GOOGLE CLOUD CERTIFIED PROFESSIONAL MACHINE LEARNING ENGINEER (PMLE)
The Google Cloud Certified Professional Machine Learning Engineer (PMLE) course equips learners with the skills required to design, build, deploy, and manage machine learning (ML) solutions on Google Cloud Platform (GCP). The course focuses on applying machine learning techniques to real-world business problems using scalable, production-ready architectures. Learners will gain hands-on experience developing ML models, preparing and transforming data, deploying models into production, monitoring performance, and ensuring ethical, secure, and reliable machine learning systems. This course prepares participants for the Google Cloud Professional Machine Learning Engineer certification and advanced ML engineering roles. Course Objectives By the end of this course, learners will be able to: Design end-to-end machine learning solutions on Google Cloud Select appropriate ML models and algorithms for business problems Prepare, transform, and manage data for ML workflows Train, evaluate, and optimize machine learning models Deploy and monitor ML models in production environments Implement responsible AI, security, and governance practices Scale ML systems using cloud-native tools and services
Course Curriculum
1
- Role of the machine learning engineer
- Machine learning lifecycle
- Overview of Google Cloud ML and AI services
- ML solution architectures
2
- Data collection, cleaning, and preprocessing
- Feature engineering techniques
- Handling missing, imbalanced, and noisy data
- Data validation and versioning
3
- Selecting algorithms and model architectures
- Supervised and unsupervised learning
- Model training, evaluation, and tuning
- Distributed and scalable training
4
- Designing ML pipelines
- Workflow orchestration and automation
- Continuous training and continuous evaluation
- Experiment tracking and reproducibility
5
- Model packaging and deployment strategies
- Online and batch prediction
- Scalable model serving architectures
- Performance and latency optimization
6
- Model performance monitoring
- Detecting data and concept drift
- Retraining strategies
- Troubleshooting ML systems in production
7
- Ethical AI and fairness considerations
- Explainability and transparency
- Securing ML workflows and data
- Compliance and governance frameworks
8
- Real-world ML use cases and scenarios
- Hands-on labs and practical exercises
- Review of certification exam domains
- Best practices for exam success
9
- Machine learning engineers
- Data scientists transitioning to ML engineering
- Data engineers and cloud engineers
- AI and analytics professionals
- Professionals preparing for the Google Cloud PMLE certification
10
- Strong understanding of data analysis and statistics
- Basic knowledge of machine learning concepts
- Programming experience (e.g., Python)
- Familiarity with Google Cloud Platform is recommended
11
- Assessment Methods
- Practical labs and projects
- Quizzes and knowledge checks
- Final assessment or certification-oriented evaluation
12
- Instructor-led training
- Hands-on labs and practical demonstrations
- Case studies and real-world ML scenarios
13
- This course prepares participants for the Google Cloud Certified Professional Machine Learning Engineer (PMLE) certification exam
14
- Comprehensive training materials
- Hands-on lab guides
- Practice exam questions
- Certificate of course completion
This course includes
- 14+ Activity Modules
- 40 hours + lessons
- Lifetime access
- Certificate of completion
- Available on desktop and mobile
What Our Participants Say
Hear from participants who have experienced our training.
The facilitator’s wealth of experience was both striking and beneficial. He really helped translate concepts to real life.
The practical session where step by step of the lecture is broken down in visual and practice
I enjoyed the interactivity. It was also very direct, pointing out to us the key things to look for in the bidding, tender and proposal administration process, while also ensuri...
The practical session of the class which helped in giving a live run through of the necessary bidding and tender platform
The atmosphere was very pleasant, as it was an interactive and engaging session, which I personally enjoyed.
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