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I recently came across an amazing opportunity – the AWS AI/ML Scholarship program. But to qualify, I had to take on the AWS DeepRacer student challenge! It turned out to be a fantastic learning experience, even though it had its challenges.

Recipient Badge
Learning, Practicing, and Competing with DeepRacer#
DeepRacer offers a unique three-part approach: learn, practice, and compete. In the "Learn" section, I completed two modules and took a test. Thankfully, three attempts allowed me to brush up on my knowledge and reach the qualifying score of 24 out of 30.
Building and Training My DeepRacer Model#
The next step was the real fun – building my own DeepRacer model based on the learning modules. Don't be intimidated! While it sounds complex, the process was surprisingly manageable. The challenge lies in training the model to complete the track in under 3 minutes. This is where your training skills come in – the better you train, the faster your model will become.

Persistence Pays Off (Eventually!)#
Let me be honest, getting my model under the 3-minute mark was tough. There were moments I almost gave up on the scholarship altogether. But remember, you get 300 minutes of training time per month. Use them wisely! Crucial Tip: Don't rush through the learning modules. They hold the key to effective model training.
Reaching the Finish Line (and Beyond!)#
After three long months (phew!), I finally cracked the code and achieved my sub-3-minute goal! Once prequalified, AWS sends you the next steps. There's a form to fill out and questions to answer, and then you'll hear back from them.
Looking Forward: The AWS DeepRacer Student League#
The AWS DeepRacer student league is an annual event, so even if you miss out on the scholarship this time, there's always next year! Here's an article I found helpful on how to win the challenge. Article Link

Ready to Take On the Challenge?#
Head over to the AWS DeepRacer Website to get started. Good luck, and remember, persistence is key!
Originally published in picklebytes on LinkedIn.


