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295 Short courses in Machine Learning

Theoretical Foundations of Machine Learning
In his three-course Johns Hopkins Engineering's Theoretical Foundations of Machine Learning Dr. Erhan Guven guides you through the full machine learning workflow: from how to clean and prepare data all the way to building deep learning neural networks.

Continual Learning (Internship)
The goal of the Continual Learning (Internship) project from King Abdullah University of Science and Technology (KAUST) is to develop and improve the capability of the machine learning methods not to forget older concepts as time passes.

Foundations of Private and Fair Statistics (Internship)
The Foundations of Private and Fair Statistics (Internship) project at King Abdullah University of Science and Technology (KAUST) will explore basic statistical model or problems for different types of data in the differential privacy or fairness model.

Channel-Adaptive Machine Learning-Based mmWave Beamforming (Internship)
The Channel-Adaptive Machine Learning-Based mmWave Beamforming (Internship) project from King Abdullah University of Science and Technology (KAUST) focuses on integrating machine learning algorithms into mmWave beamforming to dynamically adapt to changing channel conditions.

Statistical Methods for Generative Modeling (Internship)
The Statistical Methods for Generative Modeling (Internship) project from King Abdullah University of Science and Technology (KAUST) aims to explore generative models based on Generative Adversarial Networks (GANs) and Normalizing Flows (NFs).

Scaling Graph Neural Networks to 1000s of GPUs (Internship)
This Scaling Graph Neural Networks to 1000s of GPUs (Internship) project from King Abdullah University of Science and Technology (KAUST) is to scale GNN training to thousands of GPUs. We will target our new supercomputer, Shaheen III, which is projected to include 2800 Nvidia Hopper super-chips than combine a CPU with a H100 GPU.

Machine Learning and Dynamical Systems (Internship)
Students of the Machine Learning and Dynamical Systems (Internship) project at King Abdullah University of Science and Technology (KAUST) will work on machine learning techniques applied to the study of dynamical systems.

Machine Learning for Graphs (Internship)
The Machine Learning for Graphs (Internship) project is offered at King Abdullah University of Science and Technology (KAUST).

Learning Generative Causal Models from Sparse Temporal Observations during Cellular Reprogramming (Internship)
This Learning Generative Causal Models from Sparse Temporal Observations during Cellular Reprogramming (Internship) project from King Abdullah University of Science and Technology (KAUST) covers how recent work on stem cells and different mature specialized cells in different systems/organs (neurons, blood cells,) has revealed a stunning plasticity and capacity of reprogramming cells.

Safety-Guaranteed Planning and Control for Autonomous Underwater Robots (Internship)
The Safety-Guaranteed Planning and Control for Autonomous Underwater Robots (Internship) project from King Abdullah University of Science and Technology (KAUST) explore learning-based planning/control approaches that combine optimization-based design and data-driven machine learning methods.

Deep Learning for Visual Computing (Computer Vision, Computer Graphics, Remote Sensing, Vision and Language) (Internship)
The Deep Learning for Visual Computing (Computer Vision, Computer Graphics, Remote Sensing, Vision and Language) (Internship) project from King Abdullah University of Science and Technology (KAUST) covers many topics but exact topic depends on the student's interest, background, and current research topics in the group.

Imagination Inspired Vision (Internship)
The goal of this Imagination Inspired Vision (Internship) project at King Abdullah University of Science and Technology (KAUST) is to focus on developing techniques that empower AI machines to see the world (computer vision) or to create novel products (e.g., fashion and art), hence the name Imagination Inspired Vision.

Accelerated Simulation of Reactive Flows Using Deep Neural Networks (Internship)
The Accelerated Simulation of Reactive Flows Using Deep Neural Networks (Internship) project from King Abdullah University of Science and Technology (KAUST) aims to develop an algorithm for accelerated computations by developing high fidelity reduced-order data-based chemical kinetics solver using autoencoder and neural network algorithm.

Fine-Tuning of Foundation Models via Low-Rank Adaptation and Beyond (Internship)
This Fine-Tuning of Foundation Models via Low-Rank Adaptation and Beyond (Internship) project is offered at King Abdullah University of Science and Technology (KAUST).

Next Generation Continual Learning (Internship)
Could you imagine the amount of real-world applications that could be developed if we extended this human ability to modern-day AI systems (especially deep neural networks)? Learn more with the Next Generation Continual Learning (Internship) project at King Abdullah University of Science and Technology (KAUST).

AI and Machine Learning for Business
This 6-week, part-time online AI and Machine Learning for Business course at University of Southampton will introduce you to the core capabilities of Artificial Intelligence (AI) and empower you to contribute to this exciting new era in global technological development.

No Code and Agentic AI
Within the No Code and Agentic AI course at Massachusetts Institute of Technology (MIT) you will learn AI and Machine Learning skills through an industry-relevant curriculum designed by MIT faculty, with in-depth modules on Generative AI, Responsible AI, and Agentic AI.

Deep Learning and Machine Intelligence for Single Cell Genomics (Internship)
This Deep Learning and Machine Intelligence for Single Cell Genomics (Internship) project from King Abdullah University of Science and Technology (KAUST) covers subjects such as single cell biology and genomics in particular are currently transforming the biosciences.

AI and Data Science - Leveraging Responsible AI, Data and Statistics for Practical Impact
Gain in-demand techniques in AI, Data Science, ML, and Generative AI to make AI-Powered Decisions and solve real-world business challenges with this AI and Data Science - Leveraging Responsible AI, Data and Statistics for Practical Impact programme from Massachusetts Institute of Technology (MIT).

Data Engineering with AWS Nanodegree
Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets. This Data Engineering with AWS Nanodegree program at Udacity is ideal for those with a basic understanding of Python, SQL, and command-line interfaces.