Data Analysis and Visualization
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Data Analysis and Visualization Syllabus — Unit-wise Content
The official GTU curriculum for Data Analysis and Visualization (subject code 3161613) as prescribed for CSE · Semester 6 divides the course into 5 units, covering 23 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 (3161613)Unit 1 Math, probability and statistical modeling
- Exploring probability and inferential statistics
- quantifying correlation
- Reducing Data Dimensionality with linear algebra
- Modeling Decisions with Multi Criteria Decision making
- Regression Methods
- Detecting outliers
- Time-series analysis
Unit 2 Using Clustering to subdivide data
- Introducing clustering basics
- identifying clusters
- Categorizing data with Random forest algorithm
Unit 3 Modeling instances
- Recognizing the Difference between Clustering and Classification
- Making sense of data with nearest neighbor analysis
- classifying data with average nearest neighbor algorithms
- classifying data with K- nearest neighbor algorithms
- Solving Real-world problems
Unit 4 Principles of Data Visualization Design
- Data visualization: The big three
- Designing to meet the needs
- Picking the most appropriate Design style
- Choosing how to add context
- Selecting the appropriate Data Graphic Type
- Choosing a Data Graphic
- Using D3.js for Data Visualization
Unit 5 Web based applications for visualization design, Exploring best practices in Dashboard
- Making maps from spatial data Subject Code: 3161613 w.e.f
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