Tutorials: Data Science Workflows using Docker Containers | Future of Data and AI | Conference

Want to eliminate the hassle of inconsistent programming environments and achieve reproducible data science workflows? Watch this session to learn how Docker can help you achieve that and more! Learn the basics of Docker, including creating and running containers, working with images, automating image building using Dockerfile, and managing containers on your local machine and in production. Create data science workflows using docker. You will also see real-world examples of how other data scientists use Docker to streamline their workflow and address common challenges like reproducibility and dependency management. This session is interactive and hands-on so that you can learn and apply the techniques yourself! About the Speaker: Sanjay Pant – Senior Data Engineer at Data Science Dojo Sanjay is a data engineer at Data Science Dojo with experience in cloud infrastructure engineering. He contributes to the design and implementation of scalable cloud solutions for enterprise customers across industries, including proof-of-concept and production-level projects. Table of Contents: 00:00 – Introduction 02:30 – Evolution of app deployment 05:42 – Why use Docker? 06:55 – Docker Architecture 12:35 – Key concepts 12:55 – Working with Docker images 15:29 – Build images using Dockerfile 18:56 – Manage containers. 21:31 – Data persistence with volumes 23:18 – Manage networks in Docker 26:12 – Manage image storage with Docker registry 28:00 – Multi-container deployment with Docker compose 30:51 – Install Docker Desktop on Mac 31:12 – Install Docker Desktop on Windows 32:05 – Demo Hello everyone, you can find all the remaining panel discussions here: https://www.youtube.com/playlist?list=PL8eNk_zTBST_7pzerMktrBIg2hWxnqzzW -- At Data Science Dojo, we believe data science is for everyone. Our data science trainings have been attended by more than 10,000 employees from over 2,500 companies globally, including many leaders in tech like Microsoft, Google, and Facebook. Fo