AI foundations for marketing - You will clarify core AI concepts and learn how to distinguish machine learning, neural networks, and NLP, so you can choose the right tools for specific marketing goals with more confidence.
Marketing workflow automation - You will learn how to automate repetitive marketing tasks, helping you launch campaigns faster, save team time, and manage everyday promotional workflows in a more efficient way.
Stronger personalization and insights - You will discover how to use AI for personalized communication, data analysis, and audience behavior forecasting, so you can plan smarter actions and improve campaign performance.
Responsible AI use - You will understand the main ethical, legal, and data security risks, which will help you implement AI solutions responsibly and avoid costly mistakes in brand communication and execution.
AI-driven marketing strategy - You will learn how to define marketing goals with AI and connect new tools with your existing strategy, so technology supports measurable business results instead of becoming a gimmick.
Faster content creation - You will practice creating articles, posts, and other materials with AI tools, allowing you to speed up content production and keep your messaging consistent across multiple channels.
AI multimedia production - You will explore tools for creating graphics, audio, and video, so you can produce promotional assets, podcasts, or audio ads on your own without relying on a large external team.
Websites and SEO with AI - You will learn how to use AI when building websites, optimizing pages, and supporting SEO work, so you can improve brand visibility faster and better align your site with user needs.
Modern marketing increasingly relies on generative AI, AI-first operating models, and process automation across B2B and B2C activities. This section frames the landscape of tools such as ChatGPT, Gemini, Claude, Copilot, Perplexity, Midjourney, and Canva AI, then moves into prompt engineering, prompt libraries, and response quality management.
Creating content with AI covers both long-form materials and conversion-oriented copy used across marketing channels. Participants work on blog articles, newsletters, expert content, headlines, CTAs, product and service descriptions, landing pages, and promotional campaign messaging adapted to different formats.
Search visibility now combines classic SEO with GEO, so content must work both for search engines and generative systems such as ChatGPT, Gemini, and Perplexity. Topics include keyword analysis, topic clusters, article structures, AI-Ready Content strategies, brand presence monitoring, and automation of audits, competitor reviews, and publication plans.
Canva AI and related tools support the production of marketing graphics and advertising materials, while video solutions help generate clips, AI avatars, subtitles, and translations. The scope also includes voice synthesis, AI podcasts, automated voice-overs, and the legal implications of voice cloning.
Effective personalization depends on linking segmentation with dynamic communication across the customer journey. The section covers persona creation, behavior analysis, prediction of customer needs, and microsegmentation, then shows how AI tailors emails, websites, and commercial offers to specific audience groups.
Designing AI agents for marketing starts with defining roles such as content creation, competitor monitoring, campaign analysis, and handling customer inquiries. From there, the focus moves to workflow automation for campaign setup, content publishing, reporting, and generating recommendations from ongoing activities.
Social media teams use AI to plan publication calendars, generate posts, and adapt multichannel communication to the requirements of individual platforms. Attention is also given to brand monitoring, sentiment and comment analysis, as well as ad creative variants, audience optimization, and performance evaluation.
Turning marketing data into decisions requires AI support in campaign, traffic, and conversion analysis, with methods for spotting patterns and emerging trends. The module also covers automated reporting, generation of business insights, dashboard design, and preparing management-ready presentations.
Governance around AI marketing focuses on protecting customer data, aligning generative AI use with GDPR, and defining internal security policies. The section also addresses copyright, labeling of AI-generated content, publisher responsibility, and the standards needed for quality control, risk management, and department-level AI strategy.
Digital marketing basics - You should understand core digital marketing terms such as campaigns, target audience, funnel, and communication channels, so you can follow the training examples with ease.
Online content experience - You should have at least basic experience creating or editing online content, so you can move smoothly through exercises focused on content, visuals, and audio materials.
Web tools proficiency - You should be comfortable using a web browser, online forms, and common web applications, because the training includes hands-on work with AI tools and marketing platforms.
Analytical thinking - You should be able to read basic marketing data and draw simple conclusions, so you can work effectively with personalization, analytics, and market prediction topics.
