Smart Analytics, Machine Learning, and AI on Google Cloud

Course Overview

Businesses' capacity to derive insights from their data is increased when machine learning is included into data pipelines. Depending on the level of customization needed, this course examines a variety of ways machine learning can be incorporated into data pipelines on Google Cloud. This course covers AutoML, which requires little to no customization. For more specialised machine learning capabilities, this course covers Notebooks and BigQuery machine learning (BigQuery ML). Additionally, this course teaches how to use Vertex AI to create production-ready machine learning solutions. Students will gain practical experience using QwikLabs to develop machine learning models on Google Cloud.

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Prerequisites

Participants should have already completed “Google Cloud Big Data and Machine Learning Fundamentals” to benefit from this course or have equivalent experience.

Audience Profile

Data Engineers

Learning Objectives

  • Differentiate between ML, AI, and Deep Learning.
  • ML API usage with unstructured data is discussed.
  • BigQuery commands can be run from notebooks.
  • Using BigQuery's SQL syntax, create ML models.
  • Use AutoML to build ML models without writing any code.

Content Outline

In this module, we will give the overiew of the course and agenda.

This module talks about ML options on Google Cloud.

This module focuses on using prebuilt ML APIs on your unstructured data.

This module covers how to use Notebooks.

This module covers creating custom ML models and introduces Vertex AI and AI Hub.

This specific module discusses BigQuery ML.

Custom model building with AutoML

This module recaps and summarizes the topics covered in the course.

FAQs

A: By applying Google's machine learning capabilities to your dataset to forecast future user behaviour, Google Analytics automatically improves your data. Predictive metrics help you understand your consumers better by simply gathering structured event data.

A: Google Analytics Intelligence is a machine learning tool used by Google to help users better understand the analytics data. It includes a set of artificial intelligence (AI) based features which let you quickly find the insights you need without manually digging into the data.

A: MUM stands for Multitask Unified Model and is a type of AI that Google uses as a much more powerful version of BERT. MUM uses more powerful AI techniques to better understand the context around searches, search intent, and searches in different languages.

A: Radiant has highly intensive selection criteria for Technology Trainers & Consultants who deliver training programs. Our trainers & consultants undergo a rigorous technical and behavioral interview and assessment process before they are onboarded in the company.

Our Technology experts/trainers & consultants carry deep-dive knowledge in the technical subject & are certified by the OEM.

Our training programs are practically oriented with 70% – 80% hands-on training technology tools. Our training program focuses on one-on-one interaction with each participant, the latest content in the curriculum, real-time projects, and case studies during the training program.

Our faculty will quickly provide you with the knowledge of each course from the fundamental level, and you are free to ask your doubts at any time from your respective faculty.

Our trainers have the patience and ability to explain complex concepts simplistically with depth and width of knowledge.

To ensure quality learning, we provide support sessions even after the training program.

A: To attend the training session, you should have operational Desktops or Laptops with the required specification and a good internet connection to access the labs. 

A: We would always recommend you attend the live session to practice & clarify the doubts instantly and get more value from your investment. However, if, due to some contingency, you have to skip the class, Radiant Techlearning will help you with the recorded session of that particular day. However, those recorded sessions are not meant only for personal consumption and NOT for distribution or any commercial use.

A: Radiant Techlearning has a data center containing a Virtual Training environment for participants’ hand-on-practice. 

Participants can easily access these labs over Cloud with the help of a remote desktop connection. 

Radiant virtual labs allow you to learn from anywhere and in any time zone. 

A: The learners will be enthralled as we engage them in the natural world and Oriented industry projects during the training program. These projects will improve your skills and knowledge and give you a better experience. These real-time projects will help you a lot in your future tasks and assignments.

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