Want to use marketing tools and models the way they're meant to be used, only now with AI in the loop?

Our course isn't about neural networks, and it isn't a marketing course either. It's essentially a 29-hour workflow sprint. You learn to embed different AI models into the full marketing cycle, from market analysis to communications, and master agentic automation with human verification.

Academic hours
45% theory · 35% practice · 20% lab

Programme parts

Practical artifacts

up to 20

People per cohort

View programme

METHODAIVERIFY

Interactive diagram

Hover a layer to see what it contains. Click JTBD or CJM to run a task through all three layers.

01 · Method

The frameworks a task starts with. JTBD, CJM, RFM, Censydiam, PEST and SWOT set the structure of the request, so the model answers the precise question, not the convenient one. The programme has 15 modules, and every one has its own method and its own artifact.

View programme →

02 · AI layer

Prompts built on the P.R.E.S.S. framework and ready-made workflows from the MktFlow platform. You plug in your industry, product and audience, the model returns structured JSON, which moves to the next step, not into a chat window.

See it in action →

03 · Verification

Human-in-the-loop (HITL) is built into every module. You check the output against a criteria checklist before it enters a decision, and send corrections back to the model instead of rewriting it yourself.

See what skills this builds →

Without exoskeleton

This is how most people work. Only the AI layer, with no method and no verification. A prompt without a framework gives a plausible answer to an imprecise question, and without verification the error ends up in the presentation and in the budget.

HITL

verification in every module

P.R.E.S.S.

proprietary prompting framework

AI tools used throughout the course

mktflow.online

platform for workflow practice

What it looks like in practice

A platform for practicing workflows

Practice doesn't happen in a chat with a neural network — it happens on mktflow.online. Every workflow there is broken into steps with ready-made prompts, HITL checkpoints and an artifact at the end. Below is a recording of a W15/W16 run: from analysing competitor communications to a finished communication platform with a Tone of Voice.

W15 · W16 The run takes 1.2 minutes on the platform, no editing of results

What happens in the recording

01
Enter the workflow You pick the workflow you need and load your project data. The system automatically pulls in results from previous steps in the session.
02
Steps with ready-made prompts Every step is a separate request built on the P.R.E.S.S. framework. The prompt is already assembled — you adjust the inputs for your brand instead of writing from scratch.
03
HITL verification Before moving on, you accept the result or send it back for another pass. An unverified output never reaches the next step.
04
An artifact at the end W16 delivers a communication platform: Big Idea, message pillars, Tone of Voice and a link to AIDA. Export to JSON, PDF or JPG.

Try the demo access right now

Access to the MktFlow Pro platform is included in the course. The free code unlocks the full W3 "Competitive Analysis" workflow. The same engine you see in the recording, running on your own data. API keys are included in the price, and the platform stays available by subscription after the course.

Try it free

Who the course is for

Practicing marketers with 3–7 years of experience

You already have a solid marketing foundation. We add the AI tools layer and methodology you can embed into daily tasks.

Right for you if you

Run tasks, not study theory

Write briefs, analyse competitors, prepare strategies
Run campaigns in digital channels
Want to speed up routine work without losing quality
Are ready to restructure your workflow
No prior AI experience required

Key scenario

"I tried ChatGPT — got generic outputs"

The course shows how to move from "write a text" to structured steps
We move from "knowing about AI" to specific working scenarios
If you're experienced in marketing but new to AI — you'll manage
If you've taken AI courses but haven't embedded them in your workflow — this is for you

Not right for you if you

Are looking for an intro course on neural networks

Have no experience in digital marketing
Expect a tool list without methodology
Want AI to "do everything" with no verification
Aren't ready to work on real marketing tasks

What you'll be able to do after the course

Which AI-driven processes you'll master

You stay in charge of the marketing task, AI accelerates the execution. You only verify the result.

Market & competitor analysis

PEST, Porter's 5 Forces and competitive analysis get structured and several times faster, with mandatory fact-checking.

Segmentation & proto-persona

You'll master RFM analysis, Censydiam and JTBD from reviews and transcripts, and build evidence-based profiles instead of intuitive guesses.

Strategy & positioning

SWOT/TOWS, a value proposition and a radar chart of choice factors will give you strategic conclusions, filtered through your own review.

Prompts with predictable results

You'll learn the P.R.E.S.S. framework, which delivers reproducible, structural conclusions instead of generic filler.

CJM & brand model

Customer journey maps, a brand model and the foundation of a communication strategy — assembled faster and more systematically than by hand.

Verification without fear of errors

You'll get a HITL checklist and learn to cross-check AI conclusions, catch hallucinations, and never hand raw insights to management.

Choosing the right AI solution

You'll finally master the decision matrix: when you need an AI chat, when you need an agent, when you need RPA, and which skills each requires.

Skills after the course

Skill Set: 13 specific competencies

Three skill categories, from foundational AI literacy to managing agentic systems. Every skill is tied to a course module and a verifiable artifact.

Category 01

General AI Skills

01 Understand the GenAI tool ecosystem and choose the optimal model for a marketing task, from research to production campaigns

02 Design controlled prompts: tell a one-off request apart from a stable instruction and assemble them into reproducible workflows

03 Critically analyse AI outputs: apply basic fact-checking methods and reduce the risk of errors and data bias

Category 02

Marketing AI

04 Embed AI into key marketing processes: analysis, synthesis, forecasting, planning

05 Analyse the market with AI: from JTBD and segmentation to Censydiam and Customer Journey Map

06 Work through brand segmentation and positioning with AI

07 Build a brand communication strategy with AI: Brand Model 2.0, Big Idea, Tone of Voice, key messages

08 Generate content, and develop copy and visuals for performance and content marketing with AI

Category 03

AI Agent Skills

09 Tell AI agents apart from ChatGPT, bots and RPA — by autonomy, reasoning and tools

10 Classify agentic systems by type: Single-Task, Workflow Agents, Agent Swarms

11 Match AI workflows to marketing tasks with a justified type of solution

12 Design basic workflow logic: input → processing → output → HITL control

13 Use AI solution architecture and a decision matrix to assess tasks by autonomy, risk and cost

Who teaches the course

Instructors

Practitioners, not academic theorists. The course is built on real experience implementing AI in marketing processes.

Artem Movsesyan

Business Consultant · Business Psychologist · Co-founder of MktFlow

Artem operates at the intersection of strategic management, organizational psychology, and AI-augmented workflow design. He co-authored a university-level textbook on branding and marketing and serves as an independent director with a focus on governance and institutional development.

His professional credentials are anchored in European standards: Master Coach ICI, member of the European Mentoring and Coaching Council (EMCC), and Certified Assessor for the European Foundation for Quality Management (EFQM) Excellence Award — one of the most rigorous quality frameworks recognized across EU organizations. He has lectured at international graduate institutions and leads the Interdisciplinary Committee of the Association of Digitalisation Practitioners.

As a mentor on accelerator programmes focused on high-growth ventures, Artem applies a systems-oriented approach: diagnosing organizational constraints, designing governance layers, and embedding AI as a structured decision-support tool — not a substitute for managerial judgment.

AI Strategy Marketing Business Psychology Workflow Design

Alexander Demenko

Marketing Strategist · Co-founder of MktFlow

Alexander brings 25 years of hands-on experience in brand management, product development, communications, and category strategy — shaped across leadership roles in major FMCG organizations, a branding agency, and educational platforms.

His track record is defined by measurable outcomes: 18% brand sales growth through strategic repositioning; 61% growth following a full brand redesign; 16 new products launched with combined revenues exceeding €30M+/year; and a category scaled to €10M+ within a single fiscal year. He has also authored a course for one of Europe's largest digital learning platforms.

Alexander's approach treats brand strategy as an operational system — where portfolio logic, consumer signal interpretation, and go-to-market workflow are designed for verifiability and sustainable performance, not one-off campaign results.

Brand Strategy FMCG AI Agents Implementation

Graduate reviews

What marketers say after the course

Cohort A finished the course in 2026. Below are two written reviews, unedited on our part.

Curriculum

29 hours. 15 modules. Every module delivers an artifact.

Structure: lectures 45% + practicum 35% + lab sessions 20%. Every module produces a verifiable result.

AI Fundamentals

5 modules, 13 hours. The student learns to control AI: choosing tools, setting up a personal workspace, writing prompts, verifying outputs. The HITL checklist is created here and applied in every subsequent module.

Module goal

The student knows what AI solves and what stays outside its reach. They choose a tool for the specific task instead of following trends.

Topics

Three model classes: Text AI, Image AI, Voice AI — how they work, not which tool to reach for
AI Toolkit: task → model class → specific tool (Perplexity, Claude, Gamma, Canva)
Where AI lies: hallucinations, fabricated statistics, dead links, template language
Lab: comparing ChatGPT / Claude / Perplexity on the same task (writing a brief)

Theory 50% Practice 50%

Artifact

Tool comparison matrix + a "task → tool" map

Module goal

The student turns ChatGPT/Claude from an "on-demand chat" into a configured workspace with memory, custom instructions and a regular management ritual.

Topics

Three elements of a personal setup: memory, custom instructions, projects/folders
Management rituals: weekly metrics review, meeting prep, team digest
HITL for the setup: checking memory, verifying ritual artifacts
Practicum: assemble the setup and run one ritual start to finish

Theory 30% Practice 70%

Artifact

A configured personal setup + one recurring ritual with a verifiable artifact

Module goal

The student masters a prompt system that delivers predictable results on marketing tasks.

Topics

P — Position: what role AI plays
R — Request: exactly what's needed
E — Explain: what context to provide (brief, background, examples)
S — Style: tone and delivery
S — Structure: the expected output format
The "ask clarifying questions" trick reduces hallucinations
Prompt templates for marketers: brief, competitor analysis, TOV, concept
Peer review: a classmate checks your prompt for P.R.E.S.S. completeness

Theory 40% Practice 60%

Artifact

A prompt library of 5 tested P.R.E.S.S. prompts for your own tasks

Module goal

The student understands which competencies keep them resilient in the AI era, and has a system for verifying outputs.

Topics

5 competencies: Problem solving, Algorithmic thinking, System design, Automation, Orchestration
The "edit, don't accept" principle: AI gives you "content-ish," not a finished product
The HITL system: fact-checking, catching template language, adding brand nuance
Verification checklist: ≥1 fact per document, ≥1 source check, ≥1 brand tone check
Blueprint modelling: breaking a workflow into a step-by-step algorithm

Theory 50% Practice 50%

Artifact

A personal HITL verification checklist + a blueprint of one workflow

Module goal

Apply every Part A skill in an intensive session and produce a complete, verifiable result.

Assignments

Task 1 (30 min): 5 campaign concepts from a brief via P.R.E.S.S. → critique → improvement
Task 2 (45 min): a moodboard (Midjourney/Adobe Firefly) with a rationale for each visual
Task 3 (45 min): AI as "devil's advocate" — critiquing a strategy, finding blind spots
Task 4 (60 min): competitive analysis with a mandatory AI error found and corrected

Theory 0% Practice 100%

Artifact

A "Campaign in 20 min" pack: 3 improved concepts + moodboard + competitive analysis with HITL corrections

AI-Enhanced Marketing

7 modules, 14 hours. Opens with an introduction to the "Agent = Model + Harness" formula, then every module is a complete workflow with an artifact. Frameworks (PEST, Porter, SWOT, RFM, Censydiam, JTBD) are embedded inside the workflows, not taught separately. Practised on the mktflow.online platform.

Module goal

The student understands the "Agent = Model + Harness" formula. It explains why the same AI produces filler for one person and a working process for another, and shows what a reliable AI process is built from.

Topics

The Agent = Model + Harness formula: the engine and the machine built around it
Nine harness layers in three groups: talking to the model, tools and memory, planning and control
Three levels of engineering: Prompt → Content → Harness Engineering
ChatGPT Work lab: the first task delegated to an assistant on real company files

Theory 60% Practice 40%

Artifact

A breakdown of your own AI process using the formula + the lab result with facts traceable back to the source files

W1: PEST analysis via AI — prompt, data sources, reliability control
W2: Competitive analysis — 2 similarities, 2 differences, 1 missed opportunity
W3: Porter's 5 Forces — industry structure via AI generation
HITL checkpoints: verifying statistics, data recency, soundness of conclusions

Theory 38% Practice 62%

Artifact

A "Market Analysis" report: PEST + competitors + Porter's 5 Forces with HITL verification

W4: SWOT via AI — generating factors with a selection criterion
From SWOT to TOWS: 4 strategic zones (SO, WO, ST, WT)
Filtering TOWS strategies by feasibility, timeline and resources
AI as hypothesis generator, human as validator

Theory 38% Practice 62%

Artifact

A SWOT matrix + a TOWS strategic map with 3 priority strategies

W6: RFM analysis (Recency, Frequency, Monetary) — AI-assisted calculation on a real dataset
W7: Censydiam — motivational analysis (a key module of the course)
W8: JTBD — analysing existing data (review mining, transcripts), not a replacement for interviews
W9: Customer persona — synthesising RFM + Censydiam + JTBD into a distinct profile

Theory 44% Practice 56%

Artifact

A segmentation model (RFM) + a motivational profile (Censydiam) + JTBD insights + a customer persona

W11: Product attributes — functional, emotional, social
W12: Choice factors — building a radar chart (your product vs. 2 competitors)
Formulating a Value Proposition based on the chart
HITL: checking that attributes match the real product

Theory 38% Practice 62%

Artifact

A radar chart of choice factors + a Value Proposition statement

W14: Communication goals through the AIDA funnel — audience, conversion, purchases
W15: Analysis of competitor communications — channels, tone, key messages
W16: Communication platform — Tone of Voice via AI with a brand-alignment check
W17: Final message matrix (AIDA + segments + channels)

Theory 38% Practice 62%

Artifact

A communication platform: an AIDA × segments × channels message matrix + a TOV guide

W18: Content brief → finished text: a prompt chain from task setup to the final piece
Formats: a VK and Telegram post, an article for Zen, a description for RuTube
AI-assisted editing: draft → critique → improvement → final
HITL check: tone, facts, brand alignment before publishing

Theory 20% Practice 80%

Artifact

4 finished pieces (VK / Telegram / Zen / RuTube) with HITL verification

Agentic Marketing: Fundamentals

3 modules, 2 hours. The student gains the language for making automation decisions: definitions and distinctions of AI agents, a taxonomy of systems, and configuring a ready-made platform Skill with no code. Connectors, the n8n practicum, 7 AI workflows, risks and governance are covered in the advanced module.

Defining an AI agent: an autonomous system with a goal, reasoning, memory and tools
The autonomy spectrum: reactive → scripted → rule-based → autonomous
ChatGPT vs. chatbot vs. RPA vs. AI agent — clear distinctions
A decision matrix by task type

Artifact

A comparison matrix of 4 system types across 5 criteria

Single-Task Agents — narrow functions (bid optimisation, A/B testing)
Advanced Workflow Agents — complex workflows (research, reporting)
Agent Swarms — mirror departmental structures
Three operating models: Traditional / AI-Assisted / Agentic-First

Artifact

Diagnosis of 3 real scenarios with classification and justification

A Skill as a ready-made piece of harness: instructions + step order + parameters
A team's best practices → a digital playbook, no coding needed
Choosing from the task: task → playbook → template → parameters
HITL: checking the output against the playbook; a mismatch is fixed by tuning parameters, not by writing code

Artifact

A configured platform Skill + a run on real input, checked against the playbook

Learning format

How the course is structured

Not just lectures. Every module runs a cycle: lecture → practicum → lab → artifact. Without HITL verification, the assignment isn't accepted.

Lectures — 45%

Methodology with no filler: principle → mechanism → application criteria. Theory only to the extent practice requires it. Examples from real marketing cases.

Practicum — 35%

Working with real tasks, not textbook "course" cases. Exercises are tied to the full marketing cycle: analysis → segmentation → positioning → communications.

Lab sessions — 20%

Practice on the mktflow.online platform with pre-filled templates. API keys are provided. Every lab session produces a specific artifact with a HITL checkmark.

Small cohort

Up to 20 people. Peer review is a required part of the programme. Students check each other's prompts and artifacts, which speeds up learning and gives feedback from fellow practitioners.

HITL in every module

Human-in-the-loop is built in as a control layer, not as an extra step. If you accept an AI output without checking it, without finding and fixing the error, the assignment stays incomplete.

Final result: the AI Playbook

The final project comes together as a personal AI Playbook: a prompt library, a HITL checklist, a workflow map, an AI decision matrix, an implementation plan. Defence: 10 min + 5-min Q&A.

Duration

29 academic hours

Cohort size

Up to 20 people

Language

English

Platform

mktflow.online (access included)

Assessment

Ongoing 40% + Practice 35% + AI Playbook 25%

AI experience

Not required

AI tools

11 neural networks and platforms in the course

The course teaches principles, not tools. Along the way you get hands-on experience with a current AI stack for marketing.

GPT

OpenAI

Text generation, analysis, help structuring tasks.

Text AI

Gemini

Google

Multimodal AI, research, content creation with web search.

Text + Image

Perplexity

Perplexity AI

AI search with sources. Preferred for research with fact-checking.

Research

Claude

Anthropic

Low bias, natural tone, long context. Best suited for marketing copy.

Text AI

Kimi

Moonshot AI

Long context up to 200k tokens. Analysing large documents and reports.

Long Context

DeepSeek

A reasoning model for complex analytical and strategic tasks.

Reasoning

GLM

Zhipu AI

A multilingual model for coding and logical reasoning.

Multilingual

Qwen

Alibaba

Multimodal AI with mathematical and analytical reasoning.

Multimodal

DALL-E

OpenAI

Image generation for moodboards, concepts and visual communications.

Image AI

Veo 3

Google

Video generation. Video content for campaigns and product demos.

Video AI

Kling

Kuaishou

Video generation and editing. Realistic video material for marketing.

Video AI

A gift for participants

A large set of artifacts is a principle of the course

Every module produces a verifiable artifact. By the end of the course you have a working toolkit in hand, not lecture notes.

A prompt library as a gift when you enroll

Ready-made P.R.E.S.S. prompts for key marketing tasks: market analysis, competitive analysis, segmentation, TOV, content brief, strategy sessions. Every prompt is tested for reproducibility and comes with adaptation instructions.

Market Analysis PEST Competitors Segmentation TOV Content Brief Customer Persona Value Prop SWOT/TOWS

Available when you enroll

Completion document

MktFlow certificate of course completion

After defending your personal AI Playbook, you receive a MktFlow certificate for completing the "Marketing with AI" course. The document confirms specific competencies you've acquired, not just attendance at lectures.

Confirms 7 competencies and 13 specific skills
Issued after defending your personal AI Playbook
Signed by the course instructors
Includes a list of completed workflows and artifacts
Suitable for a resume and portfolio as a case study of applying AI to real tasks

Sample MktFlow certificate for completing the Marketing with AI course

Pricing

Cost

You can join with the first block for €120 and decide as you go whether to continue. The top-up to the full programme is €370 and opens when a group has open seats.

Block A

€120

5 modules, 13 hours

Core AI skills and the AI Toolkit
P.R.E.S.S. prompt framework
HITL verification checklist
Access to the mktflow.online platform
Continue with a €370 top-up

Full course

€1,200€490

15 modules, 29 hours, one-time payment

All three parts of the programme
Access to the mktflow.online platform
API keys for the training period
P.R.E.S.S. prompt library
MktFlow certificate
No VPN required

Corporate

On request

for teams of 3 or more

Case studies adapted to your industry
Corporate contract and closing documents
Group discount for 5+ participants

The €370 top-up is paid after Block A and depends on open seats in the group. We confirm your seat before payment.

Corporate training

Why send your marketer on this course

An employee who has embedded AI into their daily workflow speeds up analytical and communication tasks without losing quality and without becoming overly dependent on tools.

Faster analytics

Market research, competitive analysis and segmentation used to take days — now they shrink to hours, while verification and the quality of conclusions hold up.

A shared prompting standard

The P.R.E.S.S. framework helps the team speak to AI in one language. Instead of improvised requests, you use reproducible prompts. That makes results consistent and easy to check.

Managed quality

HITL verification lowers the risk of AI errors in strategic documents. An employee knows what to check and how, instead of blind trust or excessive caution.

Readiness for agentic AI

Part C builds an understanding of when an AI agent is needed and when ChatGPT is enough. That cuts spending on misdirected agentic implementations.

A portfolio of artifacts

By the end of the course, the employee has 15 working artifacts: a prompt library, a HITL checklist, an AI decision matrix. These are tools in daily use, not knowledge "in their head."

A corporate format

For teams of 3 or more, the course can run in a corporate format with cases adapted to your industry. Contact the MktFlow team for details.

Corporate training

Automation

AI in the marketing process: what it delivers

The course builds the foundation for moving to the advanced level: agentic automation of marketing functions. Figures from industry sources (Gartner 2025, Alvarez & Marsal 2026).

−60%

time on Keyword Research when switching to an AI workflow

+40%

conversion with AI-based lead qualification (Lead Qualification workflow)

+35%

engagement with Dynamic Content Generation and personalisation

81%

of market leaders are piloting agentic systems in marketing (Gartner, 2025)

Part C of the course lays the language for making automation decisions. The full cycle of implementing AI agents in the marketing function is covered in the advanced module. Access to it opens only after you complete the base course.

View the advanced level

Next level

Agentic Marketing: advanced module

After the base course, an advanced level opens up with the full cycle of implementing AI agents in the marketing function. From connectors and an n8n practicum to production operation with a governance framework.

Connectors and no-code data connections
n8n practicum: 4 working workflows
7 AI workflows for marketing with KPIs and HITL
Implementation, governance and 5 critical risks
APIs and the MCP protocol
Vibe-coding internal tools
Capstone: orchestrating a digital team of agents

Aimed at heads of marketing and those who have completed the base course and are ready to implement agentic workflows at their company. Enrollment opens after you complete the base course.

Frequently asked questions

FAQ

How is "Marketing with AI" different from typical courses on neural networks and prompts? +

We don't teach a list of tools — we teach how to embed AI into the full marketing cycle: from market analysis and segmentation to positioning, CJM and campaigns. Tools are treated as part of a system, not as an end in themselves.

Is this a course about tools, or about embedding AI into your daily marketing workflow? +

The focus is on workflow: you follow the path "real task → marketing methodology → AI as an amplifier." Tools are treated as part of the system, not as the goal. The course teaches principles, and they stay valid as tools change.

I've already tried ChatGPT and get generic outputs. How will this course help me work differently? +

You'll see how to turn "write a text" requests into a sequence of steps: research, hypotheses, verification. Then AI gives you structural marketing conclusions instead of generic phrases. That's exactly what the P.R.E.S.S. framework is built for.

What exactly will I be able to do after the course: audience analysis, briefs, strategies, CJM, campaigns? +

After the course you'll be able to do market and audience analysis, segmentation, customer journey mapping, positioning, brand modelling and the foundation of a communication strategy with AI, faster and more systematically, with verification at every stage.

What level of marketer does this course suit best — do I need strong analytics skills? +

The course is designed for practicing marketers with 3–7 years of experience: a basic marketing foundation is assumed, and we add the AI tools and methodology layer on top. Deep analytics knowledge isn't required.

Is it a fit if I've already taken AI courses but never embedded AI into my workflow? +

Yes, this is one of our key scenarios: we move from "knowing about AI" to specific working scenarios and standards you can implement in your daily tasks.

I've been in marketing a long time but have barely used AI. Will it be hard for me? +

If you're confident in marketing but new to AI, you'll manage just fine: we give you the AI foundation and immediately show you how to tie it to marketing tasks you already know.

How is the learning structured: how many modules, how much practice, how often are the sessions? +

29 academic hours, 15 modules across 3 parts (A: 13h, B: 14h, C: 2h). Split: lectures 45% / practicum 35% / lab sessions 20%. The exact schedule and weekly load are confirmed when you enroll.

How exactly do we work with a marketer's real tasks rather than abstract "for the course" examples? +

The core exercises are tied to the real cycle: market analysis, segmentation, positioning, product and communication strategy. You use AI on your own tasks, or ones as close to real as possible.

Will we work through my real projects (clients, brand, product), or only teaching cases? +

The course is designed so you can apply its approaches to your own tasks. Whether working through personal projects is mandatory or optional is something to confirm with the instructors when you enroll.

Will I learn to verify AI so I'm not afraid of hallucinations in research and strategies? +

Yes, the course includes a dedicated block on verification: how to cross-check AI conclusions, compare them against data, and avoid handing management raw or mistaken insights. You build the HITL checklist in module A3 and apply it in every module after that.

How does the course keep me from becoming someone who just copies prompts off the internet? +

We constantly work from classic marketing logic: first the task and the hypothesis, then framing the AI request, then critically evaluating the output. That way AI amplifies your decisions instead of replacing them.

Will my work actually get faster — which tasks specifically save time? +

The course is aimed at speeding up analysis, brief preparation, strategy drafts and supporting materials, cutting a chunk of routine work several times over. Exact time savings depend on your context and are calculated individually.

What will I have in hand by the end of the course — what can I show a manager or an employer? +

The goal of the course is for you to end up with a documented marketing case built with AI (research, hypotheses, decisions) that you can show internally at your company or in an interview. Plus 15 module artifacts and a personal AI Playbook. And of course our certificate.

Will the course strengthen my position in the job market if I'm a practicing marketer, not a CMO? +

You'll be able to honestly show experience applying AI to specific marketing tasks, rather than "I know ChatGPT." That kind of experience translates into cases, results and language that hiring managers understand.

How much support is there during the course — will assignments be reviewed and can I ask questions? +

The emphasis on practice means more than watching lectures. Confirm with the instructors which feedback format suits you — it can be individual, group, or cover only the key assignments. Our tutor takes care of any issues, and exchanging notes with fellow students in our chat is encouraged. You'll hear about all of this before enrolling.

What if I'm swamped with projects and occasionally miss sessions — can I go at my own pace? +

The availability of a flexible pace, deadlines and support mechanisms (chats, reminders, extra slots) is confirmed when you enroll. We'll walk you through the current intake format.

Will I keep access to materials and AI-in-marketing updates after the course ends? +

The policy on access duration and updates is confirmed when you enroll. Given how fast the AI field moves, this point matters, and we discuss it separately with every participant.

Want to use marketing tools and models the way they're meant to be used, only now with AI in the loop?

About the MktFlow platform

A platform for practicing workflows

Practicing marketers with 3–7 years of experience

Which AI-driven processes you'll master

Skill Set: 13 specific competencies

Instructors

What marketers say after the course

29 hours. 15 modules. Every module delivers an artifact.

How the course is structured

11 neural networks and platforms in the course

A large set of artifacts is a principle of the course

MktFlow certificate of course completion

Cost

Why send your marketer on this course

AI in the marketing process: what it delivers

Agentic Marketing: advanced module

FAQ

Enroll in the "Marketing with AI" course