on campaign metrics.

What's included

1 video10 readings1 assignment

This module explores how retrieval-augmented generation (RAG) can be leveraged for precision marketing, focusing on the importance of data specificity and real-time content personalization. Learners will gain hands-on experience integrating Elasticsearch and LangChain with large language models to deliver targeted marketing messages. Practical applications, such as optimizing product discounts based on user behavior, are also covered.

What's included

1 video6 readings1 assignment

This module explores the latest advancements in artificial intelligence and machine learning as they transform marketing strategies. Learners will discover how diffusion models, multi-modal architectures, and immersive technologies like AR and VR are shaping the future of digital marketing. By the end, you'll understand both the technical foundations and practical applications of these emerging tools.

What's included

1 video4 readings1 assignment

This module explores the ethical challenges and governance strategies associated with AI-driven marketing, including bias mitigation, privacy protection, and policy development. Learners will gain practical insights into ensuring fairness, transparency, and responsible AI use in marketing campaigns.

What's included

1 video5 readings1 assignment

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Instructor

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Packt
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