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📣 Feedback Form for Lecture 12
🌐 https://forms.gle/hNJvtZvS6dfmUj6w7
⏰ Deadline: Mar 23, 12 Midnight

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1.08K views08:33

📣 Ramtin Moslemi, one of the designers of Homework 5, explains the homework for you:
🎥 https://www.youtube.com/watch?v=rUBBmLP1Rdg

YouTube

Homework 5 | Model-Based Methods | Spring 25

Presented by Ramtin Moslemi
🔗 https://www.linkedin.com/in/ramtin-m

📂 Access the Homework:
🔗 https://deeprlcourse.github.io/homeworks/week5

Stay Connected:
✉️ deeprlcourse@gmail.com
🌐 https://deeprlcourse.github.io
📺 https://www.youtube.com/@DeepRLCourse…

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987 views20:31

Deep RL (Sp25)

📣 Website Updated with Last 2 Week’s Material!

✅ Lecture Materials for Week 5 & 6
✅ Course Notes for Week 3
✅ Workshop Video of Week 5 & 6
✅ Recitation Video of Week 5 & 6
✅ Recitation Materials for week 3-6
✅ Slides for Professor Foerster talk

🔗 https://deeprlcourse.github.io

deeprlcourse.github.io

Welcome - Deep RL Course

Welcome to Spring 2025 offering of Deep Reinforcement Learning course at Sharif University of Technology! We are excited to have you join us on this journey into the world of deep reinforcement learning.

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928 views02:35

Deep RL (Sp25)

📣 Website Updated with Last 2 Week’s Material! ✅ Lecture Materials for Week 5 & 6 ✅ Course Notes for Week 3 ✅ Workshop Video of Week 5 & 6 ✅ Recitation Video of Week 5 & 6 ✅ Recitation Materials for week 3-6 ✅ Slides for Professor Foerster talk 🔗 https:…

✅ Final Video of Lectures 9 & 10 are also out!

808 views10:44

Deep RL (Sp25)

📣 Homework 6 is out!
⏰ Deadline: Apr 6 (۱۷ فروردین) 11:59 PM (+3 Extra Days Until Hard Deadline!)

🌐 https://deeprlcourse.github.io/homeworks/week6

deeprlcourse.github.io

HW6: Multi-Armed Bandits - Deep RL Course

This page contains the homework assignment for Week 6 of the Deep Reinforcement Learning course, focusing on Multi-Armed Bandits.

😁4👍2

1.05K views10:44

Deep RL (Sp25)

📣 Solution for Homework 2 is Out!
🔗 https://deeprlcourse.github.io/homeworks/week2/#solution

deeprlcourse.github.io

HW2: Value-Based Methods - Deep RL Course

This page contains the homework assignment for Week 2 of the Deep Reinforcement Learning course, focusing on value-based methods.

1.02K views09:15

Deep RL (Sp25)

📣 Feedback Form for HW2
🌐 https://forms.gle/a6FfW23TARZMHyWQ8
⏰ Deadline: Apr 11, 12 Midnight

1K views09:17

Deep RL (Sp25)

📣 Mohammad Mohammadi, one of the designers of Homework 6, explains the homework for you:
🎥 https://www.youtube.com/watch?v=0i6zmVU7mj0

YouTube

Homework 6 | Multi-Armed Bandits | Spring 25

Presented by Mohammad Mohammadi
🔗 https://www.linkedin.com/in/mohammadmohammadi97

📂 Access the Homework:
🔗 https://deeprlcourse.github.io/homeworks/week6

Stay Connected:
✉️ deeprlcourse@gmail.com
🌐 https://deeprlcourse.github.io
📺 https://www.youtube.c…

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1.01K views16:47

Deep RL (Sp25)

📣 Quiz Solutions Now Available!

⚡️ Check them out in the Lectures section.
🌐 https://deeprlcourse.github.io

deeprlcourse.github.io

Welcome - Deep RL Course

🔥4❤2

807 views11:28

Deep RL (Sp25)

📣 Solution for Homework 3 is Out!
🔗 https://deeprlcourse.github.io/homeworks/week3

deeprlcourse.github.io

HW3: Policy-Based Methods - Deep RL Course

This page contains the homework assignment for Week 3 of the Deep Reinforcement Learning course, focusing on policy-based methods.

❤4

751 views20:45

Deep RL (Sp25)

📣 Solution for Homework 4 is Out!
🔗 https://deeprlcourse.github.io/homeworks/week4

deeprlcourse.github.io

HW4: Advanced Methods - Deep RL Course

This page contains the homework assignment for Week 4 of the Deep Reinforcement Learning course, focusing on Advanced RL Methods.

❤3👏1

793 views20:45

Deep RL (Sp25)

Lecture_12_Summary.pdf

402.3 KB

🎓 Summary of Lecture 12 📚

🔗 Quiz Link: https://forms.gle/h4k9ETs8PCT62TDx6
🕐 Deadline: 1:30 PM (before the class)

Stay on track and get it done! 🚀

👍1😁1

697 views04:32

Deep RL (Sp25)

📣 Screen Record of Lecture 13 is Out!
🎥 https://www.youtube.com/watch?v=mc6MTlxPePE

YouTube

Lecture 13 | Value-Based Theory | Spring 25 (Screen Record)

Welcome to the 13th lecture of our Spring 2025 Deep RL Course! 🚀
In this session, we dive into the Value-Based Theory🤖

💡 Want more resources?
Get the slides and extra goodies here:
🔗 https://deeprlcourse.github.io/lectures/week7

Stay Connected:
✉️ de…

❤1

690 views13:42

Deep RL (Sp25)

📣 Feedback Form for Lecture 13
🌐 https://forms.gle/e7wKGe6ghKEbjkKC7
⏰ Deadline: 12 Midnight

663 views13:43

Deep RL (Sp25)

📣 Course Notes for <Week 4: Advanced Methods> are Out!
🌐 https://deeprlcourse.github.io/course_notes/advanced

deeprlcourse.github.io

Week 4: Advanced Methods - Deep RL Course

This page delves into advanced reinforcement learning methods, focusing on actor-critic algorithms such as PPO, DDPG, and SAC. It explores key concepts like Reward-to-Go, Advantage Estimation, and Generalized Advantage Estimation (GAE), providing theoretical…

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650 views15:23

Deep RL (Sp25)

📣 Midterm Q&A Session with Prof. Rohban

We’ll be holding a Q&A session with Prof. Rohban this Tuesday from 12:30 to 1:15 PM, focused on questions related to the midterm.
If you have any doubts or need clarification before the exam, this is a great chance to ask!

🗓 Date: Tuesday
🕧 Time: 12:30 – 1:15 PM
👨‍🏫 Host: Prof. Mohammad Hossein Rohban

Make sure to join! 🚀

❤6👍1

770 views15:27

Deep RL (Sp25)

Lecture_13_Summary.pdf

258.7 KB

🎓 Summary of Lecture 13 📚

🔗 Quiz Link: https://forms.gle/8ve6qcc41f4VSwceA
🕐 Deadline: 1:30 PM (before the class)

Stay on track and get it done! 🚀

❤2🫡1

819 views04:29

Deep RL (Sp25)

📣 Midterm Q&A Session with Prof. Rohban We’ll be holding a Q&A session with Prof. Rohban this Tuesday from 12:30 to 1:15 PM, focused on questions related to the midterm. If you have any doubts or need clarification before the exam, this is a great chance…

📣 This session will be held in Class 201 of the CE Department

❤4

755 views04:39

Deep RL (Sp25)

📣 Homework 7 is out!
⏰ Deadline: May 11 (۲۱ اردیبهشت) 11:59 PM

🌐 https://deeprlcourse.github.io/homeworks/week7

deeprlcourse.github.io

HW7: Value-Based Theory - Deep RL Course

This page contains the homework assignment for Week 7 of the Deep Reinforcement Learning course, focusing on Value-Based Theory.