This is about my experience participating in the #30DaysOfGoogleCloud programme, run by SRM Ramapuram Developer Student Club (DSC) 2019–2020 via Google Qwiklabs.

I heard about the program on LinkedIn and through a WhatsApp message, applied via a Google Form, and got in within a few days. In Qwiklabs, quests are series of labs organized by technology or use case, and you earn a badge by completing them. The program had two tracks.

1. Cloud Engineering Track

Six quests, each ending in a challenge lab: creating and managing cloud resources (VM instances, Kubernetes basics, load balancers), cloud storage/monitoring/IAM, setting up a full cloud environment (BigQuery, Cloud SQL, VPC networking), deploying and managing with Kubernetes and Deployment Manager, building and securing networks (IAP, load balancers), and finally deploying Kubernetes to the cloud with Docker and Jenkins pipelines. Most challenge labs were framed around a fictitious company, Jooli Inc.

2. Data Science and Machine Learning Track

Also six quests: a platform overview, fundamental AI/ML tasks (Dataprep, Dataflow, Dataproc, NLP/Vision/Speech APIs), BigQuery and Data Studio (including a challenge analyzing COVID-19 data), engineering data pipelines (IoT analytics, BQML, TensorFlow for housing price prediction), integrating ML APIs (image captioning, entity/sentiment analysis), and finally explainable AI with the What-If Tool for bias and fairness checks.

Every quest followed a 6+1 or 7+1 pattern — six training labs building up to one challenge lab, with YouTube videos to help if you got stuck.

Note: if you get stuck, YouTube can help — but don't lean on it too heavily, or you won't actually learn the material.

After finishing both tracks, I filled a form for swag (t-shirt, laptop bag) which took a couple of months to arrive — the laptop bag turned out too small for my gaming laptop. A certificate followed by mail shortly after.

So what's next?

These tracks are the foundation for the Associate Cloud Engineer (ACE) exam. Cloud computing keeps playing a bigger role in handling big data, especially for data analysts — companies like Accenture and Polycab have been investing heavily in cloud infrastructure. If you're serious about this path, don't skip the fundamentals: Data Structures and Algorithms. (See my earlier post: A Rookie's View on Competitive Programming.)