Integrated Cloud Computing Platforms
Azure is Microsoft’s cloud computing platform where one can access cloud services including hosted applications, development tools, database management, business analytics, operating systems and other infrastructure-related services.
Microsoft is contributing to the race of bridging the cloud skills gap by providing various learning resources and a framework for higher education transformation. Microsoft Learn is a program that offers self-paced learning paths and certification (at a cost). It offers possibilities to customize learning paths in relation to job roles . The program offers modules that are relevant for all levels of learning.
The Microsoft Higher Education Transformation Framework for Higher Education allows academic institutions to leverage the advantages of Microsoft’s software ecosystem to enhance administrative processes and service delivery and by incorporating cloud technology in their taught curricula.
With Microsoft Azure, one can build, deploy, and manage applications with a comprehensive set of cloud services. It provides an open, flexible, global platform that supports multiple programming languages, tools, and frameworks and allowing researchers to achieve faster results.
Through AWS Educate learners can choose self-paced (paid) course content that suits their career choices/job preferences. These career pathways include Machine Learning, Data Science, Data Integration, Application Development, Web Development, Software Engineering, Cybersecurity Specialisation, DevOps Engineering, Solution Architecture and Cloud Support Engineering.
Through AWS Academy, academic institutions can freely access AWS authored, ready-to-teach cloud computing curricula that keeps pace with industry needs.
Google Cloud for Education offers resources, programs, and credits designed to enrich learning and discovery in higher education for students, faculty, researchers and administrators.
Students can benefit from career-readiness training, online labs and courses for hands-on learning and peer-to-peer learning through developer groups.
Administrators can leverage the cloud to enhance learning and research at their institution, to develop own individual cloud skills and knowledge, and to support the use of Google Workspace and Google Cloud Platform on campus.
Faculty can incorporate Google cloud course content, career preparation content and individual cloud skills into their curriculum, apply for credits and training discounts connect with fellow faculty and researchers.
Researchers can apply for up to $5000 in Google Cloud credits, allowing them to scale their research with greater speed, storage, and processing. They can strengthen achievements with certifications and collaborate with fellow researchers.
Nvidia Deep Learning Institute (DLI) offers self-paced online training courses; some free, some paid with certifications. Learners get access to fully configured, GPU-accelerated servers in the cloud to complete hands-on tasks included in the training such as building deep learning, accelerated computing, and accelerated data science applications for industries.
Developers, data scientists, researchers, and students can get practical experience powered by GPUs in the cloud, and IT professionals can access courses on designing and managing infrastructure to support AI, data science, and HPC workloads across their organizations.
DLI’s Educator Program provides teaching kits to qualified university educators interested in course solutions across data science, deep learning, accelerated computing, and robotics. Lecture materials, hands-on exercises, GPU cloud resources, and more can be integrated into the curriculum.
IBM supports cloud skills development through the IBM Skills Academy, a program that helps university (with signed agreement) faculty to provide students with additional skills, giving them an advantage in the job market. Students and educators can benefit from online self-paced courses, instructor-led training or hands-on lab through IBM cloud environment and regional specific free programs including one for Africa.
It also offers a learning approach for focused career paths designed on relevant market research, such as Big Data Engineer, Business Intelligence Analyst, Predictive Analytics Modeler, Security Intelligence Engineer, Cloud Application Developer, Artificial Intelligence Analyst, Blockchain Developer, IoT Cloud Developer and IBM Mainframe Foundations. Shareable badges can be obtained upon passing exams.
Databricks is an open and unified data analytics platform for data engineering, data science, machine learning, and analytics. It provides a feature-rich platform that allows one to perform quick exploratory data science or build machine learning models using collaborative notebooks that support multiple languages, built-in data visualizations, automatic versioning, and operationalization with jobs.
It also offers cloud skills learning paths and certifications through the Databricks Academy, extensive open resources for learning data science and technology, and documentation that is specifically relevant to the exploitation of AWS and Azure clouds.
EOSC was created to federate existing research data infrastructures in Europe and realise a web of ‘FAIR’ data and related services for science; it is an integrated platform that allows easy access to lots of resources for various research domains along with integrated data analytics tools. It offers infrastructure and resources aimed at supporting researchers with cloud services for data management, processing, analysis, compute, storage, security, and sharing and discovery.
Users can “grow their research knowledge and skills with specialised trainings or seek dedicated professional support for a wide range of scientific disciplines and research activities”.
The EOSC comprises various projects and implementation phases of which is the EOSC-hub that brings together multiple service providers to create a single contact point for European researchers and innovators to discover, access, use and reuse a broad spectrum of resources for advanced data-driven research.
SciServer is a fully integrated cyberinfrastructure system encompassing related tools and services to enable researchers to cope with scientific Big Data. SciServer enables a new approach to doing science by bringing analysis to the data; this will allow researchers to work with terabytes or petabytes of scientific data without needing to download any large datasets.
Cyverse is an open science workspace for collaborative data-driven discovery, enabled through interactive, web-based analysis; cloud infrastructure; web authentication and security services; data lifecycle management; resources for reproducibility, automation, and collaboration; gateway to scalable computational resources; education and training resources; and knowledge experts in all of the above.
It offers learning material through workshops, webinars and learning material.
TensorFlow is an end-to-end platform that makes it easy for you to build and deploy Machine Learning models. Whether it’s on servers, edge devices, or the web, TensorFlow lets you train and deploy your model easily, no matter what programming language or platform you use.
Through the TensorFlow Research Cloud program researchers can apply for access to a cluster of more than 1,000 Cloud TPUs. This cluster delivers a total of more than 180 petaflops of raw compute power, which can be used at no charge by researchers accepted into the program to accelerate the next wave of open research breakthroughs.
Colaboratory (‘Colab’), a product from Google Research, is an interactive environment that lets you write and execute Python code through the internet browser. Colab is a hosted Jupyter notebook service that is especially well suited to machine learning, data analysis and education. It requires no configuration to use, provides easy sharing and free access to computing resources. Colab notebooks execute code on Google’s cloud servers, meaning you can leverage the power of Google hardware, including GPUs and TPUs (using-accelerated-hardware), regardless of the power of your machine.
Specialised Platforms: Data Analytics
Power BI is a collection of powerful tools that are easy to use and highly collaborative to create rich, interactive reports and visualizations that one can manipulate, publish or share.
Tableau is an end-to-end solution to help people see and understand data from preparation to analysis to sharing insights. Tableau products aim to fit the needs of the user first, whether they’re an analyst, data scientist, student, teacher, executive, or business user, from connection through collaboration.
Data Studio is a data visualization tool from Google’s marketing platform, it allows you to create interactive dashboards and reports, and easily connect to your data from over 800 data sets and 400 connectors. Various customizable templates for reports are available for use and share with collaborators.