Introduction to AI on Google Cloud
A beginner’s guide to starting AI and machine learning with Google Cloud
Your organization may have the potential to generate petabytes of data, but are your data scientists and analysts technically equipped to handle it? Big data, machine learning, and artificial intelligence are today’s most popular computing topics, but these fields are specialized, and it can be difficult to know where to begin.
Join expert Harshit Tyagi to learn how to utilize Google Cloud Platform (GCP) for AI and machine learning, in a user-friendly environment. You’ll develop a foundation in Cloud SQL and BigQuery so that you can store and query massive datasets, and you’ll learn how to use TensorFlow for model training on Cloud ML Engine. Gain hands-on experience with live coding, and leave knowing how to create and deploy your own machine learning models using TensorFlow.
What you'll learn-and how you can apply it
By the end of this live, hands-on, online course, you’ll understand:
- The basics of fundamental SQL clauses
- How to run structured queries on BigQuery and how to query public tables
- What you need to create, train, and deploy a machine learning model
And you’ll be able to:
- Store and query massive datasets using BigQuery
- Train and deploy a TensorFlow model to Cloud ML Engine
This training course is for you because...
- You’re a programmer or an aspiring data engineer.
- You’re a beginner in the field of big data, AI, and machine learning and want to learn more.
- Basic familiarity with programming and SQL
- An understanding of elementary mathematics
- Read “Introducing the Google Cloud Platform” (chapter 1 in Hands-On Machine Learning on Google Cloud Platform)
- Finish Hands-On Machine Learning on Google Cloud Platform (book)
About your instructor
Harshit Tyagi is a full stack developer and data engineer at Elucidata, a biotech company based in Cambridge, where he develops algorithms for research scientists at some of the world’s best medical schools, including Yale, UCLA, and MIT. Previously, he was a systems development engineer at the investment management firm Tradelogic, where he designed a framework to analyze financial news from prominent sources to produce accurate trading signals. He’s a Python evangelist and loves to contribute to tech communities, including Google Developers Groups and Python Delhi User Groups, as well as other online learning platforms.
The timeframes are only estimates and may vary according to how the class is progressing
Introduction to SQL for Cloud SQL and BigQuery (60 minutes)
- Lecture: Role of the data scientist in a data-driven organization
- Hands-on exercises: Perform fundamental SQL queries on a public dataset using BigQuery; export subsets of datasets into CSV files and upload them to Cloud SQL; create and manage databases and tables
Break (5 mins)
BigQuery console quickstart (45 minutes)
- Lecture: BigQuery console basics
- Hands-on exercise: Use Web UI to query public tables and load sample data into BigQuery
Break (5 mins)
TensorFlow model training on Cloud ML Engine (55 minutes)
- Lecture: TensorFlow machine learning library basics
- Hands-on exercises: Train TensorFlow models locally and on Cloud ML Engine; deploy a prediction model using US census income datasets
Wrap-up and Q&A (10 minutes)