Subject Overview

A comprehensive study of modern web technologies, covering Internet foundations, front-end and back-end development, data management, APIs, security, cloud deployment, quality engineering, analytics, AI integration, governance and emerging web platforms.

Learning Goal

Students will be able to design, implement, secure, test, deploy and evaluate standards-compliant web applications, including data-driven and AI-enabled systems, while applying accessibility, ethics, governance and industry engineering practices.

Syllabus

1. Internet and Web Foundations

Learning Objective: Explain Internet architecture, the Web’s evolution, client–server computing, URLs, DNS, HTTP/HTTPS, TCP/IP, browsers, web servers, standards and request–response lifecycles.

Category: foundation

2. Web Architecture and Engineering Principles

Learning Objective: Apply layered, three-tier, MVC, component-based, monolithic, microservice, serverless and event-driven architectures; evaluate scalability, maintainability and technology-stack trade-offs.

Category: core

3. Semantic HTML and Web Standards

Learning Objective: Create well-structured pages using semantic HTML, forms, media, metadata, validation, DOM concepts, standards compliance and search-engine fundamentals.

Category: foundation

4. CSS, Responsive Design and User Experience

Learning Objective: Develop responsive interfaces using the cascade, box model, selectors, layouts, Flexbox, Grid, media queries, design systems, usability principles and mobile-first design.

Category: core

5. JavaScript and Browser Programming

Learning Objective: Use JavaScript syntax, functions, objects, modules, events, DOM manipulation, asynchronous programming, promises, Fetch API, browser storage and error handling.

Category: core

6. Front-End Frameworks and State Management

Learning Objective: Build component-based single-page applications using a contemporary framework, routing, reactive rendering, state management, reusable components and appropriate rendering strategies such as CSR, SSR and static generation.

Category: application

7. Server-Side Web Development

Learning Objective: Implement server applications with routing, middleware, templates, sessions, authentication, authorization, validation, logging, dependency management and secure configuration using a modern back-end framework.

Category: core

8. Web Data Management

Learning Objective: Model and manage relational and NoSQL data, write queries, use transactions, indexes and object–relational mapping, and address caching, consistency, migration and data lifecycle requirements.

Category: core

9. Web APIs and Systems Integration

Learning Objective: Design and consume RESTful and GraphQL APIs using JSON, status codes, versioning, pagination, documentation, webhooks and real-time communication; evaluate interoperability and API lifecycle management.

Category: application

10. Web Security, Privacy and Digital Identity

Learning Objective: Mitigate OWASP risks including injection, XSS, CSRF and broken access control; apply TLS, secure cookies, OAuth, OpenID Connect, token security, secrets management, privacy-by-design and regulatory principles.

Category: core

11. Accessibility, Performance and Search Optimization

Learning Objective: Evaluate and improve applications using WCAG, inclusive design, assistive-technology testing, Core Web Vitals, caching, compression, lazy loading, content delivery networks and technical SEO.

Category: application

12. Testing, DevOps and Cloud Deployment

Learning Objective: Apply unit, integration, end-to-end, security and performance testing; use Git, code review, CI/CD, containers, cloud platforms, infrastructure concepts, observability and incident-response practices.

Category: application

13. Web Analytics, Product Management and Governance

Learning Objective: Use metrics, funnels, experimentation and telemetry for evidence-based decisions while managing requirements, cost, risk, content, APIs, third-party dependencies, compliance and ethical data use.

Category: strategic

14. AI-Enabled Web Applications and Emerging Trends

Learning Objective: Integrate machine-learning services and generative AI through APIs, streaming and vector retrieval; address model UX, safety, bias and governance while examining PWAs, WebAssembly, edge computing, WebXR, decentralized technologies and future web standards.

Category: contemporary