Machine Learning on Google Cloud v4.0 Course Overview

Master the art of machine learning (ML) and explore its potential for your business with Google Cloud’s Vertex AI Platform by honing the following skills:  

  • Master Google’s cutting-edge ML platform, understanding its functionalities and leveraging its power for streamlined model development and deployment. 
  • Dive into the core principles of ML, exploring various algorithms, best practices, and feature engineering techniques to build robust and reliable models. 
  • Get hands-on with TensorFlow, the leading ML framework. Learn to craft and train your own TensorFlow models for diverse applications. 
  • Understand data management, governance, preprocessing options, custom training, model deployment, prediction, and monitoring – all within real-world business scenarios. 

After completing this course on Machine Learning on Google Cloud v4.0 Certification, Students will be able to:

  • Translate a real-world business challenge into a machine learning problem.
  • Master techniques to boost data quality and unlock its hidden potential.
  • Uncover valuable insights and patterns through data exploration.
  • Craft and train powerful supervised learning models for accurate predictions.
  • Fine-tune your models like a pro using loss functions and performance metrics.
  • Build robust and sustainable training, evaluation, and testing pipelines.
  • Bring your models to life with the practical power of Keras and TensorFlow 2.x.
  • Dive deep into gradient descent parameters and their impact on accuracy, speed, and generalization.
  • Transform and engineer features like a data sculptor to optimize model training.
  • Leverage the power of AI Platform to train your models at scale and conquer larger-than-life challenges.

Upcoming Batches

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Start Date End Date

2024-09-30

2024-10-05

2024-10-07

2024-10-12

2024-10-14

2024-10-19

2024-10-21

2024-10-26

2024-10-28

2024-11-02

Machine Learning on Google Cloud v4.0 Training: Key Features:

  • Our Google Cloud Platform training modules have 50% - 60% hands-on lab sessions to encourage Thinking-Based Learning (TBL).
  • Interactive-rich virtual and face-to-face classroom teaching to inculcate Problem-Based Learning (PBL).
  • GCP certified instructor-led training and mentoring sessions to develop Competency-Based Learning (CBL).
  • Well-structured use-cases to simulate challenges encountered in a Real-World environment during Google Cloud Platform training.
  • Integrated teaching assistance and support through experts designed Learning Management System (LMS) and ExamReady platform.
  • Being an official Google Cloud Platform Training Partner, we offer authored curricula aligned with industry standards.

Who Should Attend this Course on Architecting with Google Kubernetes Engine Specialization:

  • Machine learning career aspirants, data scientists, and data engineers.
  • Machine learning scientists, data scientists, and data analysts seeking exposure on the cloud using TensorFlow 2.x and Keras.

Prerequisites:

    To get the most out of this course, participants should have:
  • Familiarity with basic machine learning concepts.
  • Basic proficiency in a scripting language - Python preferred.

    • Why choose CloudThat as your Machine Learning on Google Cloud v4.0 Training Partner?

    • Specialized GCP Focus: CloudThat specializes in cloud technologies, offering focused and specialized training programs. We are Authorized Trainers for the Google Cloud Platform. This specialization ensures in-depth coverage of GCP services, use cases, best practices, and hands-on experience tailored specifically for GCP.
    • Industry-Recognized Trainers: CloudThat has a strong pool of industry-recognized trainers certified by GCP. These trainers bring real-world experience and practical insights into the training sessions, comprehensively understanding how GCP is applied in different industries and scenarios.
    • Hands-On Learning Approach: CloudThat emphasizes a hands-on learning approach. Learners can access practical labs, real-world projects, and case studies that simulate actual GCP environments. This approach allows learners to apply theoretical knowledge in practical scenarios, enhancing their understanding and skill set.
    • Customized Learning Paths: CloudThat understands that learners have different levels of expertise and varied learning objectives. We offer customized learning paths, catering to beginners, intermediate learners, and professionals seeking advanced GCP skills.
    • Interactive Learning Experience: CloudThat's training programs are designed to be interactive and engaging. We utilize various teaching methodologies like live sessions, group discussions, quizzes, and mentorship to keep learners engaged and motivated throughout the course.
    • Placement Assistance and Career Support: CloudThat often provides placement assistance and career support services. This includes resume building, interview preparation, and connecting learners with job opportunities through our network of industry partners and companies looking for GCP-certified professionals.
    • Continuous Learning and Updates: CloudThat ensures that our course content is regularly updated to reflect the latest trends, updates, and best practices within the GCP ecosystem. This commitment to keeping the content current enables learners to stay ahead in their GCP knowledge.
    • Positive Reviews and Testimonials: Reviews and testimonials from past learners can strongly indicate the quality of training provided. You can Check feedback and reviews about our GCP courses that can provide potential learners with insights into the effectiveness and value of the training.

    Learning objective of the course

    • Turn real-world challenges into powerful ML problems.
    • Unlock data's hidden potential with advanced cleaning and enrichment techniques.
    • Dive into data exploration to find hidden patterns and trends.
    • Build and train accurate supervised learning models.
    • Fine-tune your models for optimal performance with loss functions and metrics.
    • Build robust training, evaluation, and testing pipelines.
    • Bring your models to life with the practical power of Keras and TensorFlow 2.x
    • Master gradient descent parameters to optimize accuracy, speed, and generalization.

    Machine Learning on Google Cloud v4.0 Course Outline Download Course Outline

    Topics:

    • Overview of Machine Learning
    • Examples of Machine Learning deployment specific to Google
    • Business problems addressed by Machine Learning
    • Introduction to the Vertex AI Platform - concepts, best practices, and labs.

    Topics:

    • Introduction
    • Get to Know Your Data: Improve Data through Exploratory Data Analysis
    • Machine Learning in Practice
    • Training AutoML Models Using Vertex AI
    • BigQuery Machine Learning: Develop ML Models Where Your Data Lives
    • Optimization
    • Generalization and Sampling

    Topics:

    • Introduction to the TensorFlow ecosystem
    • Design and Build an Input Data Pipeline
    • Building Neural Networks with the TensorFlow and Keras API
    • Training at Scale with Vertex AI

    Topics:

    • Introduction to Vertex AI Feature Store
    • Raw Data to Features
    • Feature Engineering
    • Preprocessing and Feature Creation
    • Feature Crosses - TensorFlow Playground
    • Introduction to TensorFlow Transform

    Topics:

    • Introduction
    • Understanding the ML Enterprise Workflow
    • Data in the Enterprise
    • Science of Machine Learning and Custom Training
    • Vertex Vizier Hyperparameter Tuning
    • Prediction and Model Monitoring Using Vertex AI
    • Vertex AI Pipelines
    • Best Practices for ML Development

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    Course ID: 19256

    Course Price at

    $1599 + 0% TAX
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