5 steps to data mastery with Google Cloud

Have you seen the Make Google do it commercials? Learn how to make Google tackle the tough questions you want to answer for your job or business with 15+ Machine Learning and Big Data labs that can help you answer questions like:

How do self-driving cars know the speed limit? What SKUs will see the most traffic on my retail website when it’s raining? How can I analyze sentiment of my customers’ conversations with my team? And how can I prepare for Google’s Professional Data Engineer certification exam?

  1. Start with the Baseline: Big Data, ML, AI Quest if you’re new to Google Cloud. Get a basic understanding of GCP tools like Cloud SQL, BigQuery, APIs, Bigtable, Dataproc, Dataprep, and Cloud ML Engine, and explore public datasets like worldwide genomic data. With about five hours of lab work, you can earn your badge!
  2. Next, tackle more advanced concepts with the Machine Learning APIs Quest. This is where you’ll learn how to teach a self-driving car to recognize speed limit signs,   analyze blocks of text for customer satisfaction, and five more use cases. More fun with APIs, plus experience with Awwvision and Dialogflow.
  3. You’re ready for the next step, the Data Engineering exam practice Quest. These nine labs, designed by Google’s training team, help you practice critical job skills for the role of a Data Engineer. You’ll practice use cases with TensorFlow, an IoT pipeline, BigQuery and Datalab together, and you’ll learn how to correspond your sales data with the weather!
  4. Thinking about the Data Engineer certification? Try the practice exam to assess your readiness, and don’t “make Google do it” this time (: Set a timer and see how far you can get. How did it go?
  5. Extra credit: Challenge yourself with some of the most advanced labs on Qwiklabs today. The Google Cloud Solutions II Quest works through complex scenarios to knit multiple services together to solve a problem. The labs in this Quest come directly from engineers who developed these solutions in real-time. Not for the faint of heart! Dig deep into TensorFlow use cases, use BigQuery to explore NCAA data and build custom interactive dashboards with Boke, and more.

Why not try for a ML or Big Data Quest badge? A badge shows your “flight time” with Google Cloud, and differentiates you as someone with hands-on GCP experience. Would one (or more) of these badges look good on your resume?

 

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