Docker Fundamentals for Beginners

Containers are not an abstract topic for Dr. Alfred Ang; they are how the production systems under Dr. Ang's care are built, shipped and kept running. A full-stack AI developer, Agentic AI solution architect and corporate trainer, Dr. Ang is CTO of Tertiary Infotech Academy Pte Ltd in Singapore, the training organisation behind Tertiary Courses, and builds intelligent agents and business platforms end-to-end across front end, back end, databases, cloud deployment and native mobile apps. More than 300 public repositories on GitHub document that work. The course-registration platform that runs the Tertiary Courses sites in Singapore, Malaysia and Ghana is packaged with Docker and deployed through Coolify, with one codebase serving every partner site and each one redeploying automatically when new code lands on the main branch. Another project, a training environment management platform, launches Docker-based WordPress, Ubuntu and Kali Linux labs inside the browser, with role-based access, on-demand container start and stop, and idle auto-shutdown to keep running costs in check. Dr. Ang has also written reusable Claude Code skills, including one that pushes images to Docker Hub, and set up pipelines that build, sign and submit mobile apps on every commit. A video-production pipeline triggered by webhooks, which researches, scripts, renders and publishes without manual steps, shows the same automation mindset. Much of this was developed alongside AI coding assistants, which is why the course pairs Docker with Cursor, GitHub Copilot and Claude rather than treating them as separate subjects.

The course follows the path a real deployment takes. Learners set up Docker alongside an AI coding assistant, run a first container, and get comfortable with images and the Docker CLI before asking AI to draft Dockerfiles, then building and tagging images, managing volumes and data, and wiring containers together over networks. Docker Compose comes next: defining multi-container stacks with AI help, handling environment configuration and secrets properly, and using AI to explain and debug Compose files that refuse to start. The final topic covers building a CI/CD pipeline, deploying containers to the cloud, monitoring, logging and security, and optimising and scaling once real traffic arrives. Throughout, Dr. Ang draws on the realities of running containerised sites in production: keeping build contexts lean, keeping secrets out of images, and making sure database changes succeed before a new container is allowed to serve users. Those lessons make the case for reading AI-generated configuration carefully rather than pasting it in blindly, and for asking the assistant to explain every line it proposes. Sessions are hands-on, with short explanations followed by guided labs, and learners are encouraged to bring a small application of their own to containerise. By the end, participants can take a project from a laptop to a running, monitored deployment and know which questions to put to an AI assistant at each step of the journey. Explore the Docker-based projects behind this course in Dr. Ang's portfolio at https://github.com/alfredang