According to LinkedIn’s “Jobs on the Rise” report – Artificial Intelligence and Machine Learning are the top skills driving job growth. Reportedly, there has been a 75% increase in postings over the last four years. Surprisingly, there is no sign for this trend to slow down! Experts are predicting a 200% surge in Machine Learning job opportunities by 2030. Thus creating a huge demand for professionals (educators and IT pupils) trained in ML specifics. As a result, institutes are planning on expanding their course curriculum in ML and AI. Most importantly, they are giving it all to transition to the cloud, enabling students and educators to be on the same page with resources shared and knowledge gained.   

What is Machine Learning? A Quick Overview 

A popular subset of AI, Machine Learning, is all about creating intelligent machines that can learn from experience, eliminating the need for explicit programming. The particular is an advanced analytical model creation technique, based on data parsing and analysis. It keeps on searching for patterns and continues to make informed decisions, often with minimal human intervention.  

Why are Institutes More Interested in Launching Machine Learning Course Curriculum Based on The Cloud? 

By shifting the Machine Learning course curriculum to the cloud, institutes can tap into a host of compelling benefits.  

• It becomes easy for institutions to experiment with their machine learning course capabilities and scale up as the demand increases. 
• Moving to the cloud also makes it easy for educators and learners to stay connected and continue learning at their own time and convenience.  
• On the cloud, institutes can let their students leverage multiple pre-configured environments – AWS, Microsoft Azure, and Google Cloud Platform without it being mandatory for the latter to have deep knowledge of AI, or machine learning.  

Things to Consider Before Moving Your Machine Learning Course Curriculum to the Cloud 

Here is a quick walkthrough of all the key points that institutes should consider before moving their Machine Learning Course Curriculum to the cloud:  

• Enhanced Flexibility in terms of Resource Allocation: ML training involves experimenting with various hyperparameters, configurations, and algorithms. With the course based on the cloud, students should be able to easily deploy and get access to virtual machines/labs from any Operating System of choice (Linux/Mac/Windows). This flexibility allows enhanced exploration of the model space and improved performance. 
• Availability of Pre-configured Hands-On Lab Environments: The cloud provider must offer access to specialized pre-built labs for ML courses. Where the labs should be self-paced, simple to set up and come equipped with detailed lab guides. 
• Complete Privacy: By utilizing cloud resources, institutions should be able to benefit from enterprise-grade security (Microsoft SSPA, SOC2 Type 2, Penetration Testing, GDPR, and CCPA), eliminating the need for in-house expertise or infrastructure. ML coursework and training often involve personally identifiable information. Cloud service providers must employ stringent security measures, including access controls, data encryption, and compliance certifications, to ensure complete confidentiality.  

The CloudLabs for EDU Experience 

Continue with the reading task to understand how CloudLabs for EDU revolutionizes training in Machine Learning, helping institutes move and continue offering ML courses to the cloud.  

• Complete Catalog of Pre-Configured Labs – Institutes get to choose from a complete catalog with pre-configured labs suitable for Microsoft Certification Courses, Azure Advanced Bootcamps, Check Point, Cyber Security, SEED, and AI & Machine Learning courses. 
• ZERO Hardware/Software Dependencies – The labs are easy to deploy! Participants are FREE from additional software or hardware dependencies. All you need is access to a PC with a browser and a stable internet connection.  
• Shadow VM – Instructors/Educators can connect to the participants’ labs in no time, offering quick solutions, reviewing their progress, and providing targeted feedback.   
• Lab Validation – With the feature added, it gets easy to monitor student progress and track lab completion.   
• Compatible with Different Use Cases – The easy-to-deploy labs stand suitable for multiple use cases Programming & Cyber Security, Data Science, Machine Learning, Artificial Intelligence, DevOps & System Administration, Hackathons and Secure Research. 
• Multi-platform Compatibility – Hands-on labs are compatible with AWS, GCP, Azure, Jupyter, M365, MS Teams, Power Platform, and VS Code environments. 
• Advanced Admin Controls – Admins can schedule lab uptime, track consumption, and monitor lab credits with complete automation. Labs, when left idle for a certain period (admins can define the time), will automatically shut down. Thus saving on resources and cost.  
• 24×7 Support – A dedicated team of professionals is available 24×7, offering quick resolutions to technical complexities faced by the participants when operating labs.  

CloudLabs Helps Wayne Community College Deliver an Impactful Learning Experience in Machine Learning and AI With Its Pre-Configured AI-900 Labs 

Wayne Community College was able to find a self-paced pre-configured hands-on lab solution for their CSC 215 – Machine Learning program. The institute and its learners were introduced to pre-built AI-900 labs, including 17 modules per user. Also, the labs came complete with practice tests and detailed guides. 

Here is a complete list of requirements that the institute put forward: 

• All-encompassing instructional materials that would guide students through lab tasks.  
• Wayne Community College wanted to help faculty members dedicate substantial time to high-priority work rather than only developing course materials and managing resources. Also, the concern was to deal with scarcity of resources.   

The world is full of data, and machine learning (ML) with time is transforming into an essential skill, required to harness the true power of data converting it into knowledge. However, for people to be able to continue with the conversion, it is essential for them to get trained in ML and educational institutes launching ML training courses on the cloud are only making things easy. To help them in the process, CloudLabs has come up with pre-configured self-paced labs, which can be customized as well. 

Wayne Community College is already a part of our cloud success! You can be the next.  

To get a hands-on experience of our labs, book a demo with us! 

You can also download the case study here, in case you want to get a complete overview of the solutions offered by CloudLabs to Wayne Community College.