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Overview

This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.
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What You'll Learn

  • Define the course goal.
  • Recognize the course objectives.
  • Recognize the AI/ML framework on Google Cloud.
  • Identify the major components of Google Cloud infrastructure.
  • Define the data and ML products on Google Cloud and how they support the data-to-AI lifecycle.
  • Build an ML model with BigQueryML to bring data to AI.
  • Define different options to build an ML model on Google Cloud.
  • Recognize the primary features and applicable situations of pre-trained APIs, AutoML, and custom training.
  • Use the Natural Language API to analyze text.
  • Define the workflow of building an ML model.
  • Describe MLOps and workflow automation on Google Cloud.
  • Build an ML model from end to end by using AutoML on Vertex AI.
  • Define generative AI and foundation models.
  • Use Gemini multimodal with Vertex AI Studio.
  • Design efficient prompt and tune models with different methods.
  • Recognize the AI solutions and the embedded Gen AI features.
  • Recognize the primary concepts, tools, technologies, and products learned in the course.

Who Should Attend

Professional AI developers, data scientists, and ML engineers who want to build predictive and generative AI projects on Google Cloud
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Prerequisites

Having one or more of the following:

  • Basic knowledge of machine learning concepts
  • Prior experience with programming languages such as SQL and Python

Learning Journey

Coming Soon...

Module 0    Course Introduction
Topics        

  • Course introduction

Module 01    AI Foundations
Topics         

  • Why AI?
  • AI/ML framework on Google Cloud
  • Google Cloud infrastructure
  • Data and AI products
  • ML model categories
  • BigQuery ML
  • Lab introduction: BigQuery ML

Module 02     AI Development Options
Topics

  • AI development options
  • Pre-trained APIs
  • Vertex AI
  • AutoML
  • Custom training
  • Lab introduction: Natural Language API

Module 03     AI Development Workflow
Topics 

  • ML workflow
  • Data preparation
  • Model development
  • Model serving
  • MLOps and workflow automation
  • Lab introduction: AutoML
  • How a machine learns

Module 04     Generative AI
Topics

  • Generative AI and workflow
  • Gemini multimodal
  • Prompt design
  • Model tuning
  • Model Garden
  • AI solutions
  • Lab introduction: Vertex AI Studio

Module 05     Course Summary
Topics

  • Course summary

Frequently Asked Questions (FAQs)

  • Why get Google Cloud Platform (GCP) certified?

    Google Cloud certifications validate your expertise in cloud technologies and your proficiency in using Google Cloud Platform's vast array of services.

    These certifications are recognized globally and highly sought after by employers, as they demonstrate your ability to design, develop, and manage scalable and secure cloud solutions on GCP.

    Google Cloud-certified professionals are in high demand, opening doors to new career opportunities and higher earning potential.

  • What to expect for the examination?

    Google Cloud offers a variety of certification exams across different levels (Foundational, Associate, and Professional) covering various job roles and specializations.

    The exams typically consist of multiple-choice and multiple-select questions, as well as scenario-based questions that assess your ability to apply your knowledge in real-world situations.

    Note: Certification requirements and policies may be updated by Google Cloud from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • How long is Google Cloud Platform (GCP) certification valid for?

    Most Google Cloud certifications, including Professional-level certifications, are valid for two years from the date of passing the exam.

    The Cloud Digital Leader and Associate Cloud Engineer certifications are valid for three years from the date of passing the exam.

    To maintain your certification, you will need to recertify by passing the latest version of the same exam or an equivalent higher-level certification exam before your current certification expires.

    You will receive a notification from Google Cloud prior to your certification's expiration date.

    Note: Certification requirements and policies may be updated by Google Cloud from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • Why take this course with Trainocate?

    Here’s what sets us apart:

    - Global Reach, Localized Accessibility: Benefit from our geographically diverse training hubs in 24 countries (and counting!).

    - Top-Rated Instructors: Our team of subject matter experts (with high average CSAT and MTM scores) are passionate to help you accelerate your digital transformation.

    - Customized Training Solutions: Choose from on-site, virtual classrooms, or self-paced learning to fit your organization and individual needs.

    - Experiential Learning: Dive into interactive training with our curated lesson plans. Participate in hands-on labs, solve real-world challenges, and take on comprehensive assessments.

    - Learn From The Best: With 30+ authorized training partnerships and countless awards from Microsoft, AWS, Google – you're guaranteed learning from the industry's elite.

    - Your Bridge To Success: We provide up-to-date course materials, helpful exam guides, and dedicated support to validate your expertise and elevate your career.

Keep Exploring

Course Curriculum

Course Curriculum

Training Schedule

Training Schedule

Exam & Certification

Exam & Certification

FAQs

Frequently Asked Questions

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Improve yourself and your career by taking this course.

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