Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
4VTK 206Web Analitiği ve Zekası1+2+02330.07.2026
Course Details
Language of Instruction Turkish
Level of Course Unit Associate Degree
Department / Program Web Design and Development
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course The aim of this course is to equip students with the knowledge and skills to analyze data obtained from websites and digital platforms, interpret user behavior, evaluate performance indicators, develop strategies to improve conversion rates, and make data-driven decisions using web analytics tools.
Course Content Fundamental concepts of web analytics, performance metrics, user behavior analysis, key performance indicators (KPIs), Google Analytics 4, traffic sources, user acquisition channels, conversion funnel, event tracking, A/B testing, SEO analytics, data visualization, dashboard design, data analysis using Excel and basic Python applications, reporting, and data-driven optimization strategies are covered in this course.
Course Methods and Techniques Lecture, hands-on practice, case study analysis, data analysis applications, project-based learning, laboratory practices, and presentations.
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Instructor Afife ÇİFTCİ OLGUN afife.ciftci@ankarabilim.edu.tr
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Lean Analytics – Alistair Croll and Benjamin Yoskovitz
Web Analytics 2.0 – Avinash Kaushik
Google Analytics Help Center
Google Skillshop – Google Analytics 4
Google Search Central Documentation
Microsoft Excel Official Support Documentation
Python Official Documentation
Course Notes Course materials consist of lecture presentations, practical application documents, sample datasets, and up-to-date web analytics resources prepared by the instructor.Lean Analytics – Alistair Croll & Benjamin Yoskovitz
Web Analytics 2.0 – Avinash Kaushik
Google Analytics Help Center
Google Skillshop – Google Analytics 4
Google Search Central Documentation
Documents https://support.google.com/analytics https://developers.google.com/analytics
Assignments 1 Ödev 1 Proje
Exams 1 Ara Sınav 1 Final Sınavı

Course Category
Engineering %20
Engineering Design %10
Field %70

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 1 % 30
Assignment 2 % 10
Project 1 % 20
Final examination 1 % 40
Total
5
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 1 14
Hours for off-the-c.r.stud 14 1 14
Assignments 2 4 8
Mid-terms 1 7 7
Practice 14 2 28
Project 1 10 10
Final examination 1 9 9
Total Work Load   Number of ECTS Credits 3 90

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
3 Collects, reports, and interprets data using Google Analytics 4 (GA4) and similar web analytics tools.
Bilgi 
1 Explains the fundamental concepts of web analytics, performance metrics, and basic measurement methods.
Beceri 
2 Evaluates website performance by analyzing user behavior, traffic sources, and conversion data.
Yetkinlik 
4 Makes data-driven decisions and develops optimization recommendations to improve user experience using web analytics data.

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction to Web Analytics, Digital Data Concept, Importance of Measurement and Data-Driven Decision Making Research the concepts of web analytics and digital data. Lecture slides, Google Analytics introduction document.
2 Fundamental Concepts and Metrics in Web Analytics: Users, Sessions, Page Views, Engagement Rate and Conversion Rate Review web analytics metrics. Lecture slides, Google Analytics 4 documentation.
3 Key Performance Indicators (KPIs), Goal Setting and Creating Measurement Plans for Different Types of Websites Research KPIs and goal-setting concepts. Lecture slides, KPI examples.
4 Google Analytics 4 Interface, Account Structure, Data Streams and Basic Reports Review the Google Analytics 4 interface. Google Analytics 4 user guide.
5 Traffic Sources, User Acquisition Channels and User Behavior Analysis Research traffic sources. Lecture slides.
6 Customer Journey, Conversion Funnel and Evaluation of Page Transitions Review the conversion funnel concept. Conversion funnel examples.
7 E-Commerce Analytics, Product Performance, Cart Abandonment Rate, Revenue, Purchasing and Conversion Analysis Research e-commerce analytics. GA4 E-Commerce documentation.
8 Midterm Examination Review the topics covered in the first seven weeks. Course notes.
9 Event Tracking, Conversion Events, Goal Definition and Measurement Applications Review GA4 event structures. Event tracking examples.
10 A/B Testing, User Experience Measurement and Basic Conversion Optimization Techniques Research A/B testing methods. A/B testing examples.
11 SEO Analytics, Organic Traffic, Search Queries and Search Performance Evaluation Research SEO analytics. Google Search Console documentation.
12 Data Visualization, Dashboard Design, Reporting Principles and Data Interpretation Review data visualization examples. Dashboard examples.
13 Organizing, Analyzing and Visualizing Web Analytics Data Using Excel and Basic Python Applications Review Excel and Python data analysis examples. Excel worksheets.
14 Performance Analysis of a Real Website, Identifying Problems and Developing Improvement Recommendations Analyze a real website. Case study documents.
15 Project Presentations, Evaluation of Data-Driven Optimization Recommendations and General Review Prepare project presentations. Project evaluation form.
16 Final Examination Review all course topics. Course notes.
17 Final Examination Review all course topics. Course notes.

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12 P13 P14 P15 P16
C3 5 5 4 4 4 4 2 2 2
In1 4 3 2 2 2 2 2
Sk2 4 4 5 4 3 2 3
Co4 5 4 5 3 3 3 2 3 2

  Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant