Kubernetes for AI Workloads provides a comprehensive exploration of deploying, managing, and scaling AI applications using Kubernetes. Participants will engage in hands-on projects that emphasize real-world applications, ensuring they gain practical experience in orchestrating containerized AI workloads. The course is structured to facilitate interactive learning, culminating in a final project that allows participants to showcase their skills and publish their findings in Cademix Magazine.
Throughout the program, learners will delve into the intricacies of Kubernetes architecture, focusing on how to optimize it for AI-driven tasks. Topics will cover everything from setting up Kubernetes clusters to advanced deployment strategies tailored for machine learning models. By the end of the course, participants will be equipped to handle the complexities of AI workloads in a Kubernetes environment, making them valuable assets in the ever-evolving tech landscape.
Introduction to Kubernetes and its role in AI
Setting up a Kubernetes cluster for AI applications
Containerizing AI models with Docker
Managing dependencies and configurations in Kubernetes
Scaling AI workloads using Kubernetes features
Implementing CI/CD pipelines for AI model deployment
Monitoring and logging for AI applications in Kubernetes
Best practices for resource management in Kubernetes
Security considerations for AI workloads in Kubernetes
Final project: Deploying an AI application on Kubernetes and publishing results

Docker for Web Developers provides an in-depth exploration of containerization technologies tailored specifically for web development. Participants will engage in hands-on projects that emphasize real-world applications of Docker, enabling them to streamline development workflows and enhance deployment processes. This course is structured to facilitate interactive learning, where attendees will collaborate on projects that culminate in publishable results in Cademix Magazine, fostering a culture of knowledge sharing and innovation.
The curriculum is designed to equip participants with essential skills for leveraging Docker in modern web development environments. By the end of the program, learners will have a comprehensive understanding of container orchestration, microservices architecture, and best practices for deploying scalable web applications. The final project will challenge participants to create a fully functional web application using Docker, reinforcing the concepts learned throughout the course.
Introduction to Docker and its Ecosystem
Setting Up Docker on Local Development Environments
Understanding Docker Images and Containers
Creating and Managing Dockerfiles
Networking in Docker: Bridging Containers
Data Management and Volumes in Docker
Docker Compose for Multi-Container Applications
Introduction to Container Orchestration with Kubernetes
Best Practices for Docker Security
Final Project: Develop and Deploy a Web Application Using Docker

Orchestration with Kubernetes provides a comprehensive exploration of container management and orchestration, equipping participants with the skills necessary to deploy, manage, and scale applications in cloud environments. This program emphasizes hands-on experience through project-based learning, enabling participants to engage directly with real-world scenarios that reflect current industry practices. By the end of the course, learners will gain a robust understanding of Kubernetes architecture, deployment strategies, and best practices for maintaining containerized applications.
Participants will delve into various aspects of Kubernetes, including its core components, networking, and storage solutions. The course is structured to encourage collaboration and innovation, culminating in a final project that challenges learners to design and implement a scalable application using Kubernetes. Publishing results in Cademix Magazine offers an opportunity for participants to showcase their work and insights, fostering a community of knowledge sharing and professional growth.
Introduction to Containerization and Kubernetes
Understanding Kubernetes Architecture
Setting Up a Kubernetes Cluster
Deploying Applications on Kubernetes
Managing Pods and ReplicaSets
Configuring Networking in Kubernetes
Persistent Storage Solutions in Kubernetes
Implementing Helm Charts for Application Management
Monitoring and Logging in Kubernetes Environments
Final Project: Designing a Scalable Application with Kubernetes