Data Visualization and Interpretation
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Follow on Instagram for UpdatesData Visualization and Interpretation Syllabus — Unit-wise Content
The official GTU curriculum for Data Visualization and Interpretation (subject code 1719507) as prescribed for AIAD · Semester 1 divides the course into 8 units, covering 34 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (1719507)Unit 1 Introduction
- How visualization affects data interpretation
- Role of visualization in data science
- Two flavors of data visualization: exploratory and communicative
- Course projects overview
Unit 2 Visualization Design Principles I
- Data and task abstraction
- Best practices for encoding
- Marks and channels
- Tableau assignment e
- Course project details
Unit 3 Visualization Design Principles II
- Effectiveness and expressiveness
- How to critique visualizations
- Design problems and consequences
- How not to cause misinterpretation
Unit 4 Exploratory Visualization Techniques
- Handling high-dimensional data
- Comparison techniques
- Small multiples
- Handling uncertainty
- Depicting time
Unit 5 Interactive Visualization
- Why interactivity is needed
- Handling multiple views
- Brushing and Linking
- D3 instructions and assignments
Unit 6 Data Interpretability
- Causes of misinterpretation
- Role of communicative visualization in sciences
- Graphical interpretability: metrics and approaches
Unit 7 Visualization in Data Science
- Methods and Examples Explaining machine learning models
- Interpretability challenges and solutions
- Transparency and human-machine trust
- Impactful case studies: biology
- cyber security
- climate science
- social science
Unit 8 Recent Trends in the Domain of Data Visualization 02 05
- Visualization Analysis and Design by Tamara Munzner AK Peters Visualization Series
- BRANCH: COMPUTER ENGINEERING (ARTIFICIAL INTELLIGECNE AND DATA SCIENCE) Page 3
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