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About the Programme Academic Staff Program Qualifications Lessons Matrix of Course & Program Qualifications Turkish Qualifications Framework (TQF) TQF & Program Qualifications
  1. Vocational School of Information Technologies
  2. Department of Software, Application Development and Analysis
  3. Program in Front-End Software Development
  4. Course Structure Diagram with Credits
  5. Advanced Web Technologies and AI Integration
  6. Description
  • Description
  • Learning Outcomes
  • ECTS Credit Load
  • Course's Contribution to Program
  • Learning Outcomes & Program Qualifications
Last Updated: 25/06/2026

Code - Course Title Course Type Laboratory + Practice ECTS
ÖYG222 - Advanced Web Technologies and AI Integration IV. SEMESTER 2 +2 4.0
Language of Instruction Türkçe
Course Type Area Elective Courses
Course Instructor(s) ÖĞR. GÖR. AHMET AVCIOĞLU
Mode of Delivery Face to face.
Place of Delivery
Used Educational Platforms
Prerequisites None.
Courses Recomended
Recommended Resources Lecture slides and practice notes.
Work Placement
Aims of the Course

Weeks Learning Outcomes Topics Teaching Methods
Week - 1 Course introduction, presentation of course structure and assessment method, an overview of modern browser capabilities, the evolution of the web platform and the new role of web applications in the AI era.
Week - 2 Progressive web applications, the application manifest, installable applications, distribution on mobile and desktop, introduction to offline working strategies.
Week - 3 Service workers, registration and lifecycle, caching strategies, flow control between network and cache, design of the offline experience.
Week - 4 Web sockets for real time communication, event based bidirectional communication, server sent events, basic chat and live notification applications.
Week - 5 Use of large language model providers from frontend applications, API key and environment variable management, request configuration, error handling, safe processing of model responses.
Week - 6 Streaming responses, displaying content received in chunks on the interface, streaming patterns from a user experience perspective, cancellation and timeout management.
Week - 7 Fundamentals of prompt writing, generating dynamic prompts based on user intent for frontend applications, use of structured output, response enforcement with JSON schema.
Week - 8 Midterm examination.
Week - 9 Use of the retrieval augmented generation approach from the frontend side, embedding models, basic search flows, generating context aware responses to user questions.
Week - 10 AI assisted user interface components, smart search box, autocomplete, content summary and recommendation components, model assisted user experience design.
Week - 11 Chat interface design, message history management, multi turn conversation context, user feedback, experience design for error and limitation states.
Week - 12 Cost and performance optimization, monitoring token consumption, caching strategies, query batching approaches, product oriented cost awareness.
Week - 13 Privacy and security issues, limits on transferring user data to model providers, authentication and rate limiting, prompt injection and prevention methods.
Week - 14 AI integrated web application development project, execution of design, coding and evaluation stages, reflection of ethical principles in implementation and general recap.

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Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%)

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