Google Cloud Machine Learning Engineer Track

CODE: NAI22

DURATION: 3 Days | 5 Days | 10 Days

CERTIFICATIONS: CPD

  • Modern facilities
  • Course materials and certificate
  • Accredited international trainers

3 Days

₦500,000

5 Days

₦1,500,000

10 Days

₦3,500,000

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Course Overview

Course Outcomes

Key Course Highlights

Who Should Attend

Upcoming Course Dates

Course Overview

This course provides an end-to-end learning path for developing, deploying, and managing machine learning models on Google Cloud Platform (GCP). Areas covered in the course are model development, data preparation, pipeline automation, model monitoring, and MLOps best practices. Participants will engage practical tools like Vertex AI, BigQuery ML, AutoML, and TensorFlow on GCP. Participants can use this course to prepare for the Google Cloud Professional Machine Learning Engineer certification and real-world ML engineering roles in cloud environments.

Course Delivery

This course is available in the following formats:

Virtual

Classroom

Request this course in a different delivery format.

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Course Outcomes

Delegates will gain the knowledge and skills to:

Understand the ML lifecycle on Google Cloud.

Prepare and manage large datasets using GCP tools.

Build and train ML models using TensorFlow and Vertex AI.

Automate model pipelines and deployment workflows.

Implement MLOps for monitoring and continuous improvement.

Optimize model performance and manage version control.

Apply security and governance best practices for ML solutions.

Prepare for the Google Cloud ML Engineer certification exam.

Key Course Highlights

At the end of this course, you’ll understand:

  • Overview of Google Cloud’s AI and ML ecosystem.
  • Using Vertex AI for model training, deployment, and monitoring.
  • Data preparation with BigQuery and Cloud Storage.
  • Model development with AutoML, TensorFlow, and custom containers.
  • ML pipeline automation with Cloud Functions and Cloud Composer.
  • MLOps best practices: CI/CD, model drift detection, and monitoring.
  • Security, scalability, and compliance in cloud-based ML workflows.
  • Hands-on labs and real-world case studies.
  • Certification-focused training modules.
  • Deployment of end-to-end machine learning solutions on GCP.
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Who Should Attend

This course is designed for machine learning engineers, data scientists, cloud developers, AI/ML practitioners, and technical professionals seeking to build and scale ML solutions on Google Cloud. It is also beneficial for those preparing for the Google Cloud Professional ML Engineer certification. Prior experience with Python, machine learning basics, and familiarity with cloud concepts is recommended.

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Upcoming Course Dates

Delivery Format: Classroom & Virtual

Date: 27/10/2025

Location: Lagos

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Google Cloud Machine Learning Engineer Track

✓ Modern facilities

✓ Course materials and certificate

✓ Accredited international trainers

✓ Training materials and workbook

✓ Access to online resources

Enrol Now

Request Group Training

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