Who We Are at Heraventos
We build structured, technically rigorous courses on neural networks and AI architecture for people who need working knowledge, not just theory. Our program covers everything from feedforward basics to transformer internals — the kind of depth that actually matters when you're building systems.
Elk River, MN — serving learners nationwide
How this program actually works
Most online courses on neural networks stop at intuition — diagrams, analogies, and surface-level code snippets. We didn't think that was enough, so we built something that goes further: each module combines conceptual explanation with hands-on architecture walkthroughs, so learners end up with understanding they can apply.
We offer both group cohorts and private one-on-one sessions. In group settings, learners work through material together, review each other's architecture decisions, and get instructor feedback in live sessions. Private tracks move at your pace and adjust around your existing background — useful for people who have some ML experience but gaps in specific areas.
The learning path is adaptive — after an initial assessment, the system flags which foundational concepts you're solid on and which need more work. That means less time on material you've already covered and more focus where it counts. We also use QBO intuit-style structured tracking internally to manage billing and learner accounts, which keeps the administrative side clean so instructors can focus entirely on teaching.
What we care about in instruction
- Accuracy over simplification — we don't hide complexity behind vague analogies when the actual math is learnable.
- Instructor accountability — every session is led by someone who has built production ML systems, not just taught about them.
- Pacing that respects your time — materials are structured so you can revisit specific modules without redoing entire units.
- Geographic fairness — learners in smaller states get the same session quality and instructor access as those in major metros.
We're always looking for instructors who combine domain depth with genuine teaching ability. If that describes you, see our open roles.
Nadine Okafor
Lead Curriculum Architect
Nadine designed the core neural network track after several years building inference pipelines at mid-scale ML teams. She reviews every module before release.
Vesna Kralik
Head of Learner Experience
Vesna handles how learners move through the program — from onboarding assessments to deciding when a group cohort vs. private track is the better fit.
