Docker Course: The Docker software container cloud platform is increasingly being used in the fields of Data Engineering, Machine Learning, and software development in general. Discover why and how to take a Docker course.
In the past, to transport goods from one end of the planet to the other, transport companies had no choice but to load them individually onto ships. Loading and unloading were therefore very difficult and tedious.
To save time, maritime carriers came up with the idea of creating containers of different sizes that could be easily loaded and unloaded using cranes. This invention greatly simplified the transportation of goods, and it is now used systematically.
The open-source Docker platform adopts the same concept for software development. It allows for the creation of containers to transport not goods, but different elements of software. A container is a standardized unit of software, enabling the developer to isolate an application from its environment.
The container is a form of virtual machine that bundles the code of an application and all its dependencies, making it possible to quickly run the application from one computing environment to another. Containerized software will run the same way, regardless of the infrastructure: Linux, Windows, the Cloud, a Data Center…
This simplifies and speeds up the workflow, addressing the increasing complexity of application development due to the multitude of languages, frameworks, architectures, and interfaces at each stage. Furthermore, software containers offer developers the opportunity to innovate by choosing their tools, application stacks, and deployment environments for each project.
Why should I attend a Docker Course?
Since its launch in 2013, Docker has established itself as a new standard for creating and sharing containerized applications. This solution is commonly used by Web developers, Java developers, and DevOps professionals. It is also at the heart of Data Engineering and Machine Learning.
As a result, mastering Docker is highly sought after in the business world. It is also a valuable asset for independent developers and engineers, simplifying the development, deployment, and distribution of applications.
In the field of Data Science, Docker allows for the automation, sharing, and reproduction of experiments. It is also used to package and deploy Data Science applications or create easy-to-use “sandboxes.” Lastly, this tool enables large-scale data analysis and Machine Learning in Cloud environments.
A team of Data Scientists and Data Engineers can use Docker to collaborate more efficiently, without worrying about differences between various environments. Even for a Data Scientist, a Machine Learning Engineer, or a solo Data Engineer, Docker streamlines the development and deployment of models.
How to take a Docker course
To learn how to use Docker and its ecosystem (Docker Engine, Swarm, Hub, etc.), you can turn to DataScientest’s Data Engineer training. This program will teach you to master all the tools and techniques of Data Engineering, including Docker, within the module on automation and deployment.
Likewise, if you’re already a Data Scientist and wish to learn how to put Machine Learning models into production, you can opt for our Machine Learning Engineer training. This program will help you gain skills. One of the modules, focused on collaboration, offers you the opportunity to learn how to work with Docker, Flask, and Kubernetes.
You know all about Docker training. Discover other data engineering tools such as Apache Airflow and Snowflake’s Data Warehouse Cloud.
