Google Professional Machine Learning Engineer Training (Synchronous e-Learning)
About This Course
Embark on a transformative journey towards becoming a Google Professional Machine Learning Engineer. Our comprehensive preparation course is meticulously designed to cover all the critical facets of machine learning, ensuring you gain the expertise needed to pass the certification exam confidently. By engaging with this course, you will dive deep into the development of scalable machine learning models, understanding complex data pipelines, and deploying robust ML projects using Google Cloud technologies. This certification signifies to employers that you possess the acumen to leverage machine learning in a way that drives powerful, innovative solutions.
This advanced training program goes beyond the fundamentals, providing insights into machine learning algorithms, model optimization, and problem-solving techniques crucial for real-world applications. You will learn how to approach machine learning engineering with an ethical and socially responsible lens while mastering the skills to build, test, and deploy AI systems that are scalable and reliable. Our curriculum is crafted to ensure that upon completion, you will not only be prepared for the Google Professional Machine Learning Engineer exam but also equipped to propel your career forward in the thriving field of AI and machine learning.
What You'll Learn
- Assess and draft Google Cloud solution specifications to meet expected business machine learning requirements.
- Develop implementation plans and resolve issues for Google Cloud machine learning solutions.
- Develop and review processes for metrics associated with Google Cloud machine learning solution implementation.
Course Outline:
Topic 1 Google Cloud Big Data and Machine Learning Fundamentals
Topic 2 How Google does Machine Learning
Topic 3 Launching into Machine Learning
Topic 4 TensorFlow on Google Cloud
Topic 5 Feature Engineering
Topic 6 Machine Learning in the Enterprise
Topic 7 Production Machine Learning Systems
Topic 8 Machine Learning Operations (MLOps)
Entry Requirements
Knowledge and Skills
• Able to operate computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
• Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)
Attitude
• Positive Learning Attitude
• Enthusiastic Learner
Experience
• Minimum of 1 year of working experience.
Target Year Group : 21-65 years old