In this Specialization, you’ll learn how to use generative AI to plan campaigns, create on-brand social content, and improve performance across channels, without losing authenticity or trust. You’ll start by learning when to use AI (and when not to), how to prompt for ideas, captions, hashtags, and repurposed variations, and how to review outputs for accuracy, privacy, and disclosure.
Next, you’ll build campaign foundations with AI-enhanced planning, audience targeting, and content sequencing, then refine drafts for voice, clarity, and platform fit. You’ll also design and run a micro-influencer strategy, using AI to assess collaboration potential, strengthen identity, and iterate based on results.
Finally, you’ll apply AI tools in a LinkedIn-focused analytics workshop to interpret metrics, run sentiment checks, and turn insights into optimization actions.
By the end, you will be able to:
Plan multi-channel campaigns with AI-supported briefs, calendars, and guardrails.
Create and refine posts that match brand voice and ethical standards.
Measure performance and optimize content using analytics and AI-assisted insights.
Applied Learning Project
You’ll work through a realistic social media case study that follows a micro-influencer campaign across LinkedIn, Instagram, and YouTube. Activities include comparing a traditional workflow vs. an AI-assisted workflow; building a campaign plan and weekly content sequence; generating caption and hashtag drafts; and repurposing one idea into multiple platform-ready versions.
You’ll practice editing AI outputs for tone, voice, and clarity, then apply an AI ethics checklist to catch misinformation, privacy risks, misleading visuals, and missing disclosure. In the micro-influencer course, you’ll use AI to evaluate fit, draft outreach and collaboration briefs, and set iteration rules for continuous improvement.
In the LinkedIn workshop, you’ll analyze post metrics, perform basic sentiment analysis, and turn findings into an optimization plan and next-test recommendations.
