amazon web


services


complex digital product explained

  •
Amazon Web Services Logo
Course Development Copywriting Production Course Upload on Coursera

challenge

Get non-coders comfortable using machine learning software

Using machine learning, Amazon’s SageMaker Canvas software product helps non-coders answer important business questions. For example, how many customers might churn during the next quarter? And which customers are most at risk of churn? A concert venue or theater might want to know their chances of selling out seats in order to plan accordingly. Machine learning can answer those kinds of questions, among so many more.

Amazon Web Services (AWS) had a talented internal evangelist, touting SageMaker Canvas’s usefulness, both inside the company and externally at events like conferences. However, an evangelist is just one person. And as one person, their reach is necessarily limited.

In order to reach far more people, AWS brought us in to team up with their SageMaker Canvas evangelist to seamlessly create an asynchronous course. With an online course, AWS could now reach potential users anywhere and everywhere, at any time. Lessons would help users craft optimal business questions, followed by a software walkthrough to help them get the best answers.

solution

Content Development

We worked with AWS to identify the five pillars of course content and build learner profiles. We also helped them fine-tune the overall course narrative.

With AWS, we built an in-depth creative brief to ensure alignment on overall tone, target audience, and project outcome. We defined what was most important for the course, what was least important, and worked with the AWS team to create a full course outline. We also helped the team figure out what visuals might bring the material to life for learners. Edios’s development process helped the AWS team take the guesswork out of creating a learner-centric course with powerful outcomes.

Copywriting

Once the AWS team had scripts in hand, we brought in our writing team to help streamline the lessons and ensure a learner-centric experience. Our writing team has worked on myriad online courses, across subjects and companies. Our team pared the content down to its clearest, most important points, and helped ensure the language was accessible for the everyday, non-coder audience AWS wanted to reach.

  •

Production

In the leadup to the actual production, the Edios team coached the on-screen talent, building his confidence and providing best practices on how to give the best performance once the cameras start rolling. Many instructor-led courses lack visual contrast. We worked with the production team to optimize the AWS location and create a dynamic lighting scheme. We also worked with the production team to make sure filming included subtle motion, building a sense of drama, visual appeal, and movement to make the content more dynamic. We worked with wardrobe, hair, and makeup to ensure on-screen talent looked their very best in front of the cameras.

Course Upload + Publishing

We launched the course on the Coursera platform, using our longstanding knowledge of the platform’s ins and outs to ensure the course had all the necessary metadata and assets for a successful launch. We also created the shell, uploaded the course content, and tweaked it as the client made changes.

results

A dynamic course delivered on schedule.

AWS specifically liked the dynamic look and feel of the course, as well as the overall tone we achieved. We loved delivering the project on-budget and getting it live on Coursera right on schedule. We look forward to hearing AWS learner feedback and seeing usage statistics as they become available.

  • “With the help of no-code ML tools such as Amazon SageMaker Canvas, you can now achieve effective business outcomes using ML without writing a single line of code.“

    READ MORE | AWS News BLOG

  • Davide Gallitelli (Amazon Web Services) on Low-code No-code Machine Learning

    READ MORE | Ai.Nl.

The Latest

Stay up to date with the latest news and tips.