AI & ML Primer

After many years of helping clients with a wide range of data and analytics challenges, we see very few clients doing data well. Often, they:

• Want to take advantage of AI & ML but know their data isn’t ready – so they get stuck at the first step.
• Aren’t quite sure where to start on their AI & ML journey – suffer from too many choices.
• Have tried, unsuccessfully, to build an AI&ML capability and need a reset – over focused on technology.

All of this causes delay in gaining traction and finding the benefits from cloud AI & ML.

Our simplified and pre-packaged approach will deliver an outcome.

• You will gain practical experience with how a contemporary cloud AI & ML platform works
• Together we will explore a range of types of AI & ML, connecting it to problems that matter to your business

We can do this in just a few weeks.

We call it the AI & ML Primer.

We have reduced the wide variety of AWS AI&ML components capabilities up into three distinct business-facing use cases:

• Predict/forecast (See)
• Discriminate/classify (Sort)
• Generate/create/interact (Say)

We allow customers the choice to focus either on a single use case in more depth, or sample across all 3 use cases, depending on their interest.

We also include a summary report based on the learnings from the Primer which helps customers understand the next steps into projects and production.

The AI&ML Primer uses a templated environment provisioned via Infrastructure-as-Code (IaC). Off-the-shelf ML models are applied, with modest adjustments to suit the customer’s data and use case. Products used are:

• Amazon SageMaker
• Amazon Forecast
• AWS DeepLens
• Amazon Bedrock
• Amazon Q
• Amazon Simple Storage Service (S3)
• AWS Glue, Athena and Kinesis
• AWS CodeCommit and CodePipeline
• Amazon EventBridge
• Amazon Simple Notification Service (SNS)
• Amazon QuickSight or Microsoft Power BI
• AWS Identity and Access Management (IAM)
• Amazon Virtual Private Cloud (VPC)
• AWS Cost Explorer
• AWS CloudTrail
• Amazon CloudWatch