Course Description

This course provides a comprehensive introduction to the AI and machine learning (ML) capabilities of Google Cloud, specifically tailored for professionals in the telecoms industry. It explores the full data-to-AI lifecycle, from foundational concepts to practical solutions, with a focus on use cases relevant to telecoms organizations. Participants will learn how cloud technologies empower these institutions to build both predictive and generative AI projects. The course covers the technologies, products, and tools available on Google Cloud and how they are applied in areas like customer service automation, personalized customer experience, demand forecasting and capacity planning. Through engaging learning experiences and hands-on exercises, data scientists, AI developers, and ML engineers will enhance their skills and knowledge, gaining practical experience in developing and deploying AI solutions within the context of telecoms regulations and best practices.

Objectives

Recognize the data-to-AI technologies and tools provided by Google Cloud
Build generative AI projects by using Gemini multimodal, efficient prompts, and model tuning
Explore various options for developing an AI project on Google Cloud
Create an ML model from end to end by using Vertex AI

Prerequisites

Having one or more of the following:

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

Audience

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

Course Outline

Module 1: Course Introduction

Define the course goal
Recognize the course objectives

Module 2: AI Foundations

Why AI?
AI/ML framework on Google Cloud
Google Cloud infrastructure
Data and AI products
ML model categories
BigQuery ML
Lab introduction: BigQuery ML
Lab: Predicting Visitor Purchases with BigQuery ML

Module 3: AI Development Options

AI development options
Pre-trained APIs
Vertex AI
AutoML
Custom training
Lab introduction: Natural Language API
Lab: Entity and Sentiment Analysis with Natural Language API

Module 4: AI Development Workflow

ML workflow
Data preparation
Model development
Model serving
MLOps and workflow automation
How a machine learns
Lab introduction: AutoML
Lab: Vertex AI: Predicting Loan Risk with AutoML

Module 5: Generative AI

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

Note that the hands-on activities available for this session may cover general purpose use-cases, however the course content has been tailored for telecoms industries specifically.

**This event is managed by Google and ROI Training. By registering you may receive communications from either organization.

Introduction to AI and Machine Learning in Telecoms, Virtual BST