Topicwise MCQs on Data Science

If you are a Computer Science Engineer then this section is for you. This section focus on all topics of the Data Science subject. These questions will help you to prepare for interviews, entrance exams, online tests, and semester exams. This also helps you to understand Data Science deeply. Here, You can practice these MCQs chapter-wise for FREE.

1. Data Science MCQs on Basics and Data Scientist Toolbox

This part contains data science multiple-choice questions and answers on basics on basics of data sciences and toolbox, workflow of CLI and git, big data analysis and experimental design.

  • Basics of Data Science
  • ToolBox Overview
  • CLI and Git Workflow
  • Big Data
  • Analysis and Experimental Design



  • 2. Data Science MCQs on Data Analysis with Python

    This part contains data science multiple-choice questions and answers on pandas, time deltas, python plotting, data structures and computational tools.

  • Time Deltas
  • Plotting in Python
  • Pandas Data Structure
  • Computational Tools
  • Pandas Part-1
  • Pandas Part-2



  • 3. Data Science MCQs on Getting Data

    This part contains data science multiple-choice questions and answers on raw data, processed data, tidy data, web reading, API, data summarization and merging, regular expressions and text variables.

  • Raw and Processed Data
  • Tidy Data
  • Reading from Web and APIs
  • Summarizing and Merging Data
  • Regular Expressions and Text Variables



  • 4. Data Science MCQs on Data Analysis and Research

    This part contains data science multiple-choice questions and answers on graphical devices and plotting systems, basics of reproducible research, clustering, exploratory graphs and basics of literate statistical programming.

  • Graphics Devices
  • Plotting Systems and Clustering
  • Exploratory Graphs
  • Introduction to Reproducible Research
  • Literate Statistical Programming Part-1
  • Literate Statistical Programming Part-2



  • 5. Data Science MCQs on Statistical Inference and Regression Models

    This part contains data science multiple-choice questions and answers on caret, probability and statistics, basics of statistical inference, regression models, distributions, binary and count outcomes and residual variations.

  • Introduction to Statistical Inference
  • Probability and Statistics
  • Common Distributions
  • Statistical Inference Concepts
  • Introduction to Regression Models
  • Residual Variation and Multivariate
  • Binary and Count Outcomes
  • Caret