KAUST Academy Artificial Intelligence Summer 2025

This is the base Repository for the KAUST Academy Summer School that will be held in two locations in the Kingdom of Saudi Arabia.

1. King Abdullah University of Science and Technology (KAUST)
2. King Khalid University (KKU)

Program Overview

The KAUST Academy Artificial Intelligence Summer School 2025 is designed to provide participants with an in-depth understanding of key AI domains, including Computer Vision, Reinforcement Learning, and Natural Language Processing. The program spans eight weeks, with dedicated modules of three weeks on Computer Vision, two weeks on Reinforcement Learning, and three weeks on Natural Language Processing. Through a blend of theoretical instruction and hands-on projects, students will gain practical skills and insights into emerging challenges across these core areas of AI.

Content

Week 1: Computer Vision I

Topic	Instructor	Lectures	Labs	Exercises	Solutions
Day 1 (RECAP): Convolutional Neural Networks	Prof. Naeemullah Khan	Slides	Lab 1 Lab 2	Exercise 1	Solution 1
Day 2: Unsupervised Learning Overview	Prof. Naeemullah Khan	Slides	Lab 3	Exercise & Solution Lab 3	Exercise & Solution Lab 3
Day 3: Autoencoders (AE)	Prof. Naeemullah Khan	Slides	Lab 4	Exercise 4	Solution 4
Day 4: Variational Autoencoders (VAEs)	Prof. Naeemullah Khan	Slides	Lab 5	Exercise 5	Solution 5
Day 5: Autoregressive Models	Prof. Naeemullah Khan	Slides	Lab 6	-	-

Week 2: Computer Vision II

Topic	Instructor	Lectures	Labs	Exercises	Solutions
Day 6: Object Detection	Dr. Tanveer Hussain (KAUST) Dr. Shaden Alshammari (KKU)	Slides	Lab 6a Lab 6b	within the lab	will be added after the lab
Day 7: Normalizing Flow Models	Dr. Tanveer Hussain (KAUST) Dr. Shaden Alshammari (KKU)	Slides	Lab 7	within the lab	will be added after the lab
Day 8: GANs (image-to-image translation)	Dr. Tanveer Hussain (KAUST) Dr. Shaden Alshammari (KKU)	Slides	Lab 8	Exercise 1 - MNIST Exercise 2 - Birds	will be added after the lab
Day 9: Conditional GANs, PixelCNN & WaveGAN	Dr. Tanveer Hussain (KAUST) Dr. Shaden Alshammari (KKU)	Slides	Lab 9	within the lab	will be added after the lab
Day 10: Diffusion Models	Dr. Tanveer Hussain (KAUST) Dr. Shaden Alshammari (KKU)	Slides	Lab 10	within the lab	will be added after the lab

Week 3: Computer Vision III

Topic	Instructor	Lectures	Labs	Exercises	Solutions
Day 11: RNN	Dr. Tanveer Hussain (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_11	within the lab	will be added after the lab
Day 12: Transformers	Dr. Tanveer Hussain (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_12	within the lab	will be added after the lab
Day 13: Vision Transformers	Dr. Tanveer Hussain (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_13a Lab_13b	Exercise 1	will be added after the lab
Day 14: Self-Supervised Learning	Dr. Tanveer Hussain (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_14	Exercise 1	will be added after the lab
Day 15: Contrastive Learning	Dr. Tanveer Hussain (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_15	within the lab	will be added after the lab

Week 4: Reinforcement Learning I

Topic	Instructor	Slides	Labs	Exercises	Solutions
Day 1: Introduction to Reinforcement Learning	Dr. Prashant Aparajeya (KAUST, KKU)	Slides	Lab_1a Lab_1b	within the lab	will be added after the lab
Day 2: DQN + SARSA	Dr. Prashant Aparajeya (KAUST, KKU)	Slides	Lab_2a Lab_2b	within the lab	will be added after the lab
Day 3: Policy Gradient (REINFORCE) + Actor–Critic	Dr. Prashant Aparajeya (KAUST, KKU)	Slides	Lab_3a Lab_3b	Exercise_1	will be added after the lab
Day 4: Proximal Policy Optimization (PPO)	Dr. Prashant Aparajeya (KAUST, KKU)	Slides	Lab_4a Lab_4b Lab_4c	Exercise_1 Exercise_2	will be added after the lab
Day 5: DDPG	Dr. Prashant Aparajeya (KAUST, KKU)	Slides	Lab_5	within the lab	will be added after the lab

Week 5: Reinforcement Learning II

Topic	Instructor	Slides	Labs	Exercises	Solutions
Day 6: Soft Actor Critic	Prof. Fabio Cuzzolin (KAUST) Dr. Prashant Aparajeya (KKU)	Slides	Lab_6	Exercise_1	will be added after the lab
Day 7: Model Based RL	Prof. Fabio Cuzzolin (KAUST) Dr. Prashant Aparajeya (KKU)	Slides	Lab_7	within the lab	will be added after the lab
Day 8: Exploration vs Exploitation Multiarm Bandits	Prof. Fabio Cuzzolin (KAUST) Dr. Prashant Aparajeya (KKU)	Slides	Lab_8	within the lab	will be added after the lab
Day 9: RL in Real World	Prof. Fabio Cuzzolin (KAUST) Dr. Prashant Aparajeya (KKU)	Slides	Lab_9a Lab_9b	within the lab	will be added after the lab
Day 10: Meta RL Open Problems	Prof. Fabio Cuzzolin (KAUST) Dr. Prashant Aparajeya (KKU)	Slides		within the lab	will be added after the lab

Week 6: Natural Language Processing I

Topic	Instructor	Slides	Labs	Exercises	Solutions
Day 1: Introduction to NLP	Prof. George Turkiyyah (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_1a Lab_1b	within the lab	will be added after the lab
Day 2: Vector Space + Word Embeddings	Prof. George Turkiyyah (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_2	within the lab	will be added after the lab
Day 3: RNN	Prof. George Turkiyyah (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_3a Lab_3b	within the lab	will be added after the lab
Day 4: RNN Improvements	Prof. George Turkiyyah (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_4	within the lab	will be added after the lab
Day 5: Seq2Seq Models	Prof. George Turkiyyah (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_5	within the lab	will be added after the lab

Week 7: Natural Language Processing II

Topic	Instructor	Slides	Labs	Exercises	Solutions
Day 6: Attention Mechanism	Prof. George Turkiyyah (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_6	within the lab	will be added after the lab
Day 7: Transformers	Prof. George Turkiyyah (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_7a Lab_7b	within the lab	will be added after the lab
Day 8: Transformers	Prof. George Turkiyyah (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_8a Lab_8b Lab8c	within the lab	will be added after the lab
Day 9: Large Language Model	Prof. George Turkiyyah (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_9	within the lab	will be added after the lab
Day 10: Prompting + RAG	Prof. George Turkiyyah (KAUST) Dr. Muhammad Mubashar (KKU)	Slides	Lab_10	within the lab	will be added after the lab

Week 8: Advanced Topics (NLP III)

Topic	Instructor	Slides	Labs	Exercises	Solutions
Day 11: NLP Recent Advancements	Dr. Salman Khan (KAUST, KKU)	Slides	Lab_11a Lab_11b	within the lab	will be added after the lab
Day 12: NLP Recent Advancements	Dr. Salman Khan (KAUST, KKU)	Slides	Lab_12	within the lab	will be added after the lab
Day 13: Multimodal & Code Generation	Dr. Salman Khan (KAUST, KKU)	Slides	Lab_13	within the lab	will be added after the lab
Day 14: Audio Processing In NLP	Dr. Salman Khan (KAUST, KKU)	Slides	[Lab_14]	within the lab	will be added after the lab
Day 15: Audio Processing In NLP	Dr. Salman Khan (KAUST, KKU)	Slides	[Lab_15]	within the lab	will be added after the lab

Instructors

• KAUST:
  • Prof. Naeemullah Khan
    • Week 1
  • Dr. Tanveer Hussain
    • Week 2
    • Week 3
  • Dr. Prashant Aparajeya
    • Week 4
  • Prof. Fabio Cuzzolin
    • Week 5
  • Prof. George Turkiyyah
    • Week 6
    • Week 7
  • Dr. Salman Khan
    • Week 8
• KKU:
  • Prof. Naeemullah Khan
    • Week 1
  • Dr. Shaden Alshammari
    • Week 2
  • Dr. Muhammad Mubashar
    • Week 3
    • Week 6
    • Week 7
  • Dr. Prashant Aparajeya
    • Week 4
    • Week 5
  • Dr. Salman Khan
    • Week 8

Teaching Assistants

• Ali Habibullah
• Abdallah Hammad
• Abdulaziz Alomair
• Abdullah Jan
• Abdulrahman Alfrihidi
• Ali Alqutayfi
• Dr. Amanat Kafizov
• Bader Alshamrani
• Daniel Alsadiq
• Harethah Abu Shairah
• Hassain alsayhah
• Hassan Alsayhah
• Dr. Kerven Durdymyradov
• Lama Ayash
• Mohamed Eltayeb
• Yazan Alshuaibi

🏆 Certification

Participants who successfully complete the program, meet the attendance requirements, and submit the final deliverables will receive a Certificate of Completion from KAUST Academy, signed by:

• Prof. Naemmullah Khan, Deputy Director, KAUST Academy | Instructional Assistant Professor, KAUST | Associate Research Fellow, LMH, University of Oxford
• Prof. Sultan Albarakati, Associate Vice President, Saudi Talent Development, KAUST

Final deliverables include:

• A comprehensive project report
• The project source code
• A presentation poster

Maintained by The Teaching Team