Dive into a practical real-world project by building an inventory management system using Python. From database design to frontend development and reporting, this comprehensive guide covers all aspects of creating a dynamic, feature-rich application.
deployment
9 Articles
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Explore the step-by-step guide to creating a real-world project using Node.js. From planning and selecting the right stack to development, testing, optimization, deployment, and maintenance, this article covers all aspects of building a feature-rich application.
Apply your Laravel knowledge to a practical project, demonstrating your ability to create dynamic and feature-rich web applications. From planning to deployment, this guide offers a comprehensive walkthrough of a real-world Laravel project.
Discover the process of building a real-world web application, from planning and design to development, testing, and deployment. This article guides you through the stages of creating a project showcase that reflects your skills and creativity in web development.
Explore how to create a custom event display in Drupal. This guide covers everything from choosing the right modules to theming and testing, ensuring you can create a visually appealing layout for events on your site.
Explore the integration of cloud platforms and DevOps in deploying and managing applications. This guide covers popular cloud platforms like AWS, Azure, GCP, and essential DevOps tools and practices, highlighting strategies for scalability, collaboration, security, and more.
Understand how to approach and solve real-world data science problems presented in interviews with this comprehensive guide. Learn strategies for data exploration, preprocessing, modeling, evaluation, and more.
Explore the principles of database replication and high availability, critical for ensuring uninterrupted access to data. This guide covers synchronization, redundancy, load balancing, failover strategies, and disaster recovery planning, providing valuable insights for robust database management.
Unravel the steps to craft cohesive machine learning pipelines. Transition seamlessly from data collection to deployment in real-world scenarios.