Reinforcement Learning 101 - World Model RL: 6th out of 6 Sessions

​Join our 1hour/wk x 6wk, Reinforcement Learning 101 study group, from basics to RLHF, World Model, and MiniMax & Others‘ RL-for-agents Framework, and coding up RL models, with our community friend teacher Colby (Ziyu) Wang (RL class TA in TMU) and 100+ registered classmates. Open to developer, ML engineer, and ML researchers.

Reinforcement learning matters because it helps AI agents make decisions in robotics, games, healthcare, and recommendation systems, and could be an important building block on the path toward AGI.

Also sharing the overwhelming feedbacks received during the session:
“This presentation was amazing, magnificent.” — Miris
“Thank you for a very nice presentation.” — Sachin
“Great presentation.” — Blush

Just finished 1st session last wk. Feel free to watch the recording: https://lnkd.in/etCkCThs
And watch the future recording in our community “Paper Reading Group” Section: https://lnkd.in/enYhHk_4
Register for next wks class at: https://lnkd.in/gpGQExxe
Code repo for the class: https://lnkd.in/eERpA8ju

Here is the Agenda:
Week 1 — Apr 4: Introduction to reinforcement learning — how AI learns through trial and error.
Week 2 — Apr 11: Value + Policy based RL — how AI scores actions and learns to choose better actions.
Week 3 — Apr 18: Value & Policy Hybrid RL — how AI combines scoring and action-taking.
Week 4 — Apr 25: RL in Agent — how MiniMax Forge trains agents for complex tasks.
Week 5 — May 2: RLHF — how human feedback helps AI become more helpful.
Week 6 — May 9: World Model RL — how AI imagines outcomes before taking action.

​Who is this for?

• ​Curious learners who want a gentle but serious introduction to reinforcement learning

• ​People with minimal coding experience who are willing to follow walkthroughs

• ​Anyone with a basic understanding of machine learning who wants to see how RL connects with LLMs and world models

​Logistics

• ​Format: Zoom

• ​Schedule: 1 hour per week, for 5 weeks

• ​First session: Saturday, April 4th

• ​Time: 12:00 pm EDT (New York time)

​If you’re excited about the future of decision-making AI and want to explore reinforcement learning in a supportive study group, we’d love to have you join us.

​About AI Scholars

​A peer-led learning journey for engineers, students, researchers, and builders.