We’ve done a thorough research and listed the best courses for Google Cloud Certification in 2021. These courses will help you achieve the career goal that you’ve always wanted.
We’ve looked into some of the best Google Cloud Certification courses that are available online. You can sign up for any of these courses and elevate your career goals.
Let’s explore all the best Coursera Google Cloud course that is available online to conclude which Google Cloud certification is best.
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Best Course for Google Cloud Certification
1. Google Cloud Platform Fundamentals: Core Infrastructure
Note: If you’re already aware of some of Google Cloud concepts and want to explore more to advance your career, then you can find the best Google Cloud Platform Courses on Coursera. Start exploring the Coursera Google Cloud Course by jumping to the next heading.
Before diving into any of the Google Cloud courses, you should be aware of some of the core concepts of Google Cloud Platform. If you’re a beginner in cloud computing, then this course is recommended before taking some advanced courses in Google Cloud.
By taking this course, you’ll learn some of the essential concepts to work on Google Cloud Platform (GCP). This course begins by providing introductions from the basics concepts, such as the evolution of cloud computing. Learning from the basics will give you more insight into understanding cloud computing.
Additionally, the hands-on labs will give you the edge to work on real-world projects.
Let’s look at the key takeaways of this course:
- Learn from the basics of cloud computing to the essential concepts of GCP.
- Understand IAM, Identity and Access Management to manage who does what in the Google Cloud. You can assign specific permission to the individuals who work on particular tasks – thus giving you granular control of your cloud resources.
- Learn to use Compute Engine in Google Cloud.
- Understand several Google Cloud storage options that are Cloud SQL, Cloud Storage, Cloud Spanner, Cloud Datastore, and Google Bigtable.
- Containers and the container orchestration techniques on the Google Cloud using Kubernetes.
- Understand what the app engine is and how it works.
- Understand Machine Learning and Big Data services in the GCP and how it is useful.
This course duration is about 14 hours, and you can complete the fundamentals of Google Cloud Platform in about a week by dedicating 2 hours per day.
2. Architecting with Google Compute Engine Specialization
Architecting with Google Compute Engine certification course is designed by Google and consists of 5 courses in this specialization. This course concentrates on the core topic of Google Cloud that is Google Compute Engine but not limited to it.
Hence, if you’re the one who wants to learn Google Compute engine and other core services of Google Cloud, then this is the right course for you. Google Cloud Identity and Access Management, load balancing, and autoscaling are some of the few essential topics that are covered in this course.
This course is intended and designed for those who specialize in DevOps, Cloud Solutions Architects, and individuals who want to learn Google Compute Engine. Architecting with Google Compute Engine course is composed of several teaching methods that includes presentations, hands-on labs, and demos.
Let’s briefly go through what you’ll be learning in this course.
Key takeaways of this course are as below:
- You’ll learn and compare different computing services and storage services available in the Google Cloud Platform.
- Learn Google Cloud Identity and Access Management, which is an important concept in Google Cloud.
- Understand the difference in Google Storage and Compute services.
- Learn the overview of monitoring the resources in the Google Cloud Platform.
- You also learn different load balancing types in GCP and auto-scaling configurations.
- Learn to use the Deployment Manager to automate infrastructure deployment.
- Build efficient and highly reliable solutions in GCP.
By allowing 4-8 hours of your time studying in a week, you can complete this course in about 5-6 weeks.
3. Getting Started with Google Kubernetes Engine
Getting Started with Google Kubernetes Engine is an accelerated course that can be completed in one week. Learners who want to learn the Docker containers and Kubernetes Engine in Google cloud should sign up for this course.
This course is intended for Cloud Solution Architects, DevOps engineers, application developers, and IT managers. This course by Google offers interactive labs from Qwiklabs so that students can learn effectively.
Before signing up for this course, it is crucial to understand that the students should have a basic understanding of Linux OS, basic command-line tools, and knowledge on Nginx.
Key takeaways of this course are as below:
- Learn the basics of containers and deploy an existing application.
- Understand the concepts of Kubernetes and Google Kubernetes Engine.
- You’ll be able to deploy applications in Kubernetes using the CLI.
- Use Jenkins to set up a continuous delivery pipeline.
Since this course duration is of 8 hours, you can complete this course within a week. Once you complete this course, you can sign up for Architecting with the Google Kubernetes Engine course. This course will take you to provide more in-depth concepts on Kubernetes Engine.
4. Architecting with Google Kubernetes Engine Specialization
By taking this course by Google Cloud, you’ll learn to implement solutions using Google Kubernetes Engine (GKE). The course consists of 4 courses in Architecting with Google Kubernetes Engine certification course.
Using Google Kubernetes Engine, you’ll learn to build, schedule, balance load, and monitor the workloads. Learners will be able to deploy and manage containers on GKE in the Google Cloud Platform (GCP). If you know the basic command-line tools and know-how to operate Linux OS, you should be good to take this course.
The demand for Kubernetes skills set is booming right now in the current job market, which means that you’ll be able to apply for more jobs after completing this course. You’ll learn to deploy and scale the Kubernetes applications without any hiccups. You are also exposed to networking concepts when working with the Google Kubernetes Engine.
Sign up to this course if you are more latest technology of containerization techniques using Kubernetes in Google Cloud Platforms. After learning the core infrastructure of Google Cloud, you’ll dive right into the GKE. Once you complete this course, you will be proficient in Architecting with Google Kubernetes Engine.
Key takeaways of this course are as below:
- Learn how to organize resources in GCP to manage them efficiently.
- Understand all the tools required to connect, change, allocate, and release resources in GCP.
- You’ll be able to build and configure Kubernetes containers in GCP with ease.
- Learn to deploy the Kubernetes cluster using GKE and deploy pods to the GKE cluster.
- You learn to connect to Google Kubernetes Engine clusters and use it to create, inspect, interact, and delete pods.
- Also, you’ll learn to control which nodes pods may run.
- Understand the authentication and authorization of Kubernetes in GCP.
- Create health checks on your running applications.
By dedicating yourself with 2-3 hours per day, you can complete this course in 2 months. Don’t worry about the long term learning of the course. Two months may seem too long to learn, but the knowledge you gain will be with you forever.
5. Security in Google Cloud Platform Specialization
If you’re looking forward to enhancing your cloud computing career with the advanced topics, then the Security in Google Cloud Platform is the one you should be pursuing. That is if you’re interested both in cloud computing and cloud security.
Security in Google Cloud Platform certification course consists of 3 courses that will teach all the essential security concepts. These three courses will teach the basics to advanced topics, and all you need to know to improve security in the cloud.
To signup for this course, you don’t need any prior knowledge of anything. Because this specialization course comes with the Google Cloud Fundamentals course, this will teach you to get started from the basics of Google Cloud to advanced topics.
Cloud security is one of the booming careers right now. This is the best online course in Google Cloud Security. This self-pacing training by Coursera will guide you through the video training and hands-on labs.
The participants of this course will be provided with the breadth of different security techniques and controls on GCP. This essential in understanding Google Cloud security.
Key takeaways of this course:
- Learn the foundations of cloud security in GCP and understand the shared security responsibility model.
- Understand IAM and isolating VPC in Google Cloud for enhanced security.
- Learn the best practice of VPC networks and configuring VPC firewalls.
- Manage cloud devices, cloud users, and cloud apps from a single console.
- Manage VM logins and use organization policies to restrict access to cloud resources.
- Use Customer Supplied Encryption Keys to encrypt persistent disks.
- Learn to secure data by following the best practice of storage and protect against DDoS attacks.
By dedicating 2-3 hours per day, you can complete the Security in Google Cloud Platform Specialization course in about one month.
6. Developing Applications with Google Cloud Platform Specialization
Developing applications in the Google cloud is one of the best courses for Google Cloud certification for app developers. Application developers will learn to design, develop, and deploy applications in the GCP.
This course consists of 4 courses. By taking this course, you can complete their hands-on labs with your favorite programming language. It can either be Java or Python or Node.js.
Developing Applications with Google Cloud Platform certification course is designed by Google and intended for app developers who are interested in developing cloud-native applications. You can achieve this by following their video training, presentations, demos, and hands-on labs.
To get the most out of this course, you should have a working knowledge of Node.js, basic command-line tools, and Linux operating systems. Let’s briefly look into what you’ll learn in this course.
Key takeaways of this course:
- Learn the fundamentals of Google Cloud core infrastructure.
- Understand the best practice for application development in GCP.
- Introduction to Google Cloud SDK, Google Cloud Client Libraries, and Google Firebase SDK.
- Learn various data storage options for developing applications in GCP and best practice for using Cloud Datastore.
- Develop authorization and authentication for your applications in the Google Cloud Platform.
- Add intelligence to your applications using pre-trained machine learnings APIs.
- Learn to use the Cloud Functions and Cloud Endpoints for your application.
- Understand the different execution environments in GCP.
- It also covers the essentials of monitoring, debugging, and tracing performance of your application using Stackdriver.
By learning at least 2 hours per day, you will be able to complete this course in a month.
7. Networking in Google Cloud Platform Specialization
Networking in the Google Cloud Platform certification course is available in Coursera. This course involves deep-dive training on networking in Google Cloud. This course is 100% self-paced training, which consists of demos, video classes, and hands-on labs.
Networking in the GCP course consists of 3 courses. It is strongly recommended that you take all three courses in the specified order, that is starting from GCP – Core fundamentals. To get the highest benefit out of this course, you should have prior knowledge of 7 Layers of the OSI model, understanding IPv4 address, and managing IPv4 routes.
Since networking is one of the essential elements to run many services on the internet, it is one of the crucial course. Hence, you must learn from the basics. Once you complete the fundamentals, you will advance to networking concepts involved in the Google Cloud Platform.
This course involves a broad study of Cloud infrastructure and networking in the Google Cloud Platform.
Key takeaways of this course:
- Understand the fundaments of VPC and learn to configure VPC networks, subnets, and routers in Google Cloud.
- Control restricted access to the VPC objects.
- Learn about the shared VPC and VPC Peering that allows configuring private communications.
- Understand the difference between all five load balancers in GCP.
- Reduce the billing in Google Cloud Platform by administering billing.
- Learn about the most common network designs and use the Deployment Manager to automate the deployment of the network.
- Logging and network monitoring will help you troubleshoot your network infrastructure in GCP.
You can complete this course in one month and be ready to work on real-world projects.
8. Developing APIs with Google Cloud’s Apigee API Platform Specialization
Developing APIs in the Google Cloud Platform course from Coursera consists of 3 courses in this specialization certification. This course is designed by Google to introduce you to Google Cloud’s Apigee and how to apply them to your API.
This course consists of 3 courses, and the only prerequisite is a basic understanding of APIs and software development. If you are not sure what they are, you can simply learn by doing some research on Google before signing up for this course.
This specialization certification course is targeted for API developers. Though this is a fundamental course, it is highly recommended to have prior training before working on Google Cloud Apigee.
Your learning approach will start by navigating through the Apigee Edge UI and then understanding the best practice to follow to design API.
Key takeaways of this course:
- Learning to use Apigee Edge UI and designing an API.
- Hands-on lab to create OpenAPI specification in Apigee Edge.
- Deep dive into API policies and learning to include them in API proxy.
- Explore how to use the flow hooks, share flows, and extensions in Apigee Edge.
- It also covers important topics such as Mash Ups, Service Callouts, and Advance Mediation.
- Learn to secure the API keys.
- Understand different grant types that can be used in your API proxy. Hands-on labs will be provided to implement this.
After signing up for this course, you can complete this course in about one month. Once completed, you will earn a certificate that can be shared in your professional networks.
9. Data Engineering, Big Data, and Machine Learning on GCP Specialization
If you are in the pursuit of becoming an expert in Data Engineer, then you must sign up for this Google Cloud Courses on Coursera. Data Engineering, Big Data, and Machine Learning on the GCP certification course are one of the best online courses on Google Cloud. Also, check the best data engineering certification courses online.
This data engineer specialization certification course comes with five courses. You should consider taking this course if you’ve 1 year of professional experience in any one or more of the following skillset– SQL, Data modeling, ETL activities, Python, Machine learning, or Statistics.
In the first course out of 5, you’ll learn to understand the capabilities of Big Data and Machine learnings on Google Cloud Platform. Then you’ll proceed to learn to build the data lakes and data warehouse in Google Cloud. Further learnings in the course will cover many technologies utilized on Google Cloud Platform for BigQuery, Spark on Cloud Dataproc, pipeline graphs in Cloud Data Fusion, etc.
You will learn some advanced topics in this course. Hence Google has specially designed this course to be understood by anyone. Because the course starts from the basics before advancing to complex topics, don’t be overwhelmed by the amount of study time this course involves. In the end, it will be worth it.
Key takeaways of this course:
- Understand the essential information of Big Data and Machine Learning GCP.
- Learn to migrate your existing SQL to Google Cloud using CloudSQL and Cloud Dataproc.
- You’ll also learn to use TensorFlow to train and use Neural Networks in GCP.
- Learn different methods of data loading on GCP.
- Able to learn to manage data pipelines with Cloud Data Fusion and Cloud Composer.
- Learn about streaming data that involves Google BigQuery and Bigtable.
- Use the pre-built ML API’s to build different ML models.
- Gain business insights from large datasets using GCP BigQuery.
You can complete this course and earn the Coursera certification in about 4-7 weeks after enrolling into the course. The certificate from Coursera Google Cloud Certification will add many benefits to your career.
10. From Data to Insights with Google Cloud Platform Specialization
Data to Insights with Google Cloud Platform certification course consists of 4 accelerated course in Coursera. This course will teach you to gain insights from the data analysis and visualization using GCP. The hands-on labs from this course will allow learners to mine, explore, load, visualize, and extract insights using Google BigQuery Datasets.
This course is specifically intended for Business Analysts, Data Analysts, Business Intelligence, and Data Engineers who build scalable solutions on Google Cloud Platform. Also, there is no harm if you are interested in or pursuing these job roles. Getting certified in this specialization course will make you an ideal candidate for new job roles. However, please note that it is recommended that learners should have some knowledge of ANSI SQL.
You’ll gain insight on everyday challenges that data analysts face every day and solve them with big data tools on GCP. Next, using Google Data Studio, you’ll learn to ingest external data and visualize them. Then you’ll see demos of Machine Learning in action by learning key ML terms. The interactive labs will appeal to you to use pre-trained ML APIs to build your ML models.
Key takeaways of this course:
- Understand the big data tools on GCP, which you will use to analyze and visualize data.
- Learn how important it is to create high-quality datasets and necessary tools to achieve it.
- You’ll be able to load and create new datasets and when to use SQL JOINS and UNIONs.
- Learn to use Google Data Studio to compare data visualizations.
- Secure the datasets which are crucial to any organization.
- Learn Cloud Datalab, which is a key tool to use in the Data Scientist toolkit.
- Learn everything about machine learning on how it benefits your organization.
It would take around one month to complete Data Insights with Google Cloud Platform course on Coursera. Take your sweet time to understand every concept in detail and not to skip any of the topics.
11. Machine Learning with TensorFlow on Google Cloud Platform Specialization
One of the best Google Cloud Platform courses for ML is Machine Learning with TensorFlow on GCP. This course is composed of 5 courses. You can signup for this course if you have programming experience or a keen interest in learning machine learning.
Machine Learning with TensorFlow on GCP course starts from the basics where you’ll learn what the machine learning is and different kinds of ML. Since you’ll be working on Machine Learning, it would be beneficial that you know at least the basic concepts of Python programming language.
With the introduction of TensorFlow, you’ll learn all the necessary concepts and APIs in ML models. Since ML requires hands-on to learn it effectively, this course has Quiklabs to provide you with interactive labs. The course instructor will provide a walkthrough of the solutions in the labs. They will be made public for you in the later stage so that you can work on your own on future projects.
Key takeaways of this course:
- Understand what Google means when they say AI-first.
- Learn the main types of ML to accelerate your career growth to become an ML practitioner.
- After building the ML model on GCP, it is essential to learn to optimize your model.
- Study the TensorFlow model and train it using GCP infrastructure.
- Understand the modern-day ML methods where the feature crosses play a crucial role.
- Learn to use the TensorFlow tf.Transform library in pre-processing data.
- The final course involves the art and science of Machine Learning on GCP.
It would take 30-45 days to complete this course and entirely depends on how you allocate time to study. Also, the ability to grasp the concepts will play a vital role in studying. Once you finish this course, you can enroll for Advanced Machine Learning with TensorFlow, which is highlighted in the next course.
12. Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization
The Advanced Machine Learning with TensorFlow on Google Cloud Platform course involves five courses. To get the most out of this specialization course, you must have completed the earlier course Machine Learning with TensorFlow on GCP, experience in Python, statistics, and basics of SQL.
Since this is the advanced course of the ML with TensorFlow, you’ll learn end to end machine learnings with their workshop. This course teaches some of the production-ready tasks to train you everything on the Machine Learning concepts.
You’ll learn to design adaptable and high-performance ML systems and still be conscious of the cost. And you learn to work with sequences and neural networks, which all part of the essential AI concepts.
Key takeaways of this course:
- Take your Machine Learning career one step further on GCP.
- Create the dataset and build the ML model using TensorFlow.
- Review some of the high-level design involving your ML model.
- Learn the different ways of ingesting data on to the Google Cloud to power your ML models.
- Understand the benefits of leveraging the hybrid machine learning model and when to implement it.
- You’ll be able to understand how the encoder-decoder network will solve tasks in Text Summarization and Question Answering.
- Build end to end workflow in Google Cloud Platform.
Advanced ML with TensorFlow will take about 2-3 months to complete the course.
Summary
These are the 12 best courses for Google Cloud Certification in 2021. Enroll in any one of the courses and start your learning journey to acquire the certification from Coursera.
As these courses are designed by Google, it would provide more credibility to your certification. If you’ve any questions on any of the courses, feel free to leave a comment. Also, don’t forget to share this with your friends and colleagues.
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