Added GPU Programming crash course

our-initiatives/tutorials/2024-2025/_category_.json

@@ -5,4 +5,4 @@
     "type": "doc",
     "id": "tutorials/2024-2025/index"
   }
-}
+}

our-initiatives/tutorials/2025-2026/_category_.json

@@ -0,0 +1,8 @@
+{
+  "label": "2025-2026",
+  "position": 2,
+  "link": {
+    "type": "doc",
+    "id": "tutorials/2025-2026/index"
+  }
+}

our-initiatives/tutorials/2025-2026/index.mdx

@@ -0,0 +1,69 @@
+---
+sidebar_position: 1
+---
+
+import DocCardList from '@theme/DocCardList'
+
+# 💻 Machine Learning Tutorial Series
+
+Welcome to season 4 (2024-25) of the beginner machine learning tutorial series of the UCL Artificial Intelligence Society!
+
+If you have any questions about our content or machine learning more generally, feel free to ask us at the next session or make a forum post on the [UCLAIS Discord server](https://discord.gg/KSUZuQx?ltclid=3f704b3b-9044-415a-a2d7-e41007214187). You can also join our WhatsApp group chat through this [link](https://chat.whatsapp.com/JWEJn7OWvWE8MBfm2uSBhh).
+
+## Our Team
+
+This academic year, the tutorial series is being delivered by the following people:
+
+- [Wana](#) (Head of Tutorials)
+- [Zachary Baker](#) (ML Officer)
+- [Paul Chaminieu](#) (ML Officer)
+- [Anna-Maria](#) (ML Officer)
+- [Franciszek Nowak](#) (ML Officer - Visual Computing I)
+- [James Ray](#) (ML Officer - Generative Visual Computing)
+
+## DOXA Challenges
+
+Our teaching will be supplemented by engaging AI competitions on [DOXA](https://doxaai.com/) related to topics such as visual computing, natural language processing and reinforcement learning.
+
+To take part and follow along with the tutorial series content, [sign up](https://doxaai.com/sign-up) to the platform if you have not done so already.
+
+## Weekly Tutorials
+
+📚 Access our notebooks, slides and recordings here!
+
+<DocCardList />
+
+## Timeline
+
+### Term 1
+
+During the first half term, we aim to cover basic concepts of **classical ML**:
+
+- Tutorial 0: **Introduction to AI**
+- Tutorial 1: **Introduction to Python**
+- Tutorial 2: **Regression**
+- Tutorial 3: **Classification I** (Doxa)
+- Tutorial 4: **Classification II** 
+
+After reading week, we will focus on **Deep Learning**!
+
+- Tutorial 5: **Neural Networks**
+- Tutorial 6: **Visual Computing I** (Doxa)
+- Tutorial 7: **Generative visual computing**
+- Tutorial 8: **Recurrent Neural Networks** (Doxa)
+- Tutorial 9: **Introduction to Transforments**
+
+### Term 2
+
+- Tutorial 10: **Natural Language Processing I**
+- Tutorial 11: **Natural Language Processing II**
+- Tutorial 12: **Graph Neural Networks / Reinforcement Learning**
+
+## Previous Seasons
+
+The content and resources from previous years are available on GitHub:
+
+- [Season 1 (2020/21)](https://github.com/UCLAIS/Machine-Learning-Tutorials) &ndash; led by [Danny Toeun Kim](https://github.com/kimdanny)
+- [Season 2 (2021/22)](https://github.com/UCLAIS/ML-Tutorials-Season-2) &ndash; led by [Martynas Pocius](https://github.com/MartynasPocius)
+- [Season 3 (2022/23)](https://github.com/UCLAIS/ml-tutorials-season-3) &ndash; led by [Filip Trhlík](https://trhlikfilip.com/)
+- [Season 4 (2023/24)](https://github.com/UCLAIS/ml-tutorials-season-4) &ndash; led by [Angela Yu](https://github.com/angela24680403)

our-initiatives/tutorials/GPU Computing Crash Course/_category_.json

@@ -0,0 +1,8 @@
+{
+  "label": "GPU Computing Crash Course",
+  "position": 2,
+  "link": {
+    "type": "doc",
+    "id": "tutorials/GPU Computing Crash Course/index"
+  }
+}

our-initiatives/tutorials/GPU Computing Crash Course/index.mdx

@@ -0,0 +1,61 @@
+---
+sidebar_position: 5
+---
+
+import DocCardList from '@theme/DocCardList'
+
+# 💻 Machine Learning Tutorial Series
+
+Welcome to the GPU programming Crash Course
+
+If you have any questions about our content or machine learning more generally, feel free to ask us at the next session or make a forum post on the [UCLAIS Discord server](https://discord.gg/KSUZuQx?ltclid=3f704b3b-9044-415a-a2d7-e41007214187). You can also join our WhatsApp group chat through this [link](https://chat.whatsapp.com/JWEJn7OWvWE8MBfm2uSBhh).
+
+## Our Team
+
+This academic year, the tutorial series is being delivered by the following people:
+
+- [Niall Dalton](#) (Workshop lead)
+- [Wana](#) (Head of Tutorials)
+
+## Resources
+
+A curated collection of resources for learning CUDA and GPU programming
+
+## Lectures
+
+**Lecture 1** – February 4, 2026
+- Location: Malet Place 1.03
+- [Slides](https://docs.google.com/presentation/d/1JgdmR_22HVcotAzSqckPpTBj2GyGADw62eUWs_iRybY/edit?usp=sharing) | [Colab](https://colab.research.google.com/drive/1NhzPcKumIunpd4fJzk_tSmcCyFVuCJ0q?usp=sharing) | [Colab Solutions](https://colab.research.google.com/drive/1WVQmMXAhcYjRnM4oeNkraO9SCiFK9KYs?usp=sharing)
+
+**Lecture 2** – February 11, 2026
+- Location: Malet Place 1.03
+- [Slides](https://docs.google.com/presentation/d/1esSJuDdzvHIs7k6ct7KOz1zlsjrXLt2cOSW3zMj3BVI/edit?usp=sharing) | [Colab](https://colab.research.google.com/drive/1ynqrlPfZLPIXRpcv9QzlDGMTvh7OR5BN?usp=sharing) | [Colab Solutions](https://colab.research.google.com/drive/1Xe2po0x8RE586C-0SWj_IpxrGWDYwyPP?usp=sharing)
+
+## Fundamentals
+
+- [CUDA C++ Programming Guide](https://docs.nvidia.com/cuda/cuda-c-programming-guide/) – Official NVIDIA documentation covering the CUDA programming model
+- [GPU Architecture Overview](https://developer.nvidia.com/blog/cuda-refresher-cuda-programming-model/) – Understanding SMs, warps, and the memory hierarchy
+
+## Courses & Tutorials
+
+- [GPU Puzzles](https://github.com/srush/GPU-Puzzles) – Sasha Rush's interactive GPU programming puzzles
+- [Stanford CS336](https://stanford-cs336.github.io/spring2025/) – Language Modeling from Scratch, covers GPU programming for LLMs
+- [GPU Mode Lectures](https://github.com/gpu-mode/lectures) – Community-driven GPU programming lecture materials
+- [UvA Deep Learning Tutorials](https://uvadlc-notebooks.readthedocs.io/en/latest/index.html) – Comprehensive deep learning notebooks with GPU optimization content
+- [PMPP Book](https://www.amazon.com/Programming-Massively-Parallel-Processors-Hands/dp/0323912311) – Programming Massively Parallel Processors, the classic textbook
+
+## Tools & Libraries
+
+- [cuBLAS](https://developer.nvidia.com/cublas) – GPU-accelerated BLAS
+- [cuDNN](https://developer.nvidia.com/cudnn) – Deep learning primitives
+- [Triton](https://triton-lang.org/) – Python-like GPU programming
+- [TritonParse](https://github.com/meta-pytorch/tritonparse) – Compiler tracer and visualizer
+- [Nsight](https://developer.nvidia.com/nsight-systems) – Profiling and debugging
+
+## Advanced Topics
+
+- [Memory coalescing and bank conflicts](https://developer.nvidia.com/blog/how-access-global-memory-efficiently-cuda-c-kernels/)
+- [Occupancy optimization](https://docs.nvidia.com/cuda/cuda-c-best-practices-guide/index.html#occupancy)
+- [Tensor cores and mixed precision](https://developer.nvidia.com/blog/programming-tensor-cores-cuda-9/)
+- [Multi-GPU programming](https://uvadlc-notebooks.readthedocs.io/en/latest/tutorial_notebooks/DL2/High-performant_DL/Multi_GPU/hpdlmultigpu.html)
+- [Ultra-Scale Playbook](https://huggingface.co/spaces/nanotron/ultrascale-playbook?section=profiling_gpu_compute_and_communication) – Profiling and distributed training