Google Machine Learning Engineer
Instructor-led Google Cloud-aligned training in Google Machine Learning Engineer. Delivered live online by senior practitioners, with hands-on labs and a final assessment. Includes an Skilvi course-completion certificate.
Overview
The Google Machine Learning Engineer course provides an in-depth understanding of machine learning concepts and how to implement them using Google Cloud technologies. Participants will learn to build, train, and deploy machine learning models, a skill set that is increasingly vital in today's data-driven landscape.
What you'll learn
- You will be able to design machine learning models tailored to specific business needs.
- You will be able to utilize Google Cloud services for data preparation and model training.
- You will be able to implement machine learning algorithms using TensorFlow on Google Cloud.
- You will be able to evaluate model performance and optimize for better accuracy.
- You will be able to deploy machine learning models to production using Google Cloud tools.
- You will be able to integrate machine learning solutions with existing applications and workflows.
Curriculum
6 modules · outline is indicative and can be tailored to your team.
1Introduction to Machine Learning
- Overview of machine learning concepts
- Types of machine learning: supervised, unsupervised, and reinforcement learning
- Introduction to Google Cloud ML services
2Data Preparation and Exploration
- Data collection and preprocessing techniques
- Exploratory data analysis using Google Cloud tools
- Feature engineering and selection
3Building Machine Learning Models
- Choosing the right algorithms for your data
- Utilizing TensorFlow for model development
- Configuring training parameters and hyperparameter tuning
4Model Evaluation and Optimization
- Metrics for evaluating model performance
- Techniques for improving model accuracy
- Cross-validation and overfitting prevention
5Deployment of Machine Learning Models
- Best practices for deploying models to production
- Using Google Cloud AI Platform for deployment
- Monitoring and maintaining deployed models
6Integrating Machine Learning into Applications
- Building APIs for machine learning models
- Integrating with existing systems and workflows
- Real-world use cases and applications
Prerequisites
Basic understanding of programming and statistics is recommended.
Who should attend
This course is ideal for data scientists, software engineers, and IT professionals looking to expand their expertise in machine learning on Google Cloud.
Certification
Prepares you for the official Google Cloud certification exam.
Skilvi is an independent training provider and is not affiliated with, or endorsed by, Google Cloud. Trademarks are the property of their respective owners.
Frequently asked questions
What is the delivery format of the course?
The course is delivered through live online sessions led by experienced instructors.
How long is the course?
The course typically spans over several weeks, with multiple sessions each week.
Will I receive a certificate upon completion?
Yes, participants will receive an Skilvi course-completion certificate after finishing the course.
Are exam vouchers included in the course?
Exam vouchers are available through authorized channels on request.
Do I need any prior experience to attend this course?
Basic understanding of programming and statistics is recommended.
Pricing on request
- Live online (VILT)
- 24–32 hours
- Hands-on labs & assignments
- Skilvi completion certificate
- Exam voucher on request
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