Marketing Meets Machine Learning
We're teaching people how AI actually works in advertising—not the hype, the real mechanics. This program breaks down algorithms, data patterns, and automation tools that modern marketing teams rely on daily.
Explore Curriculum
Investment Structure
We've structured pricing to match different career stages and learning goals. Payment plans are available for all programs.
Essentials
- Core AI marketing concepts
- Data analysis fundamentals
- Campaign automation basics
- Weekly live sessions
- Project portfolio development
Advanced
- Advanced machine learning models
- Predictive analytics strategies
- Personalization algorithms
- Industry case studies
- Mentorship with practitioners
- Job placement resources
Mastery
- Full stack AI marketing
- Custom model development
- Team leadership training
- Strategy consultation hours
- Real client projects
- Lifetime alumni network
How We Actually Teach This
Most programs throw theory at you. We start with real campaigns and reverse-engineer them. Students see what worked, what failed, and why the algorithms made specific decisions.
Deconstruction Phase
We take successful campaigns from companies like Shopify and Slack—then break down exactly which AI components drove results. Students examine the data layers, targeting logic, and optimization loops.
Hands-On Building
Each student builds their own recommendation engine, trains a customer segmentation model, and creates automated bid strategies. You'll work with Python notebooks and actual marketing APIs.
Live Testing Cycles
We run simulated campaigns using historical data from real businesses. Students compete to optimize performance metrics—CTR, conversion rates, ROAS. The feedback is immediate and unforgiving.
Portfolio Development
By the end, you have case studies showing measurable improvements. These aren't theoretical projects—they're work samples that demonstrate you can analyze data and make strategic calls.
What Students Actually Say
These are people who finished the program and moved into roles at agencies, tech companies, and marketing departments. We asked them to be honest about what worked and what didn't.
I came from a traditional advertising background. This program forced me to think differently about targeting and measurement. The instructor wouldn't accept vague answers—you had to show your work with the data.
The case studies were intense. We'd spend three weeks on one campaign, testing different models and comparing results. It felt like real consulting work, not academic exercises.
What surprised me most was learning which AI tools actually matter versus which ones are just marketing noise. The instructors have worked at places where budgets are real and results are measured ruthlessly. They taught us to ask hard questions about every tool and technique.
The Python portion scared me initially. But they teach it in context—here's the business problem, here's how code solves it. After a month, I was comfortable manipulating datasets and building basic models.
I interviewed at four agencies after finishing. Every single one asked about my portfolio projects from this program. Having concrete examples of optimizing campaigns with machine learning gave me credibility I didn't have before.