Marketing with AI for Dummies

via Coursera

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Paid Certificate Available
Duration & workload

22 hours 18 minutes
Sessions

Self-Paced
Level

Beginner
Subtitles

English

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Overview

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Based on the best-selling book, Marketing with AI for Dummies, by Shiv Singh. This course explores the transformative power of artificial intelligence in the marketing world. You'll gain practical insights into AI-driven strategies that are reshaping customer personalization, content creation, and data analytics. The course covers essential AI tools marketers can leverage to enhance engagement and optimize campaigns, enabling them to stay competitive in today's fast-evolving digital landscape. Learn how to implement AI technologies to personalize customer experiences, enhance content development, and improve campaign performance. You will explore real-world applications of AI, gaining valuable experience in using AI tools to drive marketing growth. The course combines theoretical knowledge with practical techniques, making complex AI concepts accessible and easy to apply to marketing strategies. What sets this course apart is its focus on actionable insights and practical examples. You’ll gain the tools necessary to implement AI solutions into your marketing efforts, improving efficiency and effectiveness. No technical AI background is required, just a passion for transforming marketing strategies. Marketers, business owners, and marketing professionals will benefit from this course. A basic understanding of marketing concepts is helpful but not mandatory, as this course is designed to provide both theoretical and hands-on knowledge. From Marketing with AI For Dummies Copyright © 2025 by John Wiley & Sons, Inc. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies Used by arrangement with John Wiley & Sons, Inc.

Syllabus

A Brief History of AI

In this section, we trace AI's evolution from mythic automata to generative models, examine the Turing Test, and differentiate machine learning, expert systems, and generative AI for business use.

Exploring AI Business Use Cases

In this section, we discover high-impact generative AI opportunities in customer operations, research and development, marketing, and legal functions, converting McKinsey estimates into organization-specific return on investment figures.

Launching into the AI Marketing Era

In this section, we position AI as a vital marketing copilot, outline foundational adoption steps, present strategic frameworks, and use an AI readiness checklist to guide integration and measure progress.

Collecting, Organizing, and Transforming Data

In this section, we learn to evaluate data quality, source marketing information ethically, apply metadata governance, and build extract, transform, load pipelines for dependable machine learning readiness.

Making Connections Machine Learning and Neural Networks

In this section, we learn match marketing tasks to supervised, unsupervised and reinforcement learning, design deep neural networks, and review image, sequence and reward-driven models for prediction.

Adding Natural Language Processing and Sentiment Analysis

In this section, we implement NLP pipelines, leverage transformers for sentiment analysis, recognize emotion detection limits, and translate text-derived trends into data-driven, customer-centric marketing strategies following recommended best practices.

Collaborating via Predictions, Procedures, Systems, and Filtering

In this section, we harness machine-learning predictive analytics, architect robust AI procedures and lifecycle workflows, and dissect collaborative, content-based, and hybrid filtering to deliver data-driven, personalized decisions.

Getting Comfortable with Generative AI

In this section, we explore generative AI models and applications, demystify GPT's deep learning architecture and training process, and assess technical limitations alongside ethical, societal and business considerations.

Segmentation and Persona Development

In this section, we apply AI/ML to behavioral segmentation, build data pipelines for dynamic clusters, create and validate ethical personas, and explore synthetic panels to inform targeted marketing decisions.

Lead Scoring, LTV, and Dynamic Pricing: Overview

In this section, we apply AI to rank leads, forecast customer lifetime value with predictive analytics, and convert those insights into real-time dynamic pricing to optimize acquisition spend and revenue.

Churn Modeling and Measurement with AI

In this section, we apply machine-learning churn models, validate and calibrate performance metrics, and translate AI-generated insights into personalized retention tactics that reduce attrition and maximize customer lifetime value.

Using AI for Ideation and Planning

In this section, we streamline marketing ideation with generative AI, craft precise prompts, treat hallucinations as creative sparks, evaluate tool options, and translate rapid concept generation into actionable, evidence-based plans.

Perfecting Prompts for Conversational Interfaces

In this section, we explore marketing use cases for conversational interfaces, build role task format prompts for large language model chatbots, and apply bias mitigation techniques to deliver trustworthy natural language processing outputs.

Developing Creative Assets

In this section, we watch Midjourney, Adobe Firefly, and related models turn text into images, refine multimedia content, and illustrate brand, legal, and ethical checkpoints for artificial intelligence assisted creation.

Search Engine Optimization (SEO) in the AI Era

In this section, we analyze AI-driven search shifts like SGEs, implement techniques to boost personalized rankings, and assess automation tools that streamline optimization and link building to sustain organic traffic.

Performing A/B Testing with AI

In this section, we discover how artificial intelligence enhances A versus B, multivariate, and multi page testing, from experiment design to data interpretation, yielding continual user experience and conversion improvements.

Fine-Tuning Content with Localization and Translation

In this section, we implement AI-driven localization workflows, leverage multilingual LLMs to capture cultural context, and evaluate real-time translation solutions that enhance global marketing relevance, efficiency, and user trust.

Applying AI to Performance Marketing

In this section, we apply AI to performance marketing, launching Google Performance Max, Meta Advantage+, Amazon, and TikTok campaigns while automating targeting, smart bidding, creative generation, and ROAS tracking.

E-mail and SMS Marketing with AI

In this section, we discover how artificial intelligence personalizes email and short message service (SMS) marketing, predicts customer behavior, and turns performance data into insights for higher engagement.

Diving into Personalized Marketing

In this section, we transform customer data into actionable segments, apply predictive analytics for individualized outreach, and evaluate AI tools that automate real-time personalized content, enhancing loyalty and ROI.

Leading Your Business in the AI Era

In this section, we identify high-value artificial intelligence opportunities, embed machine learning insights in marketing workflows, and align leadership, culture and key performance indicators for data-driven transformation.

Addressing Ethical, Legal, and Privacy Concerns with AI

In this section, we establish ethical AI frameworks for marketing operations, implement privacy safeguards for proprietary and customer data, and conduct systematic bias audits, ensuring transparent, compliant, human-centric algorithm deployment.

Tens Pitfalls to Avoid When Marketing with AI

In this section, we identify critical AI-driven marketing pitfalls and demonstrate safeguards, preserving human creativity, brand consistency, qualitative insight, and long-term strategic alignment for trustworthy, sustainable campaign performance.

Ten Future AI Developments to Watch For

In this section, we survey ten emerging AI trends in marketing, explaining how quantum computing, predictive modeling, VR and synthetic media personalize content, anticipate demand and craft immersive customer experiences.