AL-603 (B) RGPV B.Tech
Data and Visual Analytics (DVA)
Previous year papers and the official syllabus are free to read, no account needed.
Previous Year Papers
3 papers, latest Jun 2026
Syllabus, notes and important questions for AL-603 (B)
Syllabus units
Topics as the official RGPV syllabus lists them.
Unit 1 Data Definitions and Analysis Techniques 12 topics
- Elements
- Variables
- Data categorization
- Levels of measurement
- Data management and indexing
- Introduction to statistical concepts
- Sampling distributions
- Resampling
- Statistical inference
- Descriptive statistics
- Measures of central tendency
- Measures of location of dispersions
Unit 2 Advanced Data Analysis Techniques 11 topics
- Statistical hypothesis generation and testing
- Chi‑Square test
- t‑Test
- Analysis of variance (ANOVA)
- Correlation analysis
- Maximum likelihood test
- Regression modelling
- Multivariate analysis
- Bayesian modelling
- Inference and Bayesian network
- Regression analysis
Unit 3 Data Wrangling 9 topics
- Introduction to data wrangling
- Gathering data
- Assessing data
- Cleaning data
- Design of visualizations
- Univariate exploration of data
- Bivariate exploration of data
- Multivariate exploration of data
- Explanatory visualizations
Unit 4 Data Ecosystem 11 topics
- Overview of the data analyst ecosystem
- Types of data
- Understanding different file formats
- Sources of data
- Overview of data repositories
- NoSQL databases
- Data marts
- Data lakes
- ETL processes and data pipelines
- Foundations of big data
- Big data processing tools (Hadoop, HDFS, Hive, Spark)
Unit 5 Data Visualization Tools 3 topics
- Python visualization libraries (matplotlib, pandas, seaborn, ggplot, plotly)
- Introduction to PowerBI tools
- Industry project examples – creating visualizations of complex datasets
Exam insights
Counted from 3 past AL-603 (B) papers.
Marks asked per paper, by unit
-
Unit 1 Data Definitions and Analysis Techniques 26 marks
-
Unit 2 Advance Data analysis techniques 28 marks
-
Unit 3 Data Wrangling 21 marks
-
Unit 4 Data Ecosystem 19 marks
-
Unit 5 Data Visualization tools 14 marks
Average marks of the questions from each unit in one paper. You answer only some of them, so the total is more than the paper’s maximum.
Asked again and again
-
Explain the concept of Data Wrangling, its process and its importance in Data Analytics.
Asked 3 times: 2026, 2024, 2023
-
Explain and compare common file formats such as CSV, JSON, XML and Parquet with suitable examples.
Asked 3 times: 2026, 2024, 2023
-
Define variables and explain different methods of data categorization
Asked 2 times: 2026, 2023