This course is designed for marketers, e-commerce store owners, business analysts, product managers, and entrepreneurs who want to put AI to work—without writing any code. Over two hands-on modules, you'll learn to use popular tools like ChatGPT, Gemini, Shopify Sidekick, Landbot, Tidio, Akkio, and Canva AI to run a smarter online store. In Module 1, you'll generate ready-to-publish product listings, set up smart product recommendations, build a customer-service chatbot, and mine customer reviews for insight. In Module 2, you'll segment customers, create multi-channel marketing campaigns, forecast demand for better inventory planning, and use AI to spot fraud and shape pricing strategy. Every lesson is 100% practical, built around real e-commerce tasks you can complete on a demo store using free tiers and trials. No programming, data science, or prior AI experience is required—just a basic understanding of how online stores work. By the end, you won't just understand what AI can do for e-commerce; you'll have real, hands-on experience implementing it with tools you can keep using in your own business. Whether you run a small side-hustle store or manage marketing for a fast-growing brand, you'll walk away able to save hours of work, create better content, and make sharper, data-informed decisions—all powered by accessible, no-code AI you already have access to.

AI for E-Commerce: No-Code Tools for Sales & Marketing

Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
4 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Use ChatGPT, Gemini, and Canva AI to generate product content, ad copy, and marketing campaigns that are ready to publish to your store.
Build a no-code customer-service chatbot and set up smart product recommendations for your store without writing a single line of code.
Turn raw sales and review data into customer segments, demand forecasts, and pricing decisions using easy no-code AI platforms.
Details to know

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Recently updated!
August 2026
Assessments
4 assignments
Taught in English
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There are 2 modules in this course
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