Menu
Menu
CODE: NAI11
DURATION: 3 Days | 5 Days | 10 Days
CERTIFICATIONS: CPD
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.
This course is available in the following formats:
Virtual
Classroom
Request this course in a different delivery format.
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.
Prepare for the Google Cloud ML Engineer certification exam.
At the end of this course, you’ll understand:
This executive course is suitable for directors, executives, managers and other professionals with some finance background, who wish to study corporate finance as a tool for making strategic decisions. A fast-paced and highly interactive course aimed at current and aspiring senior decision makers.
✓ Modern facilities
✓ Course materials and certificate
✓ Accredited international trainers
✓ Training materials and workbook
✓ Access to online resources
