Your guide to leveraging AI capabilities in research
This course is designed to help researchers harness the power of cloud computing and artificial intelligence. Whether you're new to AI and cloud computing or ready to transfer your workflow to the cloud, we'll guide you through your learning journey step by step.
If this is your first time using this educational resource, we recommend you start with the fundamentals, then move on to the AI capabilities. Click on each section below to explore the modules.
Read through these four sections first to gain a solid understanding of the fundamentals of AI, cloud computing, and the Azure platform.
Learn about Microsoft Azure's cloud platform, its benefits, and how it can transform your research workflow. Understand what "The Cloud" means, who Azure is designed for, and when to use it.
Understand the basics of artificial intelligence and its use in research. Explore the AI timeline, types of AI applications, and basics of image recognition.
Explore the ethical considerations and responsible practices when using AI in research and academia. Learn about bias, fairness, transparency, and privacy considerations.
Get comfortable with the Azure portal interface and learn how to efficiently navigate and manage your Azure resources. Master cost management and budgeting.
Ready to explore AI tools? This path will take you through our all our hands-on content, where you'll learn practical AI implementation in the cloud.
Learn to set up and manage cloud-based virtual machines for your research computing needs. Scale your computational resources dynamically as your research demands change.
Build, train, and deploy machine learning models using Azure Machine Learning Studio's intuitive interface and drag-and-drop tools. No coding required for basic models.
Utilise Azure's pre-built AI services for vision, language, speech, and decision-making in your research without building AI models from scratch.
Explore advanced generative AI tools and learn to integrate cutting-edge AI capabilities into your research workflow. Master the latest in AI technology.
scryptIQ is an innovative education provider dedicated to addressing a persisting skills gap for research scientists: bridging their deep domain expertise with the latest advances in computational technology, data science, machine learning and AI. It is actively developing training programmes of its own, and collaborates with other providers to deliver bespoke, research science-adjacent computational education.
Originally developed at University College London, scryptIQ is an active collaborator with BBI Ltd., developing and delivering the Learn to Discover (L2D) course. L2D is a fully-supported training programme and platform dedicated to upskilling researchers in the biosciences, healthcare and medicine in Python programming, data science, machine learning and AI. Its primary focus is the application of these to real-world bioscientific data. If you want to learn more about how to powerfully incorporate and customise the concepts you learn in this course from scratch in Python, we invite you to take a look at the available L2D training.