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GATE Data Science & AI Mock Test

Master Machine Learning, AI, Statistics, and Database Management. Prepare for the most in-demand GATE paper with our pattern-perfect tests.

65 Questions
Full GATE DA Pattern
180 Minutes
Official Exam Duration
Virtual Calc
Interface Practice
New Paper
2024+ Pattern

About Inkstall

Inkstall is a private tuition and exam preparation platform designed exclusively for students preparing for GATE, IIT JAM, CSIR NET, and other competitive examinations. Our mission is to provide exam-accurate practice tests and guided learning that closely simulate real exam conditions, helping students build confidence and significantly improve their scores.

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About This GATE Data Science & AI (DA) Mock Test

Our GATE Data Science & AI Mock Test series is designed to help you master the interdisciplinary concepts of data science, machine learning, and artificial intelligence for the GATE DA exam. The 180-minute test duration challenges your problem-solving speed and analytical abilities.

The mock test covers General Aptitude, Mathematics, and core Data Science subjects, following the latest GATE DA syllabus and exam pattern.

With a real-exam-like interface and detailed performance analysis, you can assess your preparation level and identify key areas for improvement to excel in the GATE Data Science & AI examination.

Exam Pattern & Details

Time Limit
180 Mins
Total Questions
65
Maximum Marks
100
Penalty
MCQ Only

GATE Data Science (DA) Paper Structure

SectionMarks WeightageNo. of QuestionsTopics Included
General Aptitude15 Marks10 QuestionsVerbal, Quant, Logic
Math/Analytics CoreApprox 25 MarksMixedLin Algebra, Stats, Calc
DA Technical CoreApprox 60 MarksMixedML, AI, DBMS, DS & Algo
Total100 Marks65 QuestionsPattern-Perfect Paper

New Paper Highlights (DA):

  • High ratio of MSQs specifically designed to test conceptual ML depth.
  • No negative marking for Numerical Answer Type (NAT) and Multiple Select Questions (MSQs).
  • Strong emphasis on Vector Calculus and Linear Algebra for Gradient Descent concepts.
  • Virtual Calculator is crucial for Statistical distributions and Hypothesis testing.

What This Mock Test Includes

Machine Learning & AI

Supervised & Unsupervised Learning, Linear & Logistic Regression, Neutral Networks, and Search Strategies.

Probability & Statistics

Random Variables, Distributions (Binomial, Poisson, Normal), Central Limit Theorem, and Hypothesis Testing.

Programming & Data Structures

Python Programming fundamentals, Arrays, Stacks, Queues, Linked Lists, and Tree Data Structures.

DBMS & Warehousing

Relational Algebra, SQL, Normalization, and Data Warehousing concepts for AI.

Linear Algebra & Calculus

Matrices, Eigenvalues, Vector Spaces, Optimization, and Partial Derivatives.

Latest Pattern MSQ

Master the Multiple Select Questions that are core to the new Data Science paper.

Who Should Attempt This Test?

CS & Allied Students

Computer Science, Math, or Stats students looking to transition into modern AI/ML roles.

Future Data Scientists

Aspirants aiming for specialized M.Tech programs in AI and Data Science at IITs.

Research Scholars

Candidates targeting research-oriented programs (MS/PhD) in Artificial Intelligence.

Why Choose Inkstall for GATE DA?

Data-Driven Content

Questions modeled exactly on the newest GATE DA syllabus introduced in 2024.

ML Focus

Specialized focus on high-weightage topics like Machine Learning and Statistics.

Topper Verified

Content reviewed by data scientists and top rankers from the inaugural DA exam.

Predictive Analytics

Get predictive insights into your likely GATE rank based on mock performance.

Learning Outcomes

  • Master the mathematical foundations of ML and AI
  • Improve Python-based algorithmic thinking
  • Expert handling of MSQs and NATs in the new DA paper
  • Efficient usage of on-screen tools mimicking the actual GATE interface
  • Better conceptual clarity on Statistical Inference and Linear Algebra

Frequently Asked Questions

Future-Proof Your Career in AI

Start your preparation for the GATE Data Science & AI paper today with the most comprehensive mock series.