Virtual Classroom
Big Data & Machine Learning
9am - 5pm PT
Join Jellyfish & Google for a free-of-charge, one-day, virtual, instructor-led training session, to help you start your learning and certification journey on Google Cloud.
This course will help you understand the big data capabilities of the Google Cloud Platform. It introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle, and explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
Through expert guidance and practical labs, you’ll gain an overview of Google Cloud and a detailed view of its data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud Platform.
This Google Cloud Platform Fundamentals: Big Data & Machine Learning course is part of the Professional Data Engineer track.
Jellyfish has recently been named a Google Cloud Specialisation Partner of the Year. This title recognises our commitment to provide world-leading Cloud-based Training solutions that help our clients succeed.
Due to the nature and content of this course, all delegates are requested to stay engaged and participate fully in the virtual classroom. This course contains exercises to complete within Qwiklabs, and all delegates will be required to complete these exercises as part of the course.
We will be in touch shortly to confirm your place. Please allow 30 minutes for your confirmation of booking to be delivered.
Who should attend:
- Data analysts, data scientists and business analysts who are getting started with Google Cloud
- Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results, and creating reports
- Executives and IT decision makers evaluating Google Cloud for use by data scientists.
Walk away with the ability to:
- Identify the purpose and value of the key Big Data and Machine Learning products in Google Cloud
- Use Cloud SQL and Dataproc to migrate existing MySQL and Hadoop / Pig / Spark / Hive workloads to Google Cloud
- Employ BigQuery and Cloud SQL to carry out interactive data analysis
- Choose between different data processing products on Google Cloud
- Create ML models with BigQuery ML, ML APIs, and AutoML
Prerequisites:
To get the most out of this course, you should have:
- Basic proficiency with common query language such as SQL
- Data engineering workflow from extract, transform, load, to analysis, modeling, and deployment
- Machine learning models such as supervised versus unsupervised models
Agenda (all times are in PT)
- 9:00am
- 9:15am
- 9:30am
- 11:15am
- 11:30am
- 12:30pm
- 1:15pm
- 3:30pm
- 3:15pm
- 5:00pm