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Public vocational training

AI content marketer
training course

Involved from course design and curriculum adjustment, now teaching 28 trainees for 20 days and 140 sessions of the 420 hour course on search, ads, and growth.

Client
SESAC Seongdong cohort 6
Period
2026-09 to 2026-12 In progress
  • 28Trainees
  • 420 hoursFull course
  • 140 sessions20 days taught

A course that prepares future marketers to handle content planning, ad delivery, analysis, and automation on their own with AI. Three instructors share it, and we teach the search, ads, and growth sections.

How we planned it

  1. 1

    Redefining the purpose of the course

    Most hiring partners were startups with no marketing team, where someone else covers marketing on the side. That means graduates will sit in a solo marketer seat that has to act like a whole agency. So although the course is called content marketer, our sections were not limited to content: trainees experience the whole marketing job with AI, from planning to ads, analysis, and automation.

  2. 2

    Adjusting our sections and rewriting materials

    We were first set to teach six days of brand design, but during curriculum adjustment we swapped them for the six day second half of AI creative while keeping 20 days in total. We rechecked the original curriculum, rewrote the six days, and framed them as three layers of inbound traffic, classic SEO, GEO, and AEO, plus channel KPIs.

  3. 3

    Ad practice without a product to sell

    A government funded course has no real product for trainees to advertise. To solve this, hiring partners were used as practice cases across four types, commerce, platform, course sales, and app, and GA4 practice runs on the public Google demo account with real sales data. A small live ad budget was planned per team across three campaign types, commerce, lead generation, and app installs, so trainees compare campaigns with different goals.

  4. 4

    Honest metrics

    Without product sales, only upper funnel metrics such as reach, clicks, and landing page time can be measured properly. We tell trainees this limit up front and set the training goal on awareness and interest optimization, which is what a startup solo marketer actually does in the first months.

  5. 5

    Linking three instructors into one course

    Each section output becomes the next section input. Content made in the Day 31 mini project becomes ad creative from Day 32, and ad results feed the AARRR diagnosis on Day 41. Topics another instructor already covered, such as ROAS, are linked briefly and then deepened, and joint handover meetings are held at every instructor change. Materials are written for non majors, with step by step screenshots and labs cut into 10 to 15 minute units.

What we did

  • Joined at the course design and curriculum adjustment stage and submitted a curriculum improvement memo.
  • Wrote separate instructor and trainee materials for all 20 days.
  • Set handover criteria at each section boundary so outputs carry over between instructors.
  • Runs and grades two team mini projects.

How we taught

  • Each day uses the same ten part frame: goals, core concepts, framework, steps, cases, AI prompts, practice criteria, common mistakes, link to the next day, and references.
  • Good cases sit beside three types of bad cases, and five self check questions let trainees judge their own work.
  • The 20 days run as one campaign, where ad data feeds the AARRR diagnosis and the diagnosis feeds automation design.
  • Original sources such as GA4 and Meta documentation, AARRR, and Lean Analytics are cited, and practice happens in real tools.

What we taught

Days 26 to 31, 6 days

AI creative, second half

  • Law and ethics in AI marketing
  • Encoding and publishing by channel
  • Classic SEO, GEO, and AEO
  • Channel KPIs
  • A mini project delivering a brand brief in one day
Days 32 to 40, 9 days

Performance and data

  • CPC, CPM, CTR, CPA, ROAS and working back from targets
  • Ad channels compared and three budget strategies
  • GA4 events and a Looker Studio dashboard
  • Meta campaign structure, audiences, and AI creative variants
  • A/B test design, landing pages, and CRO
  • Naver GFA, Kakao Moment, and an overall review
Days 41 to 45, 5 days

Growth and automation

  • AARRR and the North Star Metric
  • Retention and three CRM campaigns
  • Automation scenarios in Make
  • Agentic AI for research, planning, execution, and analysis
  • An integrated campaign mini project

Timeline

  1. Course design and materials

    • Course design, curriculum adjustment, and improvement memo
    • Instructor and trainee materials for each part
    • Days 26 to 31 rewritten and delivered on 2026-09-02

  2. AI creative, second half (6 days)

    • SEO, GEO, AEO, and channel operations

  3. Performance and data (9 days)

    • Metrics, channels, measurement, ads, tests, landing pages

  4. Growth and automation (5 days)

    • AARRR, CRM, Make, agentic AI

Results

  • The course is in progress. Our sections are designed so each of the 28 trainees leaves with 15 or more individual portfolio pieces.
  • Key outputs include a three layer brand search report with a two week channel calendar, a Looker Studio KPI dashboard, a Meta campaign with an A/B test, and a Make automation scenario.
  • These outputs feed the final project run with hiring partner companies.

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