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Venkatesh Varadachari and Gollapudi Venkata Saikumar

If you are looking for that one course that will help you gain the confidence to take your IoT knowledge to next level, by integrating with Google Cloud Platform, then you have come to the right place.

With numerous custom made illustrations and animations, we have set the standard in terms of production quality. All so that you can have a terrific learning experience.

This course is meant for anyone who wants to build exciting projects on Google cloud platform and take their IoT projects to the next level

Read more

If you are looking for that one course that will help you gain the confidence to take your IoT knowledge to next level, by integrating with Google Cloud Platform, then you have come to the right place.

With numerous custom made illustrations and animations, we have set the standard in terms of production quality. All so that you can have a terrific learning experience.

This course is meant for anyone who wants to build exciting projects on Google cloud platform and take their IoT projects to the next level

If you are a hobbyist looking to get started with Google Cloud Platform or a student who wants to know how to build IoT applications on the Google IoT core and on the Google Cloud Platform, you will find this course very useful. This is because we have tailored this course by giving equal importance to both the projects as well as the concepts.

So come join me in this introductory course on Google Cloud IoT. I am looking forward to being your instructor and hearing about all the wonderful projects you were able to make using the Google Cloud IoT Core.

Enroll now

What's inside

Learning objectives

  • Google cloud platform
  • Internet of things
  • Sparkfun esp32 thing
  • Raspberry pi

Syllabus

Introduction to Google Cloud IoT
Introduction to the course
Google Cloud IoT Core Architecture
Getting started with IoT Core
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Download the PDF from the resources of this lecture

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Uses Sparkfun ESP32 Thing and Raspberry Pi, which are common platforms for prototyping and experimenting with IoT projects
Covers financial budgeting and alerts, which is useful for managing cloud resources and avoiding unexpected costs
Explores Twilio and SendGrid, which are third-party services that may require separate accounts and potentially incur costs
Requires OpenSSL installation, which may present a challenge for beginners who are not familiar with command-line tools
Examines Google Cloud Functions, Cloud Dataflow, and BigQuery, which are powerful tools for data processing and analysis

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Reviews summary

Introduction to google cloud iot

According to learners, this course provides a solid introduction to Google Cloud IoT, particularly praised for its practical, hands-on approach using Raspberry Pi and ESP32 for labs and projects. Many found the explanations clear and easy to follow, making it great for beginners and hobbyists. However, some students noted that certain sections, like Cloud Dataflow, felt rushed, and a few encountered issues with setup instructions or dependencies, although recent reviews suggest this might be improving. Overall, it successfully delivers a foundation in connecting devices to GCP, though some wished for greater technical depth on specific topics or security.
Covers core concepts, some parts rushed.
"Good overview of the Google Cloud IoT Core services."
"the part on Cloud Dataflow felt a bit rushed and could use more detail."
"A comprehensive introduction. Covers device setup, data ingestion, and visualization."
"Some topics could be expanded upon for intermediate learners, but it serves its purpose as an introduction."
Concepts are broken down effectively.
"Excellent introductory course to Google Cloud IoT. The explanations were clear..."
"The instructor did a great job breaking down complex topics into manageable parts."
"The pace is good for beginners."
"Instructor is knowledgeable and explains well."
Practical exercises enhance understanding.
"The hands-on labs using Raspberry Pi and ESP32 were incredibly valuable."
"Loved the practical approach. Building projects with Raspberry Pi and ESP32 made the concepts stick."
"As a hobbyist, this course was perfect. The step-by-step guides for setting up hardware and connecting to GCP were easy to follow."
"Fantastic hands-on experience! The practical labs are the highlight. Connecting physical devices to GCP made everything click."
Some students faced issues with labs.
"some instructions felt a little unclear at times."
"Some minor issues with library versions during setup, but troubleshooting wasn't too difficult."
"Found this course difficult to follow... Labs had issues with dependencies."
"Outdated instructions led to frustration with labs. Dependencies were a nightmare."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Google Cloud IoT with these activities:
Review Basic Networking Concepts
Reviewing basic networking concepts will help you understand how IoT devices communicate with the Google Cloud Platform.
Show steps
  • Review the OSI model and TCP/IP protocol suite.
  • Study common network protocols like HTTP, MQTT, and CoAP.
  • Understand IP addressing and subnetting.
Brush up on Python Programming
Practicing Python will be useful for interacting with the Google Cloud IoT Core and processing data from IoT devices.
Browse courses on Python Scripting
Show steps
  • Practice writing Python scripts to interact with APIs.
  • Review data structures and control flow in Python.
  • Familiarize yourself with relevant Python libraries like `google-cloud-iot`.
Build a Simple Temperature Monitoring System
Building a temperature monitoring system will give you hands-on experience with connecting a sensor to Google Cloud IoT Core.
Show steps
  • Connect a DHT11 sensor to a Raspberry Pi or ESP32.
  • Write a Python script to read temperature data and send it to Google Cloud IoT Core.
  • Visualize the temperature data in Google Cloud Data Studio.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Document Your IoT Project
Documenting your project will help you solidify your understanding of the concepts and share your knowledge with others.
Show steps
  • Describe the architecture of your IoT system.
  • Explain how you configured the Google Cloud IoT Core.
  • Document the code you wrote to interact with the sensor and the cloud.
Follow Google Cloud IoT Tutorials
Following Google Cloud IoT tutorials will provide step-by-step guidance on setting up and using the platform.
Show steps
  • Find tutorials on connecting different types of devices to Google Cloud IoT Core.
  • Follow tutorials on using Google Cloud Functions to process IoT data.
  • Explore tutorials on visualizing IoT data in Google Cloud Data Studio.
Create a Data Visualization Dashboard
Creating a data visualization dashboard will allow you to monitor and analyze the data collected from your IoT devices.
Show steps
  • Connect your Google Cloud BigQuery data to Google Data Studio.
  • Design a dashboard to display key metrics from your IoT devices.
  • Add interactive elements to your dashboard to allow users to explore the data.
Contribute to an Open Source IoT Project
Contributing to an open-source IoT project will give you valuable experience working with a real-world codebase and collaborating with other developers.
Show steps
  • Find an open-source IoT project on GitHub or GitLab.
  • Identify a bug or feature that you can contribute to.
  • Submit a pull request with your changes.

Career center

Learners who complete Introduction to Google Cloud IoT will develop knowledge and skills that may be useful to these careers:
Internet of Things Engineer
An Internet of Things Engineer, or IoT Engineer, designs, develops, and implements IoT solutions, often involving cloud platforms. This course helps build a foundation in Google Cloud Platform, a key technology for many IoT projects. With its comprehensive approach to projects and concepts, this course is particularly helpful for anyone looking to build exciting IoT deployments on the Google Cloud. This course’s focus on the practical implementation of Google Cloud IoT, using platforms such as Sparkfun ESP32 and Raspberry Pi, makes it a valuable starting point for aspiring IoT Engineers.
Cloud Solutions Architect
A Cloud Solutions Architect designs and implements cloud computing solutions for businesses, often specializing in a particular vendor, such as Google. This course may be useful for a solutions architect who works with IoT devices on Google Cloud. It introduces how IoT core is architected on Google's cloud infrastructure and how to send telemetry. By exploring this course, a Cloud Solutions Architect can learn how to integrate IoT devices into the broader cloud architecture. This course also helps one understand cloud functions and databases, which is key for data processing in cloud solutions.
Cloud Application Developer
A Cloud Application Developer builds and maintains applications that run on cloud platforms. This course may be useful to an application developer who wants to integrate IoT devices with their cloud-based applications on Google Cloud Platform. It covers how to send data to cloud and trigger devices, this is essential when building applications that interact with IoT devices. This course also helps to understand Google Cloud Functions, which are often integrated with applications on Google Cloud. This course helps an application developer to understand the specific features required for building IoT cloud applications.
Embedded Systems Engineer
An Embedded Systems Engineer develops software for devices such as microcontrollers and hardware platforms. This course may be useful for an embedded systems engineer who is looking to integrate devices with Google Cloud. This course includes learning how to interface hardware platforms like the ESP32 and Raspberry Pi with a cloud infrastructure. The course's focus on sending data to the cloud and triggering devices from the cloud may help an embedded systems engineers understand cloud integration. This course can also help an embedded systems engineer leverage cloud based services for embedded systems.
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines for data storage, processing, and analysis. This course may be useful for an aspiring Data Engineer who wishes to work with IoT data. The course covers how to send telemetry to the cloud and explore cloud storage options. It also provides an overview of dataflow, big query, and data studio. These tools are often used by Data Engineers when designing data pipelines and visualizing data. This course can help a Data Engineer understand the dataflow from a device to the cloud.
Automation Engineer
An Automation Engineer designs and implements automated systems, often involving hardware and software integration. This course may be useful to an automation engineer who wishes to integrate cloud and IoT into their systems. The course covers the use of cloud functions, notifications, and scheduling of jobs. These tools are often used in automation solutions. The course also covers the use of devices like ESP32 and Raspberry Pi. An Automation Engineer may find this course helpful for learning to incorporate IoT devices into automated systems.
Software Developer
A Software Developer writes code for applications and systems. This course may be useful for software developers looking to expand their skill set to include cloud and IoT. This course delves into sending data to the cloud, triggering devices from the cloud, setting up cloud functions, and using notification services. These tasks are important for developing cloud based software that interacts with IoT devices. This course helps a software developer build cloud based solutions that work with IoT devices.
Technology Consultant
A Technology Consultant advises clients on how to use technology to reach business goals. This course may help a consultant when working with businesses that are looking for IoT solutions deployed on the cloud. This course covers the basics of Google Cloud Platform for IoT, as well as how to send data and manage devices on that platform. A Technology Consultant may find this helpful for understanding the practicalities of using cloud with IoT. This course provides knowledge of IoT implementations that would be useful for a technology consultant.
Data Analyst
A Data Analyst interprets data to identify trends and insights. This course may be useful for a data analyst who wants to work with IoT data. The course covers data visualization and explores tools like Bigquery and Data Studio. These are frequently used by Data Analysts to analyze and visualize data. The course focuses on getting data from devices to the cloud, which is a first step for many data based projects. A data analyst may find this course helpful for understanding the data flow from IoT devices to their analysis platform.
Research Scientist
A Research Scientist conducts experiments and studies to gain new knowledge in a specific field. This course may be useful for a researcher interested in IoT related research. The course covers the basics of using Google Cloud Platform for IoT projects, including how to send data to the cloud and how to interface with devices. Depending on their area of research, this course may help a research scientist looking to utilize cloud in their research process. The cloud-based tools in this course could be useful for exploring research questions.
Solutions Engineer
A Solutions Engineer works closely with clients to solve their technical problems using the company’s products or services. This course may be useful for a solutions engineer who needs to understand how to integrate IoT devices with Google Cloud Platform. This course covers the fundamentals of Google Cloud IoT Core, device management and data handling. This course provides the hands-on experience to effectively communicate with clients about their cloud based solutions using IoT devices. This course helps a solutions engineer to have a better understanding of IoT integration.
Technical Project Manager
A Technical Project Manager oversees technical projects, ensuring they are completed on time and within budget. This course may be useful for a project manager who needs to oversee projects involving IoT and cloud. The course provides an overview of the Google Cloud Platform, especially its IoT core, and practical examples of its application. The course includes topics like financial budgeting and alerts, which can be helpful in a project manager's role. This course helps a technical project manager who needs to manage IoT projects on the Google Cloud.
Systems Administrator
A Systems Administrator manages and maintains computer systems and networks. This course may be useful for a systems administrator who wants to manage devices connected to Google Cloud. This course provides an introduction to Google Cloud IoT core architecture, registries, and device registration. This course can help a systems administrator learn how to manage IoT devices connected to the Google Cloud. Specifically, this course helps a systems administrator gain a foundational understanding of IoT in cloud settings.
Network Engineer
A Network Engineer designs, implements, and manages computer networks. This course may be useful for a network engineer looking to understand how IoT devices connect to cloud platforms. This course introduces IoT core architecture and how devices send data to the cloud over a network. This course helps a network engineer understand how IoT devices communicate with the cloud over a network. This course can improve a network engineer's ability to integrate IoT devices with their current network.
Technical Trainer
A Technical Trainer develops and delivers training programs on technical topics. This course may be useful for a technical trainer who is interested in teaching others about IoT and cloud computing. The course provides an introduction to Google Cloud IoT, and it also includes hands-on projects. This course's approach to projects and concepts would be helpful for a technical trainer preparing to teach others by leveraging its instructional material. Such an approach could increase a technical trainer's effectiveness.

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Introduction to Google Cloud IoT.
This official guide from the Raspberry Pi Foundation provides a comprehensive overview of the Raspberry Pi computer, including its hardware, software, and various applications. It is an ideal starting point for beginners looking to get up and running with Raspberry Pi.
Seminal work on the grammar of graphics, a formal language for describing data visualizations. It covers a wide range of topics, from the basics of the grammar of graphics to the use of the grammar of graphics to create a variety of charts and graphs.
This classic book by Edward Tufte must-read for anyone interested in data visualization. It covers a wide range of topics, from the principles of visual perception to the design of effective charts and graphs.
Is specifically focused on Apache Beam, the programming model underlying Cloud Dataflow. It provides a general description of the Apache Beam model with examples, helping to create a solid understanding of the subject. It covers both batch and streaming processing pipelines and practical guide for implementing data processing pipelines with Beam. This book is essential for understanding the core concepts executed by Cloud Dataflow.
Similar to the other official study guides by Dan Sullivan, this book key resource for the Professional Data Engineer certification. It covers the concepts and practices required for data engineering on GCP, including data processing, analysis, and machine learning.
Focused specifically on cloud security on GCP, this book is invaluable for those preparing for the Professional Cloud Security Engineer certification. It covers cloud security basics, GCP security tools, and their implementation through clear explanations and practice exercises.
An expert guide for the Professional Machine Learning Engineer certification, this book covers the entire ML process on GCP, from data and feature engineering to model training and deployment using Vertex AI, TensorFlow, and Kubeflow.
Aimed at the Associate Cloud Engineer certification, this book provides a solid understanding of deploying and managing applications and infrastructure on GCP. It's an excellent resource for beginners and those looking to validate their foundational GCP skills.
Is tailored for individuals pursuing the Professional Cloud Network Engineer certification. It covers all exam objectives and provides hands-on examples using gcloud commands, making it a practical guide for network professionals on GCP.
A practical guide focusing on operationalizing scalable data analytics systems on GCP. It covers services like BigQuery, Cloud SQL, Cloud Storage, and Dataflow with hands-on examples. is highly relevant for those interested in data engineering on GCP and preparing for the Professional Data Engineer exam.
While not exclusively about Cloud Functions, this book foundational text for understanding the underlying principles of building scalable and reliable distributed systems, which is crucial for effective serverless development. It provides essential background knowledge on data management, consistency, and fault tolerance. must-read for anyone serious about designing robust cloud-native applications, including those using Cloud Functions.
Specifically designed for beginners, this book provides a solid foundation in GCP capabilities. It covers setting up accounts, using core services like Cloud Storage, Compute Engine, and Kubernetes Engine. It is particularly useful for those preparing for the GCP Associate Cloud Engineer certification.
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Authored by key contributors to the Dataflow model and Apache Beam, this book foundational text on the concepts of large-scale stream processing. It delves into the theoretical underpinnings, including watermarks and exactly-once processing, which are critical to understanding how Cloud Dataflow handles unbounded data. While not solely about Dataflow, it provides the essential conceptual background.
Provides a comprehensive overview of data visualization, covering the basics of visual perception, data types, and chart types. It great resource for beginners who want to learn the fundamentals of data visualization.
This project-based book provides a collection of 25 fun and creative projects for using Raspberry Pi. It covers topics like building a retro gaming console, creating a motion-activated security camera, and controlling home appliances with your voice. It great resource for makers and hobbyists looking for inspiration.
Delves into building, training, and optimizing machine learning models on GCP using services like Google Cloud Machine Learning Engine and TensorFlow. It's a practical guide for data scientists and ML developers looking to leverage GCP for their projects.
Focuses on applying data science techniques on GCP, leveraging its various data services. It's a valuable resource for data scientists and analysts who want to perform data processing and analysis at scale on the platform.
This guide is ideal for anyone looking to become familiar with the comprehensive list of services in GCP, including compute, storage, database, networking, and big data. It covers essential concepts and provides an overview of best practices for deploying workloads. It good starting point for beginners and cloud professionals migrating to GCP.
Focusing specifically on AWS Lambda, a key technology related to Cloud Functions, this book offers practical, example-driven guidance on building event-driven serverless applications. It's excellent for deepening understanding through hands-on examples. It serves as a useful reference for developers working with AWS Lambda and provides concrete patterns for implementing serverless functions.
Explores architectural patterns specifically for serverless systems. It's valuable for architects and senior engineers looking to design well-structured and maintainable serverless applications. It serves as a useful reference for design choices.
Offers a hands-on introduction to Google Cloud, covering practical skills and use cases. It's suitable for newcomers to the cloud and those who prefer a practical approach to learning GCP's core concepts and services.
Explores using GCP's AI-powered services for various applications, from chatbots to image analysis. It's suitable for those with a background in math and Python who want to apply AI/ML on GCP. It provides step-by-step guidance for building and training models.
Guides the reader through building scalable applications on GCP, starting with App Engine and Compute Engine. It covers implementing authentication, security, and using Cloud APIs, making it a practical guide for developers.
Delves into building event-driven architectures using patterns like Event Sourcing and CQRS, which are highly relevant for advanced serverless applications. It provides practical guidance on implementing these patterns.
A guide to using Data Studio for marketers, covering topics such as tracking marketing campaigns, analyzing customer behavior, and reporting on results.
Provides a solid foundation in serverless architectures, specifically focusing on AWS. It covers core principles, patterns, and real-world case studies, making it highly relevant for understanding the broader context of Cloud Functions. While focused on AWS, the architectural patterns discussed are applicable to other cloud providers and are essential for anyone building serverless applications. It valuable reference for understanding how serverless fits into modern cloud development.
Provides a comprehensive overview of the Internet of Things (IoT), covering the fundamentals, technologies, and applications. It is suitable for beginners and intermediate learners who want to gain a solid understanding of IoT.
Provides an excellent general overview of GCP services, covering deployment of scalable cloud applications. It's suitable for those new to GCP but with some cloud experience, offering practical insights and worked examples. It serves as a strong foundation for understanding the breadth of GCP's offerings.
Provides a deep dive into building serverless solutions using Azure Functions specifically with the C# language. It covers triggers, bindings, and building scalable applications. It's highly relevant for developers working with C# on Azure Functions.
Is designed as an entry point to GCP and the Cloud Digital Leader certification. It simplifies basic technological elements of GCP and is suitable for aspiring IT professionals and enthusiasts. It covers cloud fundamentals, data, AI/ML, infrastructure, and security.
A detailed exploration of patterns for building microservices, covering topics like decomposition, testing, and deployment. This valuable reference for architects and senior developers designing serverless solutions that involve multiple functions or services.
Event-driven architecture natural fit for serverless computing and Cloud Functions. provides a comprehensive guide to designing and building systems based on events and streaming data, which is highly relevant for advanced serverless patterns and integrations.
Offering a collection of practical recipes, this book provides solutions to common tasks and challenges on GCP. It's a useful reference for developers and administrators needing quick, step-by-step guides for implementing various GCP services.
Focuses on teaching readers how to use the Raspberry Pi's GPIO (General Purpose Input/Output) pins to control external devices and sensors. It provides a comprehensive overview of GPIO programming with Python and includes several hands-on projects.
Serverless functions are often used in conjunction with microservices architectures. highly-regarded guide to designing and building microservices, offering valuable insights into decomposition strategies, integration patterns, and testing. Understanding microservices is essential for effectively utilizing Cloud Functions in complex applications. It widely used reference in the industry.
Focuses on Azure Functions, guiding the reader from basics to more advanced concepts like Durable Functions. It's suitable for those starting with serverless development on Azure and provides hands-on examples for building scalable applications.
Beginner's guide to using Tableau, one of the most popular data visualization tools. It covers the basics of Tableau, as well as how to use Tableau to create a variety of charts and graphs.
This beginner-friendly book provides a step-by-step guide to setting up and using Raspberry Pi. It covers essential topics like installing software, connecting peripherals, and troubleshooting common issues. It great resource for students and anyone new to Raspberry Pi.
Focuses on the design aspects of IoT systems, including architecture, protocols, and security. It is suitable for intermediate and advanced learners who want to develop and implement IoT solutions.
Offers a high-level overview of GCP services through illustrations, making complex concepts more accessible. It's a valuable resource for quickly grasping the relationships between different GCP components and is suitable for visual learners and those seeking a quick reference.
Provides a friendly and framework-agnostic introduction to streaming systems concepts. It explains core ideas like data parallelization, event windows, and backpressure, which are fundamental to understanding how systems like Cloud Dataflow handle real-time data. It's a good resource for gaining a conceptual understanding of streaming.
While not solely focused on GCP, this book provides a strong foundation in cloud computing principles, architecture, and security that are highly relevant to understanding any cloud platform, including GCP. It's beneficial for gaining prerequisite knowledge.
Covers data analytics on GCP and includes information on using Cloud Dataflow for data processing and transformation. It helps users understand how to leverage Dataflow as part of a data analytics solution on Google Cloud. It's a practical guide for applying Dataflow in an analytics context.
Explores building full-stack applications using serverless technologies on AWS, incorporating modern frontend and API technologies. It provides a broader perspective on how Cloud Functions fit into a complete application architecture.

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