Training schedule
IN-COMPANY TRAINING PROGRAMS
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This one-day instructor-led Google Cloud Platform course introduces participants to the big data capabilities of Google Cloud Platform. Through a combination of presentations, demos, and hands-on labs, you will get an overview of the Google Cloud platform and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud Platform.
This training is for you if…
you have:
- Basic proficiency with common query language such as SQL
- Experience with data modeling, extract, transform, load activities
- Developing applications using a common programming language such Python
- Familiarity with Machine Learning and/or statistics
This training is not for you if…
you have:
- No experience with common query language
- No familiarity with Machine Learning
- No experience with data modelling
Clients we've helped
What you'll learn
- Purpose and value of the key Big Data and Machine Learning products in the GoogleCloud Platform
- Use Cloud SQL and Cloud Dataproc to migrate existing MySQL andHadoop/Pig/Spark/Hive workloads to Google Cloud Platform
- Employ BigQuery and Cloud Datalab to carry out interactive data analysis
The schedule
1. Introducing Google Cloud Platform
- Google Platform Fundamentals Overview
- Google Cloud Platform Data Products and Technology
- Usage scenarios
2. Compute and Storage Fundamentals
- CPUs on demand (Compute Engine)
- A global filesystem (Cloud Storage)
- CloudShell
3. Data Analytics on the Cloud
- Stepping-stones to the cloud
- CloudSQL: your SQL database on the cloud
- Lab: Importing data into CloudSQL and running queries
- Spark on Dataproc
4. Scaling Data Analysis
- Fast random access
- Datalab
- BigQuery
- Machine Learning with TensorFlow
- Fully built models for common needs
5. Data Processing Architectures
- Message-oriented architectures with Pub/Sub
- Creating pipelines with Dataflow
- Reference architecture for real-time and batch data processing
6. Summary
- Why GCP?
- Where to go from here
- Additional Resources
Classroom Live Labs
Lab 1: Sign up for Google Cloud Platform
Lab 2: Set up a Ingest-Transform-Publish data processing pipeline
Lab 3: Machine Learning Recommendations with SparkML
Lab 4: Build machine learning dataset
Lab 5: Train and use neural network
Lab 6: Employ ML APIs
- Train and use a neural network using TensorFlow
- Employ ML APIs
- Choose between different data processing products on the Google Cloud Platform
Get In Touch!
Contact Max Driessen now if you want to learn more and take your cloud skills to the next level!
Koen Maes
TrainerKoen is a very experienced consultant with a long history in the information technology and services industry. He takes on a wide variety of roles in software development, always evolving and keeping up with new innovations. He picked up the potential of the cloud early on, which led him to become one of the first Authorized Trainers for Google Cloud.
He’s passionate about creating value for the customer… and getting things done!
Structured, to-the-point, good combination of theory and practical examples, very knowledgeable trainer who can explain concepts very well
It was a hands-on and tangible course. We could apply what we learned in a matter of minutes. The trainer did a great job of answering ad-hoc questions that complemented the material. We appreciated the fact that we could apply what we were taught directly to our company.
I liked every aspect of this training and would like to thank the trainers. They did an excellent job of explaining how to use Spark for data science. This is the fourth GoDataDriven training I’ve followed. All were great, but this was the best one so far.
Climbing a steep Python and Machine Learning curve in three days. This would have taken me months on my own.
