Skip to content

Latest commit

 

History

1 Commit

Folders and files

NameName
Last commit message
Last commit date
 
 
 
 
 
 

Repository files navigation

TGS-2023040476 - Google Professional Machine Learning Engineer Training

Course: Google Professional Machine Learning Engineer Training
Course Code: TGS-2023040476
Register here: https://www.tertiarycourses.com.sg/wsq-google-professional-machine-learning-engineer-training.html

Hands-on Google Professional Machine Learning Engineer labs for learners preparing to design, build, deploy, scale, monitor, and govern machine learning solutions on Google Cloud. The labs cover Vertex AI, BigQuery, Cloud Storage, Workbench, AutoML, custom training, feature engineering, pipelines, model registry, endpoints, monitoring, responsible AI, security, and production MLOps review.

Courseware

File Description
Learner Guide Detailed step-by-step guide for the full course.
Labs Index Quick links to all hands-on labs.
Tools Guide Free and built-in tools used throughout the labs.

How to Use These Labs

  1. Read the learner guide before starting the first lab.
  2. Complete the labs in order because later labs reuse design decisions and artifacts from earlier labs.
  3. Use a Google Cloud training account, sandbox, or free trial account with billing controls enabled.
  4. Prefer small datasets, low-cost machine types, and managed services configured for training use.
  5. Clean up notebooks, endpoints, jobs, buckets, and pipelines at the end of the course.

Lab Catalogue

Data, Design, and Experimentation

Lab Topic
Lab 01 ML Solution Design, Project Setup, Governance
Lab 02 Data Ingestion, BigQuery, Cloud Storage, Profiling
Lab 03 Vertex AI Workbench, Experiment Baseline

Training, Evaluation, and Deployment

Lab Topic
Lab 04 AutoML Training, Evaluation, Model Registry
Lab 05 Custom Training, Containers, Hyperparameter Tuning
Lab 06 Feature Engineering, Feature Store Concepts, Data Leakage
Lab 07 Model Serving, Endpoints, Batch Prediction

MLOps, Monitoring, and Exam Review

Lab Topic
Lab 08 Pipelines, CI/CD, MLOps Orchestration
Lab 09 Model Monitoring, Responsible AI, Security
Lab 10 Capstone Production ML Solution and Exam Review

References

Free Tools Used

  • Google Cloud Free Trial or instructor-provided sandbox account
  • Google Cloud Console
  • Cloud Shell
  • Google Cloud CLI
  • BigQuery sandbox or training project
  • Cloud Storage
  • Vertex AI Workbench
  • Vertex AI Pipelines
  • Cloud Logging and Cloud Monitoring
  • diagrams.net

About

10 hands-on Google Professional Machine Learning Engineer labs covering Vertex AI, BigQuery, Cloud Storage, Workbench, AutoML, custom training, feature engineering, pipelines, model registry, endpoints, monitoring, responsible AI, security, MLOps, and exam review.

Topics

Resources

Stars

1 star

Watchers

0 watching

Forks

Releases

Packages

Contributors