Learn Cloud Computing From Scratch in 2026

What Is Cloud Computing?

In simple terms, cloud computing refers to delivering computing services such as storage, processing power, and applications over the Internet. 

I always like to give this example: imagine that instead of having your computer, you rent a powerful one from providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud. They provide you with resources like storage, processing power, and even entire applications online. This way, you don't have to worry about things like setting up servers or keeping your software updated. You just use what you need when you need it, and you only pay for what you use.

Cloud computing offers a suite of services that have revolutionized how businesses operate and innovate. But what features make cloud computing such a transformative technology? Let’s have a look at them:

• On-demand self-service: You can provision computing resources, such as storage and processing power, as needed without requiring someone’s intervention from the provider.
• Broad network access: Cloud services are available over the internet and are accessible from a wide range of devices like laptops, tablets, and smartphones.
• Resource pooling: Cloud providers use multi-tenant models to pool resources and serve multiple customers, optimizing resource utilization.
• Rapid elasticity: The cloud allows you to quickly scale up or scale down resources to meet demand, ensuring high availability and performance.
• Measured service: With cloud computing, you only pay for the resources you use, which offers great cost efficiency.

Cloud computing isn't a one-size-fits-all solution. It comes in various forms depending on your needs and the level of control you require:

• Infrastructure as a Service (IaaS): This is the most basic form of offering virtualized computing resources, such as servers, storage, and networking. Here, we can mention AWS EC2, Google Compute Engine, and Microsoft Azure Virtual Machines.
• Platform as a Service (PaaS): PaaS provides a platform allowing you to develop, run, and manage applications without dealing with the underlying infrastructure. Here, we can find Google App Engine and AWS Elastic Beanstalk.
• Software as a Service (SaaS): SaaS offers you fully functional software applications delivered over the internet, such as Google Workspace, Microsoft 365, and Dropbox.
• Function as a Service (FaaS): Also known as serverless computing, this allows you to run individual functions or pieces of code in response to specific events without worrying about the infrastructure. AWS Lambda is a popular example.

Why Is Learning Cloud Computing Useful?

Cloud computing has a variety of applications 

We’ve already mentioned that cloud computing is very versatile and powers various industries and applications. But let’s look at a few specific examples of where you can use them:

• Data storage and backup: Cloud storage solutions like Google Drive, Dropbox, and iCloud provide easy access to files from anywhere while also ensuring secure backups.
• Big data analytics: Cloud computing makes it easier for businesses to analyze large sets of data, offering tools and resources to process data quickly and efficiently.
• Content delivery: Streaming platforms like Netflix, YouTube, and Spotify rely heavily on the cloud to deliver content to millions of users worldwide.
• Gaming: Cloud gaming platforms like Google Stadia and Microsoft Xbox Cloud Gaming allow players to stream games without the need for high-end hardware.

There is a demand for skills in cloud computing

The adoption of cloud computing has been rising in recent years. As a result, the global demand for cloud professionals has grown exponentially. Companies are constantly seeking individuals skilled in cloud platforms such as AWS, Azure, and Google Cloud, and many positions offer competitive salaries.

According to Glassdoor's 2026 data, the average U.S. cloud engineer earns about $152,000 per year, with total compensation reaching $238,000 for top earners. Built In reports a similar $151,000 average base, plus roughly $27,000 in additional cash compensation.

How to Learn Cloud Computing from Scratch in 2026

Learning a new technology can always be very challenging. However, if you learn cloud computing methodically, you have a higher chance of success. Let’s focus on a few principles you can use in your learning journey.

1. Understand why you’re learning cloud computing

Before you learn technical details, define your motivation for learning Cloud Computing. Ask yourself:

• What are my career goals?
• Is cloud computing a skill you need to advance in your current role or land a dream job?
• Are you aiming for a career transition into cloud architecture, cloud engineering, DevOps, or cloud security?
• Which opportunities do you see opening up by mastering cloud technologies? Think about specific roles like Cloud Architect, DevOps Engineer, Cloud Security Engineer, or Solutions Architect.
• What problems am I trying to solve?
• Are you facing challenges with managing on-premises infrastructure, such as high maintenance costs, limited scalability, and slow deployment times?
• Do you need to improve your organization's agility and efficiency by leveraging cloud services?
• Are you struggling to manage and secure your organization's data and applications in a multi-cloud environment?
• What interests me?
• Does building and managing scalable, reliable, and cost-effective cloud-based solutions excite you?
• Are you interested in exploring the latest cloud technologies, such as serverless computing, containerization, and artificial intelligence?
• Are you interested in the broader impact of cloud computing on businesses and industries?
• Do I have a specific project in mind that requires cloud computing capabilities?
• Are you working on a personal project that involves cloud technologies, such as deploying a web application on AWS or building a serverless API?
• Does your company have an upcoming cloud migration project, or are they looking to adopt new cloud-native technologies?

2. Start with the basics of cloud computing

After you identify your goals, master the basics of cloud computing and understand how it works.

Understanding the cloud deployment models

One of the first things to understand about cloud computing is the concept of cloud deployment models, which define how a cloud infrastructure is set up. The main types of deployment models are public cloud, private cloud, and hybrid cloud.

In a public cloud, resources are owned and operated by a third-party cloud service provider and shared with other customers. On the other hand, a private cloud is a cloud environment where resources are used exclusively by a single organization.

Lastly, a hybrid cloud combines public and private infrastructures, offering a blend of shared and dedicated resources. To learn more about this, check DataCamp’s Understanding Cloud Computing course.

Understanding cloud service providers and their offerings

Among the cloud service providers, Amazon Web Services (AWS) is the most popular, with offerings in compute (EC2), storage (S3), and databases (RDS, DynamoDB).

Microsoft Azure is known for strong integration with Microsoft tools, covering computing, storage, networking, and AI. Google Cloud Platform (GCP) excels in big data (BigQuery), machine learning (TensorFlow), and Kubernetes. IBM Cloud and Oracle Cloud focus on enterprise solutions, AI, and hybrid clouds.

Each platform has its approach to security, scaling, and management, so exploring their documentation helps you understand their strengths and best use cases. DataCamp’s AWS concepts, Understanding Microsoft Azure, and Introduction to GCP courses can help you speed up.

Setting up your first cloud environment

If we really want to understand cloud computing, then we should get hands-on experience. I recommend that you create an account on one of the major cloud platforms, such as AWS, Microsoft Azure, or Google Cloud, as they offer free tiers for beginners to explore basic services like virtual machines, storage, and databases.

Next, you should familiarize yourself with the cloud console and interface, which allows you to manage resources and services. After that, launch your first virtual machine (VM) or instance to get exposure to IaaS and the underlying infrastructure.

Finally, you should explore simple tasks like setting up a database or deploying a website using managed services, such as AWS RDS or Google Cloud SQL, to deepen your understanding of cloud technologies. 

3. Master intermediate cloud computing skills

Once you're comfortable with the basics, it's time to explore specific technologies and tools. Learn about containerization, cloud networking, and how cloud services can integrate with existing IT infrastructure.

Cloud networking

In my experience, a key skill in cloud computing is understanding networking within a cloud environment.

This includes setting up a Virtual Private Cloud (VPC) to create isolated networks within your cloud provider. You'll also need to learn how to configure subnets, route tables, and security groups to control data flow and manage traffic permissions.

Additionally, mastering load balancing and auto-scaling is crucial for distributing traffic across multiple instances, ensuring high availability and fault tolerance for your applications. Check DataCamp’s AWS  security and Understanding Microsoft Azure Architecture courses to know more about this topic. 

Cloud storage solutions

If you are working with data, you must understand how to store it in the cloud. Different cloud providers offer various storage options tailored to your different needs. On one hand, object storage, such as AWS S3 and Azure Blob Storage, is ideal for storing unstructured data like images and backups.

On the other hand, block storage, like AWS EBS and Google Persistent Disk, is used for virtual machines and databases, providing high-performance, persistent storage. File storage options, such as AWS EFS and Azure Files, are designed for shared file systems, allowing multiple instances to access the same files concurrently. Learn more on DataCamp’s AWS services and Microsoft Azure Management courses.

Containerization and Kubernetes

Containers have become a fundamental aspect of cloud computing, enabling efficient application deployment and scaling. To work with containers, you can use Docker for containerization and Kubernetes for orchestrating and managing containerized applications.

Popular tools like Amazon Elastic Kubernetes Service (EKS), Google Kubernetes Engine (GKE), and Azure Kubernetes Service (AKS) provide managed Kubernetes environments, allowing you to easily deploy, scale, and maintain containerized workloads in the cloud. Understand more about their features and differences by taking a look at DataCamp’s blog articles:

• Fundamentals of Container Orchestration With AWS Elastic Kubernetes Service (EKS)
• ECS vs EKS: Which AWS Container Service is Right for You?

Managed databases and serverless

Cloud computing simplifies database management through managed services. For relational databases, you can explore solutions like AWS RDS, Google Cloud SQL, or Azure SQL Database.

For NoSQL databases, services such as DynamoDB, Firestore, and Cosmos DB are ideal for handling unstructured data. Additionally, serverless architectures like AWS Lambda, Azure Functions, and Google Cloud Functions enable event-driven computing without the need to provision or manage servers, making it easier to scale applications efficiently. I recommend starting by learning Redshift.

4. Learn cloud computing by doing

Now that we know the basic and intermediate concepts of cloud computing, it’s time for some practical experience. There are many things you can do to become skilled in cloud computing, but here are some that I suggest:

• Get hands-on experience while training to earn certifications like the AWS Certified Cloud Practitioner, Google Cloud Professional Cloud Architect, or Databricks certification. Check which Cloud certifications are worth taking, by reading this DataCamp article.

• Participate in cloud challenges on platforms like AWS Skill Builder, Google Cloud Skills Boost, and Microsoft Learn. 

• Create a simple web application and deploy it on AWS EC2. Use S3 to store static files like images or documents. 

• Build an event-driven app using AWS Lambda, where actions like file uploads to S3 trigger Lambda functions.

• Use Google Cloud Storage to host a simple static website and connect it to a Cloud Function for serverless backend tasks.

• Import a dataset into Databricks and use Spark to clean and preprocess the data for analysis.

5. Build a portfolio of projects

As you keep moving in your Cloud Computing learning journey, you will complete different projects. To showcase your Cloud Computing skills and experience to potential employers, you should compile them into a portfolio. 

This portfolio should reflect your skills and interests and be tailored to the career or industry you're interested in. For example, if you are looking for a cloud architecture role, showcase a project that focuses on designing, planning, and implementing scalable solutions. For DevOps positions, focus on automation with tools like Terraform, or security projects for cloud security and compliance. For cloud developer positions, I recommend highlighting projects that involve coding, deploying, and testing cloud applications.  

6. Keep challenging yourself

Learning Cloud Computing is a continuous journey. Technology constantly evolves, and new features and applications are being developed regularly. Cloud is not the exception to that.

Once you’ve mastered the fundamentals, you can look for more challenging tasks and projects such as building secure cloud environments, exploring encryption techniques, and mastering compliance standards (HIPAA, GDPR). You can also experiment with machine learning integration using tools like AWS SageMaker or Azure Machine Learning, and dive into serverless computing with AWS Lambda or Google Cloud Functions. Focus on your goals and specialize in areas that are relevant to your career goals and interests.

Keep up to date with the new developments, by following release notes and blogs from AWS, Azure, and Google Cloud, and keep an eye on industry proposals like Kubernetes and edge computing. Build more complex systems and participate in cloud challenges to further hone your skills. Collaborate on open-source projects for practical experience and embrace mistakes as learning opportunities. 

An Example Cloud Computing Learning Plan

Even though each person has their way of learning, it’s always a good idea to have a plan or guide to follow for learning a new tool. We’ve created a potential learning plan outlining where to focus your time and efforts if you’re just starting with Cloud Computing.

Month 1-3 learning plan

• Cloud computing fundamentals. Start by understanding the core concepts of cloud computing, such as the different service models, and cloud deployment models. Complete the Understanding Cloud Computing.
• Creating an account. Pick one cloud provider create a free-tier account and explore which type of services they offer.
• Hands-on experience. Deploy your first virtual machine, store files in cloud storage, and experiment with setting up a basic networking environment.

Month 4-6 learning plan

• Cloud security. Learn about Identity and Access Management (IAM), encryption, security groups, and compliance standards such as GDPR and HIPAA.
• Cloud networking. Understand the principles of VPC (Virtual Private Cloud), subnets, firewalls, and load balancing. Learn how to design a secure and efficient cloud network.
• Virtualization. Dive into virtualization technologies that enable cloud environments, including hypervisors and containerization (Docker, Kubernetes).
• Start building projects. Now that you have a better understanding of cloud services, start building real-world cloud projects to add to your portfolio. Focus on creating projects that demonstrate your ability to integrate cloud services, work with databases, or deploy applications at scale. You can take a Cloud Case Study DataCamp’s Course to understand how to work on a real-world project. You can also learn and apply data streaming in this DataCamp course on Streaming Data with AWS Kinesis and Lambda.

Month 7 onwards

• Azure Fundamentals or  AWS Cloud Practitioner Skill Track. Complete the Azure or AWS skill track on DataCamp, which covers the fundamentals of Azure and the use and secure core AWS compute database and storage services, respectively.
• Get certified. Pick one of the cloud providers and get a certification as a Cloud Expert. This will help you showcase your knowledge to potential employers.
• Develop a more complex project. Pick a specialization and develop a more complex project. There are many examples of projects you can work on, but some of them I can suggest are: 
• A large-scale project, such as designing and deploying systems involving databases, load balancing, auto-scaling, security practices, and disaster recovery. 
• Integrating services from multiple providers or setting up disaster recovery solutions.
• Machine learning projects,  where you can work with tools like AWS SageMaker, Google AI Platform, or Azure ML to deploy models. 

Best Ways to Learn Cloud Computing

Let’s cover a few efficient methods of learning cloud computing.

Take online courses

Online courses offer an excellent way to learn cloud computing at your speed. DataCamp offers cloud computing courses for all levels, as well as skill tracks on different cloud technologies. The courses cover introductory concepts to more advanced topics and are designed with hands-on exercises.

Here are some of the cloud computing-related courses and skill tracks on DataCamp:

• Understanding Cloud Computing
• Introduction to Azure
• Introduction to GCP
• AWS Cloud Technology and Services Concepts
• Microsoft Azure Fundamentals Skill Track
• AWS Cloud Practitioner Skill Track

Follow online tutorials

Tutorials are another great way to learn cloud computing, especially if you are new to the technology. They contain step-by-step instructions on how to perform specific tasks or understand certain concepts. For a start, consider these tutorials:

• Azure Data Factory
• Google Cloud for Data Science
• Snowflake vs AWS
• Setting Up vLLM on Google Cloud
• AWS Lake Formation

Check out cloud cheat sheets

Cheat sheets are helpful for quickly referencing key commands, configurations, and tools. DataCamp offers cheat sheets for AWS and Google Cloud that can help you as you get started:

• AWS, Azure and GCP Service Comparison
• Azure CLI Cheat Sheet

Complete projects on the cloud

Working on cloud computing projects will give you hands-on experience and can be a great way to build a portfolio. Try deploying applications on different cloud platforms and experimenting with cloud-based storage or computing. 

Check for cloud computing projects or code-along to work on at DataCamp. These allow you to apply your cloud skills leveraging Snowflake, Amazon Redshift, Google BigQuery, or Databricks:

• Exploring London's Travel Network
• Analyzing Ticket Sales Data with Amazon Redshift
• Analyzing Olympics Data in SQL & Databricks

Read blogs

To have a deeper knowledge of the advantages of Cloud Computing, you should also understand what are the key similarities and differences among the different providers. You can read articles on what different providers offer such as the following:

• Edge vs Cloud Computing
• AWS vs Azure
• Azure Data Factory vs Databricks
• Databricks vs Snowflake
• AWS CloudTrail vs AWS CloudWatch

Discover cloud computing through books

Books are an excellent resource for learning Cloud Computing. They offer in-depth knowledge and insights from experts alongside code snippets and explanations. Here are some of the most popular books on Cloud Computing:

• Cloud Computing: Concepts, Technology & Architecture
• Cloud Native Infrastructure
• AWS Fundamentals

The Different Careers in Cloud Computing Today

Because the adoption of cloud computing continues to grow, so do the career opportunities for professionals with cloud skills, such as Cloud Architects, Engineers, and Consultants. If you are evaluating the fit of your Cloud skills, consider these roles:

Cloud architect

As a cloud architect, you are responsible for designing, building, and maintaining designing, building, and maintaining cloud infrastructures that are scalable, reliable, and cost-efficient.

Your role involves selecting the right cloud services and solutions from providers like AWS, Azure, and Google Cloud to meet the specific needs of the organization. You’ll need to ensure high availability and fault tolerance across cloud systems, as well as design solutions that scale dynamically to accommodate changing traffic loads. 

• Key skills: 
• Strong understanding of cloud architecture and cloud components
• Proficiency in cloud service providers like AWS, Azure, and Google Cloud.
• Experience with cloud automation tools.
• Expertise in designing scalable, fault-tolerant systems using cloud-native technologies like containers and Kubernetes.
• In-depth understanding of serverless architecture.
• Key tools used: 
• AWS, Azure, Google Cloud Platform
• Terraform, CloudFormation
• Kubernetes, Docker
• AWS Lambda, Azure Functions, Google Cloud Functions
• CloudWatch, Azure Monitor, Google Stackdriver

Cloud developer

As a cloud developer, your role focuses on building, deploying, and maintaining cloud applications that are scalable, efficient, and secure. You are responsible for writing code that leverages cloud services and tools to create dynamic applications that can automatically scale and respond to user demands. You will also collaborate with other teams to integrate CI/CD pipelines and ensure smooth application delivery.

• Key skills: 
• Strong understanding of cloud service providers like AWS, Azure, and Google Cloud.
• Proficiency in cloud-native application development.
• Familiarity with cloud storage solutions.
• Knowledge of cloud databases.
• Proficiency in automating deployments using CI/CD pipelines and DevOps tools.
• Key tools used: 
• AWS, Azure, Google Cloud Platform
• Terraform, CloudFormation
• Kubernetes, Docker
• AWS Lambda, Azure Functions, Google Cloud Functions
• Jenkins, GitLab CI, Azure DevOps

Cloud security engineer

As a cloud security engineer, your primary responsibility is to protect cloud environments by implementing and maintaining security measures to safeguard data, applications, and systems.

You will design and enforce security policies, monitor cloud resources, and manage security tools to prevent unauthorized access, data breaches, and other security threats. Your role also involves ensuring compliance with regulatory standards, securing cloud-native applications, and collaborating with other teams to build secure, scalable, and resilient cloud architectures.

• Key skills: 
• Proficiency in cloud service providers like AWS, Azure, and Google Cloud.
• Strong understanding of cloud security principles and practices.
• Experience in securing cloud infrastructures.
• Knowledge of security monitoring and incident response tools.
• In-depth understanding of compliance frameworks and regulations.
• Experience with vulnerability scanning, penetration testing, and cloud-native security practices.
• Key tools used: 
• AWS, Azure, Google Cloud Platform
• AWS IAM, Azure Active Directory, Google Cloud IAM
• AWS CloudTrail, Azure Security Center, Google Cloud Security Command Center
• CloudWatch, Azure Sentinel, and Google Chronicle
• Qualys, Tenable, and Rapid7
• Kali Linux and Burp Suite

Cloud consultant

As a cloud security engineer, you are responsible for advising organizations on how to effectively leverage cloud technologies to achieve their business goals. You will assess clients’ current infrastructure, identify opportunities for cloud adoption, and recommend the best cloud solutions based on their needs and requirements. You will collaborate closely with stakeholders, develop cloud roadmaps, and guide the implementation of cloud technologies.

• Key skills: 
• Strong understanding of cloud platforms services and capabilities.
• Experience in cloud strategy development and the ability to assess client needs.
• Knowledge of cloud migration processes for moving on-premises applications and infrastructure to the cloud.
• Expertise in cloud security and compliance, regulatory requirements, and best practices for data protection.
• Familiarity with cloud automation tools.
• Ability to communicate technical concepts to non-technical stakeholders
• Key tools used: 
• AWS, Azure, Google Cloud Platform.
• AWS Well-Architected Framework, Azure Cloud Adoption Framework, Google Cloud Architecture Framework.
• AWS Cost Explorer, Azure Cost Management, and Google Cloud Pricing Calculator.
• AWS Shield, Azure Security Center, Google Cloud Security Command Center.
• CloudWatch, Azure Monitor, and Google Stackdriver.

How to Find a Job That Uses Cloud Computing or in Cloud Computing

While having a degree can be very valuable when pursuing a career in a data-related role that uses Cloud Computing, it's not the only path to success. More and more people from diverse backgrounds and with different experiences are starting to work in data-related roles. With dedication, consistent learning, and a proactive approach, you can land your dream job that uses Cloud Computing.

Keep learning about cloud computing

Stay updated with the latest trends and advancements in cloud computing. Follow influential professionals in the cloud computing space on social media, read blogs focused on cloud technologies, and listen to podcasts that cover everything from infrastructure to cloud-native applications.

Engage with thought leaders like Werner Vogels, CTO of Amazon, and Urs Hölzle, SVP of Technical Infrastructure at Google, who play a key role in shaping the cloud landscape. By following them, you'll gain insights into emerging cloud trends, new services, and the future of the cloud ecosystem. You can also explore blogs such as the AWS Architecture Blog and Google Cloud Blog, which provide in-depth articles, case studies, and tutorials on various cloud topics, from deployment strategies to security best practices.

Additionally, keep an eye on industry events like KubeCon, DataCamp cloud webinars, and podcasts to stay ahead of the curve and network with industry experts.

Develop a portfolio

You need to stand out from other candidates. One good way to do it is to build a strong portfolio that showcases your skills and completed projects. 

You can host your profile website on a cloud platform to demonstrate your basic skills in the cloud, analyze data using cloud tools, and take advantage of machine learning tools. Check which cloud computing projects you can showcase in this DataCamp article. 

Develop an effective resume

Hiring managers have to review hundreds of resumes and distinguish great candidates. Also, many times, your resume is passed through Applicant Tracking Systems (ATS), automated software systems used by many companies to review resumes and discard those that don't meet specific criteria. So, you should build a great resume and craft an impressive cover letter to impress both ATS and your recruiters. 

Get noticed by a hiring manager

If you get noticed by the hiring manager or your effective resume goes through the selection process, you should next prepare for a technical interview. To be ready, you can check this article on Top 30 Cloud Computing Interview Questions and Answers. 

Final Thoughts

Learning cloud computing can open doors for better opportunities and career outcomes. It is rewarding but requires consistency and hands-on practice. Experimenting and solving challenges can accelerate your learning process and provide real-world examples to showcase your practical skills when looking for jobs.