Google Professional Machine Learning Engineer Certification (GCP-PMLE) with Practice Exam
Master Google Professional Machine Learning Engineer Certification (GCP-PMLE) with our comprehensive course tailored for success.
This course will provide a comprehensive overview of key topics and skills necessary for the Google Cloud Professional Machine Learning Engineer Certification.
The course begins with an introduction to Cloud Computing for Machine Learning, covering essential concepts and principles that enable machine learning on cloud platforms. Participants will gain a solid understanding of the benefits and capabilities of cloud computing in the context of machine learning.
Next, the course explores image classification using AutoML and Vertex AI in Google Cloud. Participants will learn how to leverage these advanced tools to build and train image classification models. They will also discover techniques for managing and classifying image datasets using Cloud Storage.
The course then focuses on training an AutoML image classifier machine learning model. Participants will learn how to prepare data, configure the model, and evaluate its performance. Through hands-on exercises, they will gain practical experience in building and refining their own image classification models.
Moving forward, the course covers the construction of a streaming data pipeline in Google Cloud using BigQuery. Participants will learn how to ingest and process real-time data streams, utilizing the powerful capabilities of BigQuery for data manipulation and analysis. They will gain insights into building scalable and efficient streaming data pipelines.
Additionally, participants will explore building data streaming Dataflow Pipelines using Google Cloud API. They will learn how to leverage Dataflow to process and transform large-scale data streams, enabling efficient data processing and analysis in real-time scenarios.
Finally, the course covers querying and visualizing data with BigQuery SQL. Participants will learn how to write SQL queries to extract meaningful insights from data stored in BigQuery. They will discover techniques for analyzing and visualizing data, empowering them to derive valuable information and make informed decisions.
By completing this course, participants will be equipped with the knowledge and skills required to pursue the Google Cloud Professional Machine Learning Engineer Certification. This certification demonstrates expertise in leveraging Google Cloud's machine learning capabilities and positions individuals for success in the field of machine learning engineering. Don't miss out on this opportunity to enhance your career and expand your machine learning capabilities – enroll in the course today.
Your Instructor
Alexandra Kropf is Mammoth Interactive's CLO and a software developer with extensive experience in full-stack web development, app development and game development. She has helped produce courses for Mammoth Interactive since 2016, including the Coding Interview series in Java, JavaScript, C++, C#, Python and Swift.
Mammoth Interactive is a leading online course provider in everything from learning to code to becoming a YouTube star. Mammoth Interactive courses have been featured on Harvard’s edX, Business Insider and more.
Over 12 years, Mammoth Interactive has built a global student community with 4 million courses sold. Mammoth Interactive has released over 350 courses and 3,500 hours of video content.
Founder and CEO John Bura has been programming since 1997 and teaching
since 2002. John has created top-selling applications for iOS, Xbox and
more. John also runs SaaS company Devonian Apps, building
efficiency-minded software for technology workers like you.
Course Curriculum
-
Start00A What Is Machine Learning (5:26)
-
Start00B Types Of Machine Learning Models (12:17)
-
Start00C What Is Supervised Learning (11:04)
-
Start01 How Does A Machine Learning Agent Learn (7:38)
-
Start02 What Is Inductive Learning (4:11)
-
Start03 Performance Of A Machine Learning Algorithm (4:14)
-
Start04 Handle Noise In Data (5:22)
-
Start05 Powerful Tools With Machine Learning Libraries (12:11)
-
Start01 Why Use The Cloud For Machine Learning (2:38)
-
Start02 Benefits Of Cloud Computing (1:23)
-
Start03 Public Vs Private Cloud Computing (3:18)
-
Start04 Managed Vs Unmanaged Cloud Computing (1:30)
-
Start05 Iaas Vs Paas Vs Saas In Cloud Computing (3:33)
-
Start06 Google Cloud Vs Aws Vs Azure For Machine Learning (3:32)
-
StartSource Files