Artificial General Intelligence, taught clearly
Structured lecture sequences on AGI built for people who want to understand the field — not just follow it. Delivered online, accessible from anywhere.
Built by researchers who stayed in the field
Navulser's instructors are not generalists who read about AGI. They are researchers and engineers who spent years working on specific, hard problems in machine learning, cognitive architectures, and AI safety.
Each lecture sequence is designed by someone who has published in the area they teach. The platform was founded in 2014 with that principle as its starting point, and it has not changed.
Oleksiy Bortnyak
Spent eight years on goal-directed reasoning systems before joining Navulser. Designed the core AGI theory sequence and teaches it directly.
Iryna Kovalchuk
Former research engineer at a European AI lab. Structures how concepts build on each other — so nothing gets introduced before you have the tools to handle it.
Dmytro Savchenko
Focuses on alignment theory and the practical limits of current approaches. Brings technical honesty to a topic that often gets oversimplified.
Referenced, not just reviewed
- 01 Cited in graduate syllabi
Several university courses on AI foundations have linked directly to Navulser lectures as supplementary material — without being asked.
- 02 Discussed in technical communities
Learners regularly share specific lecture segments in AI research forums when explaining foundational concepts to others.
- 03 Consistent over time
Content is reviewed and updated when the field moves. Nothing stays on the platform just because it was there before.
After the lectures end
The goal is not to produce people who can recite definitions. It is to build the kind of understanding that lets you read a new paper and know what question it is actually trying to answer.
Conceptual fluency
Knowing why a design choice matters — not just what it does. That fluency transfers to new problems the moment they appear.
Reading the field independently
Lectures are structured so you can follow primary sources — papers, technical reports — without needing someone to translate them first.
Calibrated skepticism
AGI claims range from careful to reckless. Finishing this material gives you the tools to tell the difference without relying on someone else's judgment.
Support that exists
Some parts of AGI theory are genuinely hard. The support structure here is not designed to make everything feel easy — it is designed to help you get through the hard parts without stalling.
Response times vary. The people answering questions are not automated systems. That means the answers are slower but more useful.
Instructor office hours
Scheduled sessions where you can ask about specific lecture content directly. Not a chatbot, not a FAQ page.
Peer discussion threads
Each lecture has a thread where learners at the same point in the material can compare their understanding.
Written clarifications
Submit questions in writing and receive a written response. Useful when you need to think through the answer rather than hear it once.
Not everyone belongs here
This platform works well for specific kinds of learners. Being honest about that saves time for everyone.
Tends to work well for
Not necessarily in AI — but comfortable with abstract reasoning, formal notation, and the idea that some questions do not have clean answers yet.
The material rewards re-reading. People who rush through to collect certificates tend to leave frustrated.
AGI is an open field. If you need every question resolved before moving forward, this will be difficult.
Likely a poor match for
There are faster ways to get a certificate. The work here is the point, not the document at the end.
Understanding AGI deeply is genuinely useful. Whether it leads to a specific job depends on far more than one platform can control.
The entry-level material exists, but it assumes you are comfortable learning from text and can sit with confusion for a while.
The distance between now and then
Most people arrive knowing AGI exists and that it matters. They leave knowing what the actual disagreements are, why they are hard, and how to keep up with a field that moves fast.
That is a specific, measurable shift. It takes time — typically several months of consistent work — and it does not happen automatically just by watching lectures.
Orientation — what AGI actually means
Clears up the terminology before anything else. Most confusion in this field starts with people using the same words to mean different things.
Core theory — how current approaches work and where they fall short
The bulk of the material. Takes the longest and requires the most re-reading.
Open problems — what the field is actually working on
Introduces the real research questions without pretending they are close to solved.
Independent reading — following the field on your own
The final stage is not more lectures. It is you reading primary sources and knowing what you are looking at.