Generative AI in Marketing

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Generative AI in Marketing

COURSE OVERVIEW

The Generative AI in Marketing course helps learners understand how AI is transforming digital marketing, content creation, customer engagement, campaign planning, and brand growth. Today, marketers need faster content production, better audience insights, stronger personalization, and smarter campaign decisions. Therefore, practical GenAI skills are becoming important for future-ready marketing roles.

Through this course, learners explore how Generative AI can support ad copywriting, blog creation, social media content, customer segmentation, campaign optimization, SEO, trend analysis, and brand communication. In addition, the course connects AI concepts with real marketing use cases.

Moreover, learners understand both the opportunities and ethical responsibilities of using AI in marketing. As a result, participants become better prepared to create smarter campaigns, engage audiences better, and use AI responsibly for business growth.

WHAT YOU'LL LEARN

By completing this Generative AI in Marketing course, learners will understand how AI can improve content creation, customer engagement, campaign planning, and marketing performance.

Use Generative AI tools to create ad copies, visuals, blogs, and social media content
Apply AI for audience segmentation and personalized engagement at scale
Use AI for predictive analytics, SEO, and campaign optimization
Understand ethical boundaries in AI-powered marketing
Build practical GenAI skills for brand communication and growth strategy

Overall, this course helps learners create smarter, engage better, and redefine marketing with Generative AI.

Create Smarter, Engage Better - Redefine Marketing with Generative AI.

CURRICULUM

The Generative AI in Marketing curriculum is divided into nine practical learning sections. Each section helps learners understand how Generative AI, digital marketing, customer insights, content creation, and campaign strategy work together.

In addition, the course begins with GenAI fundamentals and gradually moves toward content marketing, customer engagement, SEO, campaign optimization, analytics, and responsible AI marketing. As a result, learners build both conceptual clarity and practical marketing-focused AI skills.

Module 1: Introduction to Generative AI and Its Evolution

Topics Covered:

This section introduces Generative AI and explains why it has become important across industries. It also helps learners understand the history, limitations, and ethical concerns connected with AI adoption.

Meaning of Generative AI
History and milestones in AI development
Traditional AI versus Generative AI
Key drivers such as big data, compute power, and neural networks
Real-world applications of GenAI
Limitations and ethical considerations

As a result, learners build a strong foundation before moving into advanced AI applications in marketing, branding, and growth strategy.

Module 2: Fundamentals of Large Language Models (LLMs)

Topics Covered

Large Language Models are central to many modern GenAI applications. Therefore, this section explains how models such as GPT, BERT, T5, and PaLM work behind the scenes.

Transformers and attention mechanism
GPT, BERT, T5, and PaLM comparisons
Training versus inference
Prompt engineering basics
Zero-shot, few-shot, and fine-tuning approaches
Responsible use of LLMs

In addition, learners understand how LLMs can be used responsibly in marketing content, campaign planning, customer communication, and brand messaging.

Module 3: Generative AI Tools and Platforms

Topics Covered

This section introduces popular AI tools and platforms used across professional domains. Instead of focusing only on theory, learners understand how different tools support marketing, creativity, productivity, and business growth.

ChatGPT, Claude, Bing AI, and GitHub Copilot
Image generation tools such as DALL·E, Midjourney, and Stable Diffusion
AI tools for video, music, and voice
Open-source and proprietary GenAI tools
Tool selection based on professional goals

Moreover, this section helps learners choose suitable GenAI tools for content creation, campaign execution, audience engagement, and marketing productivity.

Module 4: Prompt Engineering and Task Design

Topics Covered

Prompt engineering helps professionals get better results from AI tools. This section focuses on writing clear prompts, designing useful marketing tasks, and reducing weak or misleading outputs.

Anatomy of an effective prompt
Zero-shot, few-shot, and structured prompting strategies
Task types such as summarization, translation, content generation, and analysis
Tool-specific prompting examples
Reducing hallucinations and bias through prompt tuning

Consequently, learners become more confident in using AI tools for content planning, ad copywriting, campaign ideas, customer messaging, and marketing communication.

Module 5: Ethical, Legal, and Societal Implications of GenAI

Topics Covered

AI must be used with responsibility, fairness, and professional judgment. Therefore, this section explores the ethical and legal boundaries of Generative AI.

AI hallucinations and misinformation
Plagiarism and content ownership concerns
Bias and fairness in LLMs
AI and job displacement
Global perspectives on AI regulation
Responsible AI frameworks, including OECD and EU AI Act references

Furthermore, learners understand why transparency, authenticity, privacy, and ethical decision-making are important in AI-powered marketing.

Module 6: GenAI in Everyday Productivity & Collaboration

Topics Covered

Generative AI can improve workplace productivity when used correctly. This section explains how professionals can use AI as a practical assistant for communication, documentation, and collaboration.

Writing, summarization, and content creation with AI
AI in Excel, PowerPoint, CRM, and documents
Workflow automation with Zapier and Make
AI for meetings, brainstorming, and reporting
Chatbots and virtual assistants

As a result, learners understand how AI can support everyday work before applying it to advanced marketing strategy and growth tasks.

Module 7: Content & Creative Marketing with GenAI

Topics Covered

This section connects Generative AI with content creation, branding, campaign communication, and creative marketing workflows. Learners explore how AI can support faster and more personalized content production.

Automated ad copy generation
Blog and social media content creation with AI
Personalization at scale for emails and product recommendations
AI-powered design and creative branding tools
Campaign automation using GenAI

In addition, this section shows how AI can help marketing teams save time, improve consistency, and produce more relevant customer-facing content.

Module 8: Customer Insights & Engagement

Topics Covered

Customer engagement improves when brands understand audience needs, behaviour, and sentiment more clearly. Therefore, this section focuses on AI-powered customer insights and personalized engagement.

Customer segmentation using AI-driven analysis
AI chatbots for brand engagement
Virtual influencers and AI-assisted customer interaction
Sentiment and trend analysis using GenAI
Customer journey optimization use cases

Moreover, learners understand how AI can help brands deliver more relevant, timely, and meaningful customer experiences.

Module 9: Data-Driven Marketing Strategy with GenAI

Topics Covered

Modern marketing requires data intelligence, experimentation, and responsible decision-making. This section explores how GenAI can support performance marketing, SEO, predictive analytics, and strategic growth.

Predictive demand forecasting with AI
AI-enhanced SEO and search optimization strategies
A/B testing and campaign performance improvement with GenAI
Responsible AI marketing practices
Ethical concerns such as deepfakes, misinformation, and brand credibility risks

Finally, learners understand how to use AI responsibly for smarter campaigns, stronger customer insights, and better marketing growth decisions.

WHO SHOULD ENROLL

The Generative AI in Marketing course is suitable for learners and professionals who want to understand how AI can improve digital marketing, content creation, customer engagement, campaign performance, and brand growth.

Digital marketing professionals and strategists
Content creators and brand managers
Entrepreneurs and startup founders
Students and professionals aiming to integrate AI into marketing roles
Business owners who want to improve marketing productivity with AI

Therefore, this course is ideal for learners who want practical exposure to AI-powered marketing and future-ready growth skills.

WHAT YOU'LL GET

Learners receive structured course resources, practical exposure, and certification support throughout the program. In addition, the course provides learning material that helps participants revise concepts and apply them beyond the classroom.

Industry-recognized certification upon completion
Real-world case studies and guided assignments
Practical exposure to AI-driven campaign design
Expert mentorship and feedback on practical assignments
Online access to course content

Furthermore, these resources help learners understand how AI-powered marketing solutions are used in content creation, SEO, customer engagement, campaign planning, branding, and business growth.

PROJECT SUBMISSION

The project submission process helps learners apply marketing and Generative AI concepts in a practical and structured way. Therefore, participants complete project work to demonstrate their understanding, originality, and professional application.

Choose Your Project Topic

First, explore the project topics available in the LMS. Review the project description, learning outcomes, and required skills before selecting your topic.

If required, ask your guide or mentor for support. After that, finalize your topic and begin your project work.

Submit Your Project

Once your project report is complete, follow the project submission guidelines for formatting, font, spacing, citations, and originality.

Your report will go through a plagiarism check. Therefore, keep the work original, properly structured, and clearly written.

Finally, upload your final PDF report and any supporting files to the LMS.

Project Evaluation

After submission, your project is evaluated by an organization mentor and an internal faculty supervisor.

The evaluation focuses on report quality, depth of understanding, concept application, problem-solving skills, professional behaviour, and timely submission. In some cases, a viva or presentation may also be required.

Credits, Certificates and Results

Credits may be awarded as per applicable UGC NEP 2020 guidelines. In addition, your internship certificate will be issued after report approval, evaluation completion, and uploading of the required organization certificate.

Thereafter, learners can download the internship completion certificate directly from the LMS.

OUTCOME

After completing the Generative AI in Marketing course, learners will be ready to design and execute AI-powered marketing campaigns, gain actionable customer insights, and automate creative workflows.

In addition, participants will understand how AI can support content generation, personalization, trend analysis, SEO, campaign optimization, and responsible brand communication.

Overall, this course prepares learners to become future-ready marketers who can lead in the era of intelligent, data-driven, and AI-powered marketing.

KNOW MORE ABOUT

Explore Internship Courses – Benefits and Offerings to understand how SkillGroom programs support practical learning, project submission, certification, and career-focused development.

Also, learners can browse related GenAI internship courses to build wider expertise in finance, marketing, HR, operations, data science, IoT, cybersecurity, and AI foundations.

Finally, choose the course that best matches your career goals and begin building practical skills for the future of marketing and work.

INTERNSHIP COURSES - BENEFITS AND OFFERINGS