By Matt Robinson, Sr. Partner Solutions Architect at AWS
With the rapid growth in cloud computing over the last decade, machine learning (ML) has transformed from an aspirational technology to the mainstream and is making an impact across industries and verticals.
At Amazon Web Services (AWS), we see machine learning as a core component of tomorrow’s technology solutions. That’s why we are working with customers and AWS Partner Network (APN) Partners across the world to help accelerate this transformation journey.
AWS has developed several partner programs to help accelerate the process and enable you to drive value for your own customers through machine learning.
This post explores through two such programs available—APN Navigate, a comprehensive enablement program for APN Partners, and the AWS Machine Learning Competency, which validates and promotes a partner’s expertise in ML.
APN Navigate Overview
APN Navigate is an enablement program that provides prescriptive guidance from trusted AWS experts on how to transform your business on Amazon Web Services. Navigate provides a step-by-step path to help you build, market, sell, and specialize as an APN Partner.
All APN Partners can participate in the APN Navigate program to accelerate your business growth, regardless of where you are in your APN journey. Navigate equips partners with a roadmap, enablement tools, and resources to help you achieve your business goals.
Through the APN Navigate program, AWS is also able to gain visibility into a partner’s journey and collaborate on the most effective path forward. This includes weekly progress reviews, identification of next steps, and addressing any general questions on the APN Navigate program.
AWS Machine Learning Competency Overview
The AWS Competency program is designed to identify, validate, and promote APN Advanced and Premier Tier Partners with demonstrated AWS technical expertise and proven customer success.
The AWS Machine Learning Competency demonstrates that an organization has deep expertise in ML on the AWS platform, and can deliver their organization’s solutions seamlessly on the AWS Cloud.
Attaining the AWS Machine Learning Competency helps you market and differentiate your business to AWS customers by showcasing ML capabilities, skills, and successes.
There are two categories for the AWS Machine Learning Competency:
- APN Consulting Partners have demonstrated the ability to help large organizations solve the most challenging problems in artificial intelligence (AI). This includes work around data engineering, data science, machine and deep learning, and production deployment for inference at scale.
- APN Technology Partners provide ML solutions that help organizations solve their data challenges, enable ML and data science workflows, or offer SaaS-based capabilities that enhance end applications with machine intelligence.
As part of the AWS Competency program, APN Partners are vetted, validated, and verified against a high bar. Using APN Navigate, partners are provided a structure, process, and guidance needed to earn this Competency.
Using APN Navigate to Prepare for the ML Competency
Leveraging APN Navigate, partners can access tools and assets to simplify and streamline the process of achieving the AWS Machine Learning Competency.
Through APN Navigate, we offer partners end-to-end enablement to help train your team, understand the Competency process (including detailed checklists of activities), and receive prescriptive guidance on best practices when it comes to documentation associated with the application process.
The starting point for this process is enrolling in the Machine Learning track of APN Navigate. Whether your team is comprised of data scientists, ML researchers, or developers, AWS offers machine learning services and tools tailored to meet your needs and level of expertise.
Upon enrollment in APN Navigate’s Machine Learning track, your Alliance Lead will guide you through the process of accessing the APN toolbox of resources that can be used to kick start the ML Competency process. Within the toolbox, you’ll find assets such as deep-dive learning guides, how-tos for documenting case studies, and detailed information on program requirements for both APN Consulting and Technology Partners.
Recommendations for Enabling Your Team in ML
Machine learning is a broad subject area with many exciting areas to dive into. To most efficiently train your team, we recommend you focus on areas that will add the most value to customers, and then expand your expertise over time.
Rather than setting out from day one to master the complete ML ecosystem, focus first on your core competencies and developing ML skills in this space. As you identify new opportunities working with your customers, incrementally expand your capabilities into new domains with these advanced technologies.
Here are some recommendations based on our experience with working with APN Partners that have successfully leveraged APN Navigate to enable their teams in ML:
- Prioritize on specific ML domains based on demand from your customers
- Adopt a persona-based approach to training aligned with job role or focus area
- After building a foundational level of expertise across the team, specialize learning based on job role. Not all resources will need to be skilled in building ML models or data engineering. Through a persona-driven approach, you will get a more effective ROI on time invested in learning.
- Drive for use-case level mastery before service level mastery
- Service level expertise is valuable when delivering solutions for your customers, but understanding the optimum business use cases and scenarios in which to use services will be more beneficial to your customers.
- Focus on the end-to-end lifecycle of an ML solution
- Understanding the process to design, build, deploy, and operationally support an ML solution is an important but often neglected area. Areas such as ML Ops and how a machine learning solution will be securely deployed and supported are additional areas to focus on.
- Get hands on!
- In addition to structured learning and training, hands-on exposure and experimentation is critical in understanding how to effectively leverage ML.
- Some helpful exercises to get hands on can be found in the AWS Samples or AWS Labs GitHub, or by looking through example solutions in the AWS Machine Learning Blog.
Applying for the AWS Machine Learning Competency
For both APN Consulting and Technology, you must be an Advanced Tier partner to apply for the AWS Machine Learning Competency. At a high level, APN Partners are also required to cover the following areas as part of their application for the ML Competency.
AWS customer references/examples:
- APN Partners must have unique AWS customer case studies/examples specific to completed ML projects which are in production.
- At least two (2) of the provided customer case studies/examples must have a publicly available case studies.
AWS ML web presence and focus:
- APN Partners must have a microsite describing their AWS ML practice/AWS solutions with links to AWS customer references or case studies.
- APN Partners must also provide evidence of their ML capabilities and experience from either a consulting or solution perspective and any other relevant information supporting the your expertise related to machine learning.
- APN Consulting Partners must have at least six (6) employees (data scientists or ML practitioners) that have completed the AWS Solutions Training for Partners: Machine Learning on AWS – Technical course.
- APN Technology Partners must provide evidence they have field-ready documentation articulating their product’s value proposition to AWS customers. In addition, they must be able to offer product support via web chat, phone, or email support.
As the nature in which APN Partners leverage machine learning in customer solutions varies significantly, the exact requirements differ for each type of partner; hence the above criteria is an outline rather the full details of what is required.
For further information on the complete business and technical requirements required for each area, please see the validation checklist for the respective partner type (links to these documents can be found at the end of this post).
Best Practices for Your Application
To apply for the AWS Machine Learning Competency, APN Partners must submit a formal application covering the areas highlighted in the above section.
Based on our experience working with partners across many industries and domains, we have identified some best practices to help you move quickly through the application process:
- Focus on both the business and technical lens of your ML practice/solution
- The AWS Machine Learning Competency focuses on your holistic ML capabilities rather than just individual solutions, so ensure you highlight both of these elements comprehensively.
- When documenting case studies and your ML practice or solution, cover business elements such as customers outcomes, ML practice capabilities, team size, and technical elements like the technologies used in your solutions.
- Dive deep into your customer references
- A key area of any application is the ability to articulate in detail the technical solution delivered to customers. When documenting this solution, include all components and avoid summarizing areas of the solution as you would do for a non-technical audience.
- When reviewing your application, the AWS team will expect to dive deep; try to preempt this by providing technical details up front as part of your application.
- Leverage AWS-Well Architected to effectively document your solutions/case studies
- The AWS Well Architected Framework provides architectural guidance on how to build secure, high-performing, resilient, and efficient applications in the cloud. When the AWS team is reviewing your application, Well-Architected principles and best practices will be used to analyze the effectiveness of your architectures.
- The Machine Learning Lens of the Well-Architected Framework is an excellent asset you can leverage to produce a successful application.
- Use metrics and data to support your application
- At Amazon, we are a data-driven company and expect to see any relevant data points as part of your application. Areas we look to see quantified could be ML practice size, number of customers using the solution, or technical elements such as the accuracy percentage of your ML model.
- As a rule of thumb, include any and all data points which support your application or give perspective on the scale of a given solution.
- Clearly highlight the customer outcome and benefits of your solution
- ML can be a fascinating technical area, but it’s important we remain focused on the “why” of any solution and the value it brings to customers.
- Throughout your application, highlight the value your organization has delivered to customers (supported with data), and also the capabilities your organization possesses that enable you add value to new customers in the future.
In addition, APN Navigate for Machine Learning provides step-by-step guidance on case study and microsite development for AWS Competencies:
- AWS Competency Program: Public Case Study Guide (Partner Central login required)
- How to Build an Architecture Diagram (login required)
- How to Build a Microsite (login required)
How to Get Started
If your business is new to the AWS Partner Network and you are an APN registered member or higher, get started building your AWS-based business with the APN Navigate Foundations Path:
- APN Navigate overview
- APN Navigate Foundations Toolbox (login required)
- APN Foundations Deep Dive Resource Guide (login required)
To get started in APN Navigate’s Machine Learning track, a minimum number of five (5) business and five (5) technical individuals from your organization must complete key enrollment trainings. This will better equip your organization to complete the APN Navigate checklist activities and engage with AWS experts:
- APN Navigate Machine Learning Track – Business Training (login required)
- APN Navigate Machine Learning Track – Technical Training (login required)
Following this enrollment, Select, Advanced, and Premier Tier Partners can work with their Alliance Lead to begin the process of obtaining the AWS Machine Learning Competency.
The following assets are some helpful documents to deep-dive into the process and kickoff the path to the Machine Learning Competency:
- AWS Machine Learning Competency overview
- AWS Competency Partner Benefits (login required)
- AWS Machine Learning Competency Validation Checklist – Consulting (login required)
- AWS Machine Learning Competency Validation Checklist – Technology (login required)
- AWS Competency Application Readiness Checklist (login required)
We hope this post has given you good insight into the benefits APN Navigate can bring to your organization.
For more information about APN Navigate, the AWS Competency program, or any areas in which AWS can help you on your cloud journey, please reach out to your local APN representative.