Wait a second, is it time to make our resolutions already? Well, we at Cloud Academy like to think ahead and we say yes – yes it's time. So instead of dreading the gaping chasm of uncertainty that is 2022, why not give yourself an opportunity to take some big, concrete steps in your career growth? We have a framework for your success. When you join Cloud Academy, you get our structured learning paths full of certification training, job role paths, labs, exams, and more.

In April, our Content Team released three new or updated learning paths, 15 courses, 18 hands-on labs, and six lab challenges! You can always find the latest content additions, as well as insight into what content we're working on next, on our Content Roadmap. A new set of machine learning labs has been added to the training library. These labs are based on the general machine learning concepts featured in the AWS Machine Learning certification. See the list of labs in the Data Science & AI section below.

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. 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. DevOps and IT professionals managing infrastructure across public, private, and hybrid clouds can use this learning path to get started with Terraform.

Is it possible to distinguish one class of samples from another, based on some set of measurements? Research investigating this and related medical questions have spurred innovation in medicine and the application of statistical methods and machine learning for decades. In this post, we'll address how to answer these questions using highly available, scalable, and easy-to-use cloud computing services that are included in Amazon Web Services (AWS). We'll start by guiding you through using Amazon Machine Learning to classify medical tumor samples as benign or malignant. Then, we'll explore other machine learning services and how they could be used to investigate medical questions.

Today, we'll be following up on our recent post on the Google Cloud Natural Language API. In this post, we're going to take a second look at the service and compare it to the Stanford CoreNLP, a well-known suite for Natural Language Processing (NLP). We will walk you through how to get started using the Stanford CoreNLP, and then we'll discuss the strengths and weaknesses of the two solutions. Artificial intelligence and machine learning are some of the hottest topics in IT. The major cloud platforms--Amazon Web Services, Google Cloud Platform, and Microsoft Azure--are increasingly exposing a variety of these functions in a way that makes it easy for developers to integrate them into their apps.

Today, we'll be following up on our recent post on the Google Cloud Natural Language API. In this post, we're going to take a second look at the service and compare it to the Stanford CoreNLP, a well-known suite for Natural Language Processing (NLP). We will walk you through how to get started using the Stanford CoreNLP, and then we'll discuss the strengths and weaknesses of the two solutions. Artificial intelligence and machine learning are some of the hottest topics in IT. The major cloud platforms--Amazon Web Services, Google Cloud Platform, and Microsoft Azure--are increasingly exposing a variety of these functions in a way that makes it easy for developers to integrate them into their apps.

In today's guest post, Alex Casalboni and Giacomo Marinangeli of Cloud Academy discuss the design and development of their new Inspire system. Our Challenge Mixing technology and content has been our mission at Cloud Academy since the very early days. We are builders and we love technology, but we also know content is king. Serving our members with the best content and creating smart technology to automate it is what kept us up at night for a long time. Companies are always fighting for people's time and attention and at Cloud Academy, we face those same challenges as well.

Speak with Alex Casalboni, Roberto Turrin and Luca Baroffio, a dedicated team inside our Engineering group at Cloud Academy, and learn how they use AWS to manage daily challenges and build a Machine Learning system. You'll learn: - How to deploy Machine Learning models in the Cloud. Start our 7-day free trial and enjoy the content: https://cloudacademy.com/