From Data to Insights with Google Cloud

Course Certification

This course helps you prepare to take the:
Google Cloud Certified Professional Machine Learning Engineer Exam;

Course Outline

Module 01: Introduction to Data on Google Cloud

• Analytics Challenges Faced by Data Analysts
• Big Data On-premise Versus on the Cloud
• Real-world Use Cases of Companies Transformed Through Analytics on the Cloud
• Google Cloud Project Basics

Module 02: Analyzing Large Datasets with BigQuery

• Data Analyst Tasks, Challenges, and Google Cloud Data Tools
• Fundamental BigQuery Features
• Google Cloud Tools for Analysts, Data Scientists, and Data Engineers

Module 03: Exploring your Public Dataset with SQL

• Common Data Exploration Techniques
• Use SQL to Query Public Datasets

Module 04: Cleaning and Transforming your Data with Dataprep

• 5 Principles of Dataset Integrity
• Dataset Shape and Skew
• Clean and Transform Data using SQL
• Introducing Dataprep by Trifacta

Module 05: Visualizing Insights and Creating Scheduled Queries

• Data Visualization Principles
• Common Data Visualization Pitfalls
• Google Data Studio

Module 06: Storing and Ingesting New Datasets

• Permanent Versus Temporary Data Tables
• Ingesting New Datasets
• Differentiate between native BigQuery table storage and external data source connections
• Load new data into BigQuery

Module 07: Enriching your Data Warehouse with JOINs

• Merge Historical Data Tables with UNION
• Introduce Table Wildcards for Easy Merges
• Review Data Schemas: Linking Data Across Multiple Tables
• JOIN Examples and Pitfalls

Module 08: Advanced Features and Partitioning your Queries and Tables for Advanced Insights

• Advanced Functions (Statistical, Analytic, User-defined)
• Date-Partitioned Tables

Module 09: Designing Schemas that Scale: Arrays and Structs in BigQuery

• BigQuery Versus Traditional Relational Data Architecture
• ARRAY and STRUCT Syntax
• BigQuery Architecture

Module 10: Optimizing Queries for Performance

• BigQuery Performance Pitfalls
• Prevent Data Hotspots
• Diagnose Performance Issues with the Query Explanation Map

Module 11: Controlling Access with Data Security s

• Hashing Columns
• Authorized Views
• IAM and BigQuery Dataset Roles
• Access Pitfalls

Module 12: Predicting Visitor Return Purchases with BigQuery ML

• Machine Learning on Structured Data
• Scenario: Predicting Customer Lifetime Value
• Choosing the Right Model Type
• Creating ML models with SQL

Module 13: Deriving Insights From Unstructured Data Using Machine Learning

• ML Drives Business Value
• How does ML on unstructured data work?
• Choosing the Right ML Approach
• Pre-built AI Building Blocks
• Customizing Pre-built Models with AutoML
• Building a Custom Model

Course Mode

Instructor-Led Remote Live Classroom Training;

Trainers

Trainers are GCP Official Instructors and certified in other IT technologies, with years of hands-on experience in the industry and in Training.

Lab Topology

For all types of delivery, the Trainee can access real Cisco equipment and systems in our laboratories or directly at the Cisco data centers remotely 24 hours a day. Each participant has access to implement the various configurations thus having a practical and immediate feedback of the theoretical concepts.
Here are some Labs topologies available: