Google Cloud Platform Big Data and Machine Learning Fundamentals

Overview This course on Google Cloud Platform Big Data and Machine Learning Fundamentals offers an in-depth exploration of cloud-based big …

Google Cloud Platform Big Data and Machine Learning Fundamentals

Google Cloud Platform Big Data and Machine Learning Fundamentals

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Google Cloud Platform Big Data and Machine Learning Fundamentals Overview

This course on Google Cloud Platform Big Data and Machine Learning Fundamentals offers an in-depth exploration of cloud-based big data and machine learning technologies. You’ll start with the basics of data warehousing and quickly progress to more advanced topics like data flow, virtual data management, and data visualisation using Google’s powerful BigQuery tool.

Learning Outcomes

  • Understand the fundamentals of data warehouses and their role in big data analytics.
  • Gain proficiency in using Google BigQuery for data analysis.
  • Perform your first data exploration to uncover patterns and insights.
  • Learn the basics of data flow within cloud environments.
  • Dive deeper into the functionalities and features of BigQuery.
  • Create and manage virtual data views to streamline workflows.
  • Apply techniques for effective data visualisation to communicate findings.
  • Develop skills to write intermediate-level SQL queries for complex data analysis.
  • Appreciate the importance of scalable data architecture in supporting big data initiatives.
  • Master the integration of machine learning capabilities with big data tools for predictive analytics.

Who Is This Course For

This course is designed for IT professionals, data analysts, and anyone with a foundational knowledge of database concepts who wishes to expand their skill set in big data and machine learning on the Google Cloud Platform. It is ideal for those looking to leverage cloud technologies for data processing, analysis, and visualization, and it provides valuable skills that are increasingly in demand across various industries.

Eligibility Requirements

Candidates for this course should have a basic understanding of database structures and a genuine interest in data science and machine learning. Prior experience with SQL and a foundational knowledge of programming are recommended to benefit from the course materials fully. This course is particularly suitable for those looking to enhance their technical skills in cloud-based technologies.

Entry Requirements

  • Age Requirement: Applicants must be 16 or older, making the course accessible to both young learners and adults.
  • Academic Background: No prior qualifications required, open to all backgrounds.
  • Language Proficiency: A good understanding of English is essential, as all lessons are in English.
  • Numeracy Skills: Basic writing and numeracy skills are needed to follow the course content.

Why Choose Us

  • Affordable, engaging & high-quality e-learning study materials;
  • Tutorial videos/materials from the industry-leading experts;
  • Study in a user-friendly, advanced online learning platform;
  • Efficient exam systems for the assessment and instant result;
  • The UK & internationally recognised accredited
  • Access to course content on mobile, tablet or desktop from anywhere, anytime;
  • The benefit of career advancement opportunities;
  • 24/7 student support via email.

Career Path

Upon completion of this course, participants will be well-equipped to pursue careers in cloud computing and data science. Opportunities include roles in project management, data analysis, and machine learning engineering where proficiency in big data tools and technologies is crucial. This course also serves as a stepping stone towards more advanced certifications and roles that focus on architecting and managing big data solutions on cloud platforms.

Course Curriculum

Unit 01: Introduction
Section 01: Welcome to This Course 00:01:00
Section 02: How to Get Maximum Value from This Course 00:06:00
Section 03: Course Structure & Coverage 00:02:00
Section 04: Technology in This Course 00:02:00
Unit 02: Introducing Data Warehouse & BigQuery
Section 01: Data Warehouse 00:07:00
Section 02: Start With BigQuery 00:05:00
Section 03: BigQuery Web User Interface 00:04:00
Unit 03: First Exploration
Section 01: First Data 00:04:00
Section 02: Basic Exploration 00:16:00
Section 03: Functions 00:14:00
Section 04: Common Data Types 00:07:00
Section 05: Different Query 00:01:00
Section 06: Exploring Common Data Types 00:25:00
Section 07: Converting Data Types 00:07:00
Unit 04: Data Flow Basic
Section 01: Data Quality 00:06:00
Section 02: Clean & Transform 00:13:00
Section 03: Store Data 00:06:00
Section 04: Upgrading From Sandbox Account 00:01:00
Section 05: Clean & Transform With Dataprep 00:25:00
Section 06: Scheduled Query 00:04:00
Section 07: Analyze Data 00:05:00
Section 08: Data Visualization 00:06:00
Unit 05: Diving into BigQuery
Section 01: Essential BigQuery 00:15:00
Section 02: Load Data into BigQuery (Part 1) – The Basic 00:36:00
Section 03: Tip: Mock Data 00:01:00
Section 04: Load Data into BigQuery (Part 2) – Handling Errors 00:22:00
Section 05: Load Data into BigQuery (Part 3) – Efficient Load 00:14:00
Section 06: Load Data into BigQuery (Part 4) – From Your Data to BigQuery 00:23:00
Section 07: Load Data into BigQuery (Part 5) – In Microservice Architecture 00:20:00
Section 08: Tip: Message Broker Overview 00:08:00
Section 09: Load Data into BigQuery (Part 6) – Recurring Load 00:12:00
Unit 06: Virtual Data using View
Section 01: BigQuery View 00:06:00
Unit 07: Data Visualization
Section 01: What We Will Learn 00:01:00
Section 02: Google Sheets & BigQuery 00:10:00
Section 03: Google Data Studio 00:13:00
Unit 08: Intermediate Query
Section 01: Using Join – Theory 00:04:00
Section 02: Using Join – Hands On 00:16:00
Section 03: Union & Intersect 00:06:00
Section 04: Basic Statistical Functions 00:05:00
Assignment
Assignment – Google Cloud Platform Big Data and Machine Learning Fundamentals 00:00:00
Order Certificate
Order Certificate 00:00:00

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