AI Digital Marketing Course

Lesson 1 • Digital Marketing Landscape Overview

Survey owned, earned, and paid channels and their interdependencies. Provides the channel map that all subsequent AI applications will target.

Lesson 2 • Ethical and Regulatory Considerations

Apply responsible AI principles including transparency, fairness, and consumer privacy compliance. Prepares marketers to build trust while avoiding reputational and legal risk.

Lesson 3 • AI Tool Categories in Marketing

Classify AI tools by function: content, analytics, personalization, and automation. Enables informed tool selection aligned to specific marketing objectives.

Lesson 4 • Data Fundamentals for AI Marketing

Identify first-, second-, and third-party data types and their quality requirements. Grounds students in the data infrastructure AI models depend on.

Lesson 1 • Predictive Audience Modeling

Build lookalike and propensity models to expand and prioritize audiences. Enables marketers to allocate budget toward highest-value prospects.

Lesson 2 • Social Listening and Sentiment Analysis

Apply natural language processing tools to extract audience insights from social data. Feeds real-time consumer intelligence into segmentation and messaging strategy.

Lesson 3 • Customer Data Platforms and AI

Configure customer data platforms to unify profiles and feed AI segmentation models. Connects data infrastructure to real-time audience activation.

Lesson 4 • Persona Development with AI Insights

Synthesize AI-generated data signals into validated, actionable marketing personas. Bridges quantitative audience data with creative and messaging decisions.

Lesson 1 • AI-Generated Visual and Multimedia Content

Apply image, video, and audio generation tools to marketing creative production. Expands content capabilities without proportional increases in production cost.

Lesson 2 • Content Personalization at Scale

Implement dynamic content systems that tailor messaging to individual user attributes. Connects audience segmentation outputs to personalized content delivery.

Lesson 3 • Content Quality Assurance and Governance

Establish review workflows, style guides, and AI output auditing to maintain standards. Ensures AI-generated content meets accuracy, compliance, and brand requirements.

Lesson 4 • Long-Form and Short-Form Content at Scale

Use AI to draft blogs, emails, social posts, and ad copy efficiently. Teaches quality control processes that preserve brand voice across high-volume output.

Lesson 1 • Technical SEO Auditing with AI

Automate crawl analysis, site health scoring, and issue prioritization using AI tools. Accelerates technical fixes that unblock organic ranking potential.

Lesson 2 • AI-Enhanced Keyword Research

Use AI to uncover search intent clusters, semantic keywords, and content gaps. Replaces manual keyword guesswork with data-driven topic prioritization.

Lesson 3 • Measuring and Iterating SEO Performance

Track organic KPIs, attribute traffic to content efforts, and refine strategy with AI insights. Closes the loop between content investment and measurable search outcomes.

Lesson 4 • On-Page Optimisation with AI Tools

Optimise title tags, meta descriptions, headings, and body content using AI recommendations. Directly improves page relevance signals for search engine ranking.

Lesson 1 • Dynamic Creative Optimisation

Build modular ad creative systems that AI assembles and tests in real time. Maximises creative performance without manual A/B test management overhead.

Lesson 2 • AI Audience Targeting in Paid Channels

Apply in-market, affinity, and custom intent audiences alongside lookalike targeting. Connects audience segmentation work to paid media activation.

Lesson 3 • AI Bidding Strategies and Automation

Configure smart bidding algorithms to optimise for conversions, value, and target metrics. Teaches when to trust automation and when to apply manual overrides.

Lesson 4 • Campaign Performance Analysis and Scaling

Diagnose campaign inefficiencies using AI analytics and apply scaling frameworks. Translates data insights into budget reallocation and growth decisions.

Lesson 1 • Email Analytics and Continuous Optimisation

Measure deliverability, engagement, and revenue attribution to refine email programmes. Applies AI-generated insights to iterative improvements in open, click, and conversion rates.

Lesson 2 • Email Marketing Strategy and Architecture

Define list segmentation, journey mapping, and programme goals before automation setup. Ensures AI optimisation operates on a strategically sound programme foundation.

Lesson 3 • AI-Powered Segmentation and Targeting

Apply predictive engagement scoring and behavioral triggers to segment email audiences. Delivers the right message to the right subscriber at the right moment.

Lesson 4 • Personalization and Dynamic Content in Email

Implement AI-driven subject lines, product recommendations, and body content variations. Moves beyond first-name personalization to contextually relevant messaging.

Lesson 1 • AI-Powered Community Management

Deploy AI to triage comments, detect sentiment shifts, and draft response templates. Maintains brand responsiveness at scale without proportional staffing increases.

Lesson 2 • AI-Informed Social Media Strategy

Use AI trend analysis and competitive benchmarking to set platform-specific social goals. Grounds social tactics in audience intelligence and business objectives.

Lesson 3 • Influencer Identification and Vetting with AI

Use AI platforms to discover, score, and vet influencers by audience quality and brand fit. Reduces influencer selection risk and improves campaign ROI.

Lesson 4 • Content Creation and Scheduling Automation

Generate, repurpose, and schedule social content using AI tools and automation platforms. Increases publishing consistency while reducing manual production time.

Lesson 1 • Predictive Analytics and Forecasting

Apply AI forecasting models to predict demand, revenue, and campaign performance. Shifts marketing planning from reactive to proactive and evidence-based.

Lesson 2 • Multi-Touch Attribution Modeling

Compare rule-based and data-driven attribution models to assign credit accurately across channels. Enables budget decisions grounded in true channel contribution.

Lesson 3 • Strategic Planning and AI-Driven Roadmaps

Synthesise analytics outputs into integrated marketing strategies and AI adoption roadmaps. Prepares students to lead data-informed planning at organisational level.

Lesson 4 • Marketing Mix Modeling with AI

Use AI-enhanced marketing mix models to quantify channel contribution and optimise spend allocation. Provides a privacy-resilient alternative to cookie-dependent attribution.