A 2017 IDC White Paper “recommend[s] that organizations that want to get the most out of cloud should train a wide range of stakeholders on cloud fundamentals and provide deep training to key technical teams” (emphasis ours). Regular readers of the Cloud Academy blog know we’ve been talking about this for a long time. Future-proofing your organization requires technical excellence, collective experience, business context, and shared understanding. In a word, culture.
Cloud Academy’s latest Learning Paths go broad and deep—covering CI/CD, machine learning, AI, big data, and even preparation for the first AWS certification designed for non-technical staff.
Here’s what’s new on Cloud Academy:
Solving Infrastructure Challenges with Terraform
DevOps and IT professionals managing infrastructure across public, private, and hybrid clouds can use this learning path to get started with Terraform. You’ll learn when to use it, the ins and outs of configurations, and how to work with providers and resources.
Applying Machine Learning and AI Services on AWS
This learning path will help those with some machine learning experience to begin applying core Machine Learning and Artificial Intelligence services available on the AWS platform including Amazon Rekognition, Amazon Lex, Amazon EMR, and more.
Machine Learning on Google Cloud Platform
Neural networks are the hottest approach to machine learning, and TensorFlow is the most popular toolkit for building them. Both come together on Google Cloud Machine Learning Engine. This learning path will help you get started building and training neural networks with TensorFlow and Google Cloud Machine Learning Engine.
AWS Developer Services for CI/CD
AWS developer tools and services take much of the undifferentiated heavy lifting out of building a DevOps practice with a structured CI/CD process. This learning path focuses on the practical and hands-on knowledge teams need to understand, operate, and master running DevOps processes on AWS Developer Services.
Cloud Practitioner Certification Preparation for AWS
For sales, marketing, finance, and other non-tech roles, this learning path trains the cloud basics and the most important AWS products from a business perspective, including hands-on experience in compute, storage, databases, and networking.
Big Data Analytics on Azure
Azure’s robust services make it easy and cost-effectivee to incorporate big data analysis into your cloud applications. This learning path focuses on getting your team up to speed using two key Azure services: Data Lake Analytics and Stream Analytics.
Assign these Learning Paths with a Training Plan, customize them with Content Engine, or stop by our booth at AWS Summit London on May 9-10 to discuss how you can use all three to power your teams up the cloud capability curve.
Explore all of our learning paths, courses, and hands-on labs in the Cloud Academy Content Library.
AI and Machine Learning: How They Are Changing the Content Industry
Machine learning falls under an array of artificial intelligence (AI) technologies that learn how to do certain tasks with the intention of automating them. These systems use historical data to predict future patterns and execute their tasks according to accurate data gathered. The more...
Cloud Academy Content Roadmap Updates
Welcome to our Q1 2020 roadmap. This is the content we plan to build over the next three months, between February 1 - and April 30, 2020. Let's look at some of our roadmap highlights. Atlassian Bamboo for CI/CD We had a lot of requests for practical guides on how to apply DevOps tool...
AWS Machine Learning Services
The speed at which machine learning (ML) is evolving within the cloud industry is exponentially growing, and public cloud providers such as AWS are releasing more and more services and feature updates to run in parallel with the trend and demand of this technology within organizations t...
What is Deep Learning and Does Your Enterprise Need It?
What is Deep Learning? The most frequent question asked by my students is: Do I need to learn deep learning? Beyond the buzzwords bounced back and forth in blog posts and news articles, deep learning is probably the most revolutionary technology of the last century. Discovered in the ...
4 Key Takeaways from Google Cloud Next ’19
Google Cloud Next ’19 was the flagship Google Cloud Platform developers conference, held in San Francisco’s Moscone Center. I was lucky enough to attend it with Cloud Academy, and got the chance to check out tons of breakout sessions and get great insight firsthand. Next ’19 was my...
How to Build an Intelligent Chatbot with Python and Dialogflow
Chatbots are a powerful example of artificial intelligence (AI) in use today. Just think about Google Assistant and how intelligent the platform became thanks to machine learning. But, what is a chatbot? How do you create a custom bot for your website? Which technologies can you use to ...
What is Azure Machine Learning
The meal was fantastic, the service was friendly and professional, the setting was cozy, and the company was engaging. As the evening ended, however, there was a slight hiccup as my credit card was declined. There was more than enough money in my account to cover the cost of the (very d...
Microsoft Ignites Cloud Industry With Nadella Keynote
On Monday, Microsoft kicked off its Ignite conference, an annual gathering of developers and IT professionals. Over the next week, attendees will learn about upcoming Microsoft innovations in IoT, artificial intelligence, machine learning, and cloud (all while getting some good networki...
What are the Benefits of Machine Learning in the Cloud?
A Comparison of Machine Learning Services on AWS, Azure, and Google Cloud Artificial intelligence and machine learning are steadily making their way into enterprise applications in areas such as customer support, fraud detection, and business intelligence. There is every reason to beli...
AI-Driven Automated Testing to Enhance Continuous Delivery
The demand for continuous delivery has changed the approach to development and release tools, especially in keeping up with the high demand of DevOps and agile development practices. This has coincided with the emergence of artificial intelligence (AI) and subsequent AI-driven automated...
Top Cloud Skills in Demand for 2018: Big Data, AI, Machine Learning
Cloud is a pathway to innovation. Where yesterday’s cloud deployments were about moving an on-premises infrastructure in your data center to a cloud environment, companies today are using cloud platforms to build new features for their products and services that are integrated at a soft...
New on Cloud Academy, March ’18: Machine Learning on AWS and Azure, Docker in Depth, and more
Introduction to Machine Learning on AWS This is your quick-start guide for building and deploying with Amazon Machine Learning. By the end of this learning path, you will be able to apply supervised and unsupervised learning, ML algorithms, deep learning, and deep neural networks on AW...