This post has been republished via RSS; it originally appeared at: New blog articles in Microsoft Tech Community.
As part of the Applied Computational Science & Engineering MSc at Imperial College London we ran a interactive Learning day for the course participants to expand students’ skills in Machine Learning and responsible Artificial Intelligence.
Imperial College London, Faculty of Engineering, Department of Earth Science & Engineering utilises Microsoft Azure within their course. to enables our students to expand their Data Science experiences in relation to building and developing real world Machine Learning and Artificial Intelligence (AI) experiences. 
Students undertake modules on Numerical Methods and Advanced Programming, Applied Computational Science and Engineering MSc students have the opportunity to develop their Machine Learning and AI skills and then progress onto further advanced Machine Learning modules later in the year.
The MSc Advanced Computational Science Engineering course objectives include:
• To educate future domain-specialists in computational science.
• To impart knowledge and skills associated with cutting edge computational techniques for science and engineering applications.
• To use appropriate computational methods to understand, define and develop solutions to a range of science and engineering problems.
• Modern, sustainable software development
• Modelling dynamical processes & numerical methods
• Machine learning & optimisation methods
• Advanced programming & parallel algorithms
• Real-world problem solving using these skills and techniques & HPC resources
• To place students in an ideal position to:
• pursue academic careers (through a PhD for instance) in many fields: computational techniques, numerical analysis, optimisation and inversion, fluid mechanics, heat transfer, machine learning applications.
• work as an expert analyst in industry, for example extractive industries, climate science, engineering, finance.
Microsoft Supporting Students and Faculty
Microsoft is supporting students to use the cloud with an array of services and offerings, from online training, to Microsoft Student Partners who help fellow students, and global competitions, such as the Imagine Cup.
“It’s vital that today’s students learn how to capitalise on the ease of adopting the cloud and developer tools so young innovators can stay focused on their ideas and solutions for changing the world, rather than the tech. Learning skills while still studying in cloud and AI will give student technologists an advantage as they graduate and enter the workforce, especially on Microsoft’s Azure platform, which is used by 95% of Fortune 500 companies.” Jennifer Ritzinger, General Manager of Student Developer Advocacy
Self-learning
In preparation for the workshop, students developed a basic understanding of cloud technologies with Azure Fundamentals, a module on online learning platform Microsoft Learn .
Students have also had a chance to investigate some prebuilt AI on Azure, as well as using Python to develop tailored Machine Learning solutions and utilise Microsoft Learn, Azure Subscriptions and Azure Notebooks to undertake tutorials, modules and labs.
The students will also use Microsoft Learn to work through online tutorials at their own pace after the workshop, as self-learning or blended within the course curriculum.
Dr Gerard Gorman, Course Director for the Applied Computational Science and Engineering MSc says: “The nature of the course is that it must be very hands-on. Having Microsoft in for a day gives real world experience with AI that the students will develop in their independent projects, and in their careers after graduation.”
Workshop and Resources
During the day students will get hands on with the following Lab Workshop Hands on Lab resources which cover Azure Machine Learning designer, Azure Automated Machine Learning, Azure Machine Learning SDK (Software Development Kit) and AI developer services including Azure Cognitive Services.
These hands on labs sessions, help the students build machine learning models faster than they think might be possible, working on Open Source technologies, Microsoft Azure and Microsoft software development platform to enable cloud services.
The session allowed attendees to get hands on with the content in a lab format, to skill them in using prebuilt AI to solve business challenges, to learn more about Machine Learning and Artificial Intelligence and why it’s so powerful, and then dive into how to train and test baseline models.
Closing the event
Charlotte Yarkoni, Corporate Vice President of Commerce and Ecosystems at Microsoft, was interviewed by Imperial College, Microsoft Student Partner David Buchanan. David, is currently studying Mechanical Engineering Integrated Masters. David competed in the Imagine Cup UK finals in 2018, and became a Microsoft student partner soon after. The interview focused on cloud computing and inclusivity in technology industry.
Charlotte recorded the following short podcast with Victoria Murphy from the Department of Earth Sciences and Engineering.
Additional Resources
Microsoft Learn - FREE Learning Resources for Labs and Tutorials http://docs.microsoft.com/learn
AI ML Hands on Workshop Github Repo and Resources - https://github.com/leestott/ignite-learning-paths-training-aiml/tree/workshop
DP-100: Designing and Implementing a Data Science Solution on Azure - https://docs.microsoft.com/en-us/learn/certifications/exams/dp-100
Course DP-100T01-A: Designing and Implementing a Data Science Solution on Azure - https://docs.microsoft.com/en-us/learn/certifications/courses/dp-100t01
Microsoft Learn - Build AI solutions with Azure Machine Learning service - https://docs.microsoft.com/en-us/learn/paths/build-ai-solutions-with-azure-ml-service/