Two years ago, I embarked on a significant career goal: to become an AWS Machine Learning Hero. Today, I’m thrilled to share that this aspiration has become a reality. This achievement marks a pivotal moment in my professional journey, and in this article, I’ll detail the path I took, both the visible contributions and the behind-the-scenes efforts, focusing on how Aws For Machine Learning played a central role.
The AWS Hero program recognizes individuals who are deeply engaged and influential developers within the AWS community, particularly those making a substantial impact. This encompasses a diverse group of builders worldwide, each with unique skills and experiences, united by their passion for AWS technologies. Being recognized among such an impressive community is truly an honor, and I hope my experience can inspire others aiming for similar achievements within the AWS ecosystem, especially in the realm of machine learning.
Brooke Jamieson AWS Machine Learning Hero
The AWS Hero program spans various categories, including Community, Container, Data, DevTools, IoT, Machine Learning, and Serverless. These categories include conference speakers, open-source contributors, meetup organizers, authors, technical trainers, and content creators, all contributing to the vibrant AWS community.
Currently, I am among a select group of AWS Machine Learning Heroes globally, and within Australia, the number is even smaller. This recognition is a profound honor, and I aim to share insights that might guide you on your path to becoming recognized for your expertise in AWS for machine learning.
My Journey to Becoming an AWS Machine Learning Hero
In short: Dedicated and persistent effort! In detail: My journey was significantly shaped by my involvement as an AWS Community Builder, consistent content creation focused on AWS for machine learning, and active participation as a global conference speaker on related topics.
It’s important to note that my experience is just one perspective. The official AWS Hero website highlights key attributes of an AWS Hero:
- Enthusiasm: Regular participation and engagement within the AWS community.
- Expertise: Deep knowledge of AWS and continuous learning of new trends, particularly in areas like machine learning.
- Leadership: Building community relationships and fostering stronger connections.
While my approach worked for me, your path might differ. However, I hope my experiences offer valuable starting points, especially for those focusing on AWS for machine learning.
Leveraging the AWS Community Builder Program for Machine Learning Growth
The AWS Community Builders program is an exceptional initiative and played a crucial role in my professional development over recent years. This program, application-based, is highly recommended for anyone serious about deepening their AWS expertise. If applications are currently closed, joining the waitlist is advisable. For a comprehensive understanding, Stephen Sennett’s article ‘How to Become an AWS Community Builder’ provides excellent insights.
My year as an AWS Community Builder emphasized that the program prioritizes community building over solitary expertise. It’s about sharing knowledge and engaging with the community, both online and offline. Don’t let perceived technical gaps deter you from applying, but also recognize that strong technical skills alone might not suffice.
Essentially, possessing knowledge is valuable only when shared. The AWS Community Builder program is fundamentally about community engagement, particularly within the AWS for machine learning space.
Content Creation to Showcase AWS Machine Learning Expertise
In the tech world, continuous learning is essential, yet many delay developing crucial skills like creating concise and impactful content. I had been creating content, including ghostwriting, before joining the AWS Community Builders program. However, the program motivated me to significantly increase my output, particularly focusing on AWS for machine learning applications and insights.
I share content on platforms like dev.to, LinkedIn, Twitter, and TikTok. It’s important to reiterate that content creation isn’t a formal requirement for becoming an AWS Hero. It was simply a path I chose and enjoyed, allowing me to share my passion for AWS and machine learning.
My content creation is driven by genuine interest, not obligation. My TikTok content, for example, reflects my enjoyment in connecting with the community in creative ways. I even developed AWS-themed augmented reality TikTok filters, such as ‘Which AWS Service Are you?’ and an AWS Summit Crown. Were these requested or directly related to becoming an AWS Hero? Probably not. But they were fun to create and allowed me to engage with the AWS community in a unique and accessible way, highlighting the fun and engaging side of AWS for machine learning.
Conference Speaking: Amplifying AWS Machine Learning Knowledge
It’s crucial to emphasize: Neurodiversity or anxiety should not prevent you from pursuing conference speaking! Despite not being naturally outgoing, I’ve delivered over 40 conference talks and speaking engagements in recent years, many focusing on AWS for machine learning. Initially, even attending events was challenging due to anxiety. It was a gradual journey to gain confidence, starting from asking audience questions to eventually presenting my talks. It was challenging but incredibly rewarding.
For those interested in becoming conference speakers, I offer a freely available hour-long talk from NDC Sydney titled ‘How to Become a Tech Conference Speaker,’ detailing the process. Speaking at conferences is excellent for enhancing communication skills and increasing community involvement within the AWS machine learning community. Speaker passes often provide access to numerous events, allowing me to attend and learn from countless sessions and network with community members I might not have otherwise met. Conference speaking has also provided opportunities for international travel, an unexpected and enriching aspect. Starting is the hardest part, but the rewards are significant, especially for those passionate about sharing their expertise in AWS for machine learning.
Bringing It All Together: Community Leadership in AWS Machine Learning
The overarching theme is that becoming an AWS Hero seems to be about community leadership within the AWS ecosystem, not just excelling in private. It’s about creating valuable content, contributing positively to the global AWS Community, and demonstrating expertise in areas like AWS for machine learning. Engage with the AWS Community Builders, connect with Community & Developer Advocate teams in your region, participate in local AWS User Groups, and, most importantly, enjoy the process of learning and sharing your AWS machine learning journey.
There’s no single formula for success, but this approach worked for me. If you have questions, please leave them in the comments below.
About the Author: Brooke Jamieson is an AWS Machine Learning Hero based in Brisbane, Australia. To learn more about their journey as an AWS Developer, watch this video, or explore their profiles on LinkedIn, Twitter, Dev.to, and TikTok.
