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Content Roadmap


Content Roadmap
FY20 Q1 Content Roadmap


A brief overview of the content we plan for the next three months/what we have built already and how we go about prioritizing what to build for you next.


- [Andy] Hello Andy Larkin here, Head of Content at Cloud Academy. Welcome to our Q1 2020 roadmap. Now this is the content we plan to build over the next three months, between February 1st and April 30th. Now you can find our roadmap on the link in our menu bar. Meanwhile, here's a quick walkthrough to get you started. Let's look at some of our roadmap highlights. Now you asked for practical guides for applying DevOps tool chains at scale. So, we're doing a learning path using Atlassian Bamboo for CI/CD. And in this learning path, we'll help you learn how to use and manage Atlassian Bamboo for performing continuous integration and continuous deployment. We will provide you with not only the theory of how Atlassian Bamboo works, but also provide you with a detailed demonstration using a sample polyglot microservices based project, which itself utilizes technologies such as Java, Dotnet and Go. Now this learning path will include several hands-on labs that we'll train you to perform related to Atlassian Bamboo CI/CD tasks. Brilliant. Next up we've got Docker Certified Associate exam preparation, or the DCA. And this learning path will help you learn and prepare for the Docker exam. It will provide you with detailed information covering each subject domain, so this learning path will include several hands-on labs that we'll train you to perform tasks associated and assessed within the DCA exam. Another big ask was for Kubernetes Tools, and this Learning Path will help you extend your existing Kubernetes skill set, by introducing you to several important and popular tools found within the Kubernetes tooling ecosystem. We've got Helm, the package manager for Kubernetes, and this course will provide you with detailed insights as to how to use Helm to create and deploy packages into Kubernetes. Next we've got Istio, Kubernetes service mesh, and this course will provide you with detailed insights on how to use Istio to perform tasks such as request routing, fault injections, retries, rate limits, traffic control, traffic logging et cetera. Now the word Istio translates to sale in ancient Greek, which has absolutely nothing to do with the roadmap. Anyway let's press on with this learning path. We also cover KNative, which allows us to run serverless applications on Kubernetes. And this course will provide you with detailed insights as to how to use Knative to deploy and operate serverless workloads into Kubernetes, brilliant. Next up we've got AKS or Azure Kubernetes Service, and this Learning Path will provide you with the basic concepts involved with running and operating AKS based cluster. Now AKS is Microsoft's managed Kubernetes service and we will provide you with not only the theory of how AKS works but also detailed demonstrations, which take a sample polyglot micro service based application and deploy it into a newly provisioned AKS cluster. You've also asked for more site reliability in DevOps. So, we're doing the SRE, DevOps Site Reliability Engineering certification provided by the DevOps Institute, and this LP will include several courses following SRE principles in collaboration with the DevOps Institute, a fantastic Learning path. Okay another big ask was helping you leverage artificial intelligence and machine learning services. So, we've come up with an incredible curriculum of content, thanks to our relationship with QA. First off we've got data literacy. Now QA have developed a unique curriculum alongside Carolyn Carruthers, who's the author of "The Chief Data Officer's Playbook" and this content will help senior stakeholders understand how to deliver transformation value from their data. So this course will provide a rampup for executives and business teams looking to get started in the wider organization. We also include a learning path on practical big data analysis and this includes an introduction to Python, data science and Big Data, plus a deep introduction to the major Big Data technologies so this content will be ideal for people who are currently working as software engineers with data, or in business intelligence, looking to level up to the next stage of large data analysis skills in contemporary patterns of data science. We have a learning path practical machine learning and this is designed for people, who are already working on basic data science problems, and starting the statistical analysis of data with Python. This learning path will help you recognize and explain what a machine learning approach looks like in an organization. So, you'll learn how to implement different machine learning models, validate their quality and how to implement them practically. Another big ask we had was practical data science with Python. So, here's an introduction to statistics R Python analytics data science and machine learning, and this learning path sets up practitioners with working knowledge of the whole field of data science along with intermediate practical knowledge of key analytical tasks. So, it's gonna be ideal for fledgling data science practitioners or IT professionals, who wish to move to the exciting world of data analytics and machine learning. We're also covering the fundamentals of R with an introduction to the R language. R language is a mathematical and statistical modeling language used extensively in data analysis and big data. It's designed for anyone planning to work with large big data solutions, machine learning. By completing this learning path you will learn how to write programs using the R language, to create effective statistical outputs and to visualize data using R's library. Now there's a lot of content there, so we've wrapped this up in a data science 101 learning path/training plan. And this Learning Path will provide a far start for anyone wanting to dive straight into data science. It will be made up of all of this new content plus existing content and it will be designed to fast-track you from newbie to ninja with data science. Another big ask we had was for more development support. So, I'm very happy to announce our full stack developer learning path. It takes the learner through the front and back-end technologies with specific focus on some of the common frameworks. We're covering web development fundamentals with HTML and CSS JavaScript, bootstrapping, developing apps using Angular, developing apps using React JS, developing apps in service development with Node JS. All right now that's not to leave out all of our fantastic vendor specific content. We've got some very exciting certification goodies in the plan for Q1. So, we're doing the AZ-500, which is our Azure Security Technology Certification Learning Path. That will be completed this quarter. It's in preview currently, so you're able to get started with that. We'll be doing the AZ-400. In Q1, we'll be adding a substantial amount of Azure DevOps content to get you started on preparing for Microsoft's AZ400 exam. We're covering the AI-102 exam which will be a preview version of our Azure AI solutions certification learning path. Now Microsoft has announced that it will be changing its four most popular Azure exams. AZ-103, AZ-203, AZ-300 and AZ-301. So, we will have learning paths ready to help you prepare for these new exams. For GCP, we're adding yet another GCP certification path for you, this time for the Professional Cloud Developer certification. We're also redoing our AWS solutions architect associate learning path to be absolutely in line with the latest curriculum. We will be releasing AWS Data Specialty Learning Path and the AWS Data Analytics Specialty Learning Path. Exciting stuff coming in all of these domains. Okay so looking forward to seeing you in these learning paths. Get into it, looking forward to your feedback. Thank you very much. This is Andrew Larkin signing off.

About the Author

Learning paths50

Head of Content

Andrew is an AWS certified professional who is passionate about helping others learn how to use and gain benefit from AWS technologies. Andrew has worked for AWS and for AWS technology partners Ooyala and Adobe.  His favorite Amazon leadership principle is "Customer Obsession" as everything AWS starts with the customer. Passions around work are cycling and surfing, and having a laugh about the lessons learnt trying to launch two daughters and a few start ups.