GATE DA 2026 Exam Analysis: Paper Review, Difficulty Level & Expert Insights

GATE DA 2026 : Quick Overview

Exam Name: GATE 2026 Data Science & Artificial Intelligence (DA)

Conducting Body: Indian Institute of Technology (IIT) Guwahati

Exam Date: February 15, 2026 (Saturday)

Shift: Shift 2 (Afternoon Session)

Exam Timing: 2:30 PM to 5:30 PM

Exam Duration: 3 Hours (180 Minutes)

Total Questions: 65 Questions

Total Marks: 100 Marks

Exam Mode: Computer‑Based Test (CBT)

Overall Difficulty Level

Based on extensive student feedback and expert analysis, the GATE DA 2026 paper was rated Moderate to Tough in overall difficulty, with heavy emphasis on mathematics.

Difficulty Assessment:

General Aptitude: Easy to Moderate - Scoring section

Core DA Subjects: Moderate to Tough - Mathematics‑focused and calculation‑intensive

Overall Paper: Moderate to Tough - Time‑consuming with tricky questions

Key Observations:

• Paper was heavily mathematics‑focused
• Many questions were calculation‑intensive and time‑consuming
• MSQ questions were of moderate difficulty
• Analytical and problem‑solving questions required careful calculations
• Machine Learning and Probability & Statistics dominated
• DBMS questions were straightforward, some tricky
• AI questions were relatively easier to manage
• Time management was crucial and challenging
• Previous year patterns partially helpful
• Strong mathematical foundation was essential

Question Distribution Pattern

The GATE DA 2026 paper had a specific distribution:

MCQs (Multiple Choice Questions): 33 questions

MSQs (Multiple Select Questions): 14 questions

NATs (Numerical Answer Type): 18 questions

Total Questions: 65

This distribution showed:

• MCQs dominated the paper (50.7%)
• MSQs had significant weightage (21.5%)
• NATs required precision (27.7%)
• No negative marking for MSQs and NATs

Section‑Wise Detailed Analysis

1. General Aptitude (15 Marks)

Difficulty Level: Easy to Moderate

The General Aptitude section was the most scoring part of the exam with standard questions.

Topics Covered:

• Verbal reasoning
• Quantitative aptitude
• Logical reasoning
• Data interpretation
• Reading comprehension
• Analytical ability

Student Feedback:

• Questions were direct and conventional
• Relatively easier compared to core sections
• Time spent: 15‑20 minutes
• Most students attempted 8‑10 questions
• High accuracy achievable with basic preparation
• This section helped boost overall scores

Expected Score: 11‑14 marks for well‑prepared students

2. Core Data Science & AI Subjects (85 Marks)

Note: GATE DA does not have a separate Engineering Mathematics section. Mathematics is integrated into the core DA syllabus.

Difficulty Level: Moderate to Tough

The core DA section was heavily mathematics‑focused and calculation‑intensive, making it the most challenging part.

High‑Weightage Topics:

Machine Learning (25‑30%)

• Supervised learning algorithms
• Unsupervised learning
• Classification and regression
• Decision trees and random forests
• Support Vector Machines
• Neural networks basics
• Model evaluation and validation
• Very high weightage - Moderate to tough

Probability and Statistics (20‑25%)

• Probability distributions
• Statistical inference
• Hypothesis testing
• Regression analysis
• Bayesian methods
• Random variables
• High weightage - Tough and tricky

Linear Algebra (15‑20%)

• Matrices and determinants
• Eigenvalues and eigenvectors
• Vector spaces
• Linear transformations
• High weightage - Calculation‑intensive

Programming and Data Structures (10‑15%)

• Python programming
• Data structures implementation
• Algorithm complexity
• Coding problems
• Moderate weightage

Database Management Systems (8‑12%)

• SQL queries
• Relational algebra
• Normalization
• Transactions
• Moderate weightage - Straightforward with some tricky

Artificial Intelligence (8‑12%)

• Search algorithms
• Knowledge representation
• Logic and reasoning
• Planning
• Moderate weightage - Relatively easier

Calculus (5‑8%)

• Differentiation
• Integration
• Differential equations
• Optimization

Data Visualization (3‑5%)

• Plotting techniques
• Data representation
• Visualization principles

Topic‑Wise Weightage Analysis

Machine Learning: 16‑20 questions (Very High)

Probability & Statistics: 13‑16 questions (Very High)

Linear Algebra: 10‑13 questions (High)

Programming & Data Structures: 6‑10 questions (Moderate)

DBMS: 5‑8 questions (Moderate)

Artificial Intelligence: 5‑8 questions (Moderate)

Calculus: 3‑5 questions (Moderate)

Data Visualization: 2‑3 questions (Low)

Good Attempts and Score Estimation

Based on student feedback and expert analysis:

Excellent Attempt: 45‑50 questions → 70‑80 marks

Very Good Attempt: 40‑45 questions → 60‑70 marks

Good Attempt: 35‑40 questions → 50‑60 marks

Safe Attempt: 30‑35 questions → 40‑50 marks

Qualifying Attempt: 25‑30 questions → 32‑40 marks

Section‑Wise Good Attempts:

General Aptitude: 8‑10 questions (11‑14 marks)

Core DA: 25‑35 questions (40‑65 marks)

Expected Cutoff for GATE DA 2026 Shift 2

Based on the moderate to tough difficulty level:

General Category: 29‑33 marks

OBC‑NCL/EWS Category: 26‑30 marks

SC/ST/PwD Category: 19‑22 marks

Important Note:

• The mathematics‑heavy and tough paper may result in moderate cutoff
• Final cutoff will depend on overall candidate performance
• Official cutoff will be declared with results on March 19, 2026

Student Reactions and Feedback

Positive Feedback:

• General Aptitude was scoring
• AI questions were relatively easier
• DBMS questions were straightforward
• Questions aligned with syllabus
• No out‑of‑syllabus questions

Challenges Faced:

• Paper was heavily mathematics‑focused
• Probability and Statistics questions were tricky
• Many calculation‑intensive problems
• Time management was extremely difficult
• Some mathematics problems very time‑consuming
• Required careful calculation for accuracy
• MSQ questions needed deep understanding
• NAT questions required precision

Common Student Comments:

"The paper was math‑heavy. If you're strong in probability and statistics, you had an advantage."

"Machine Learning questions were conceptual and required good understanding of algorithms."

"Time was a major constraint. Many questions were lengthy and calculation‑intensive."

"DBMS and AI were relatively easier sections. Math and ML were tough."

"Accuracy was more important than speed. Tricky questions everywhere."

Preparation Strategy for Future Aspirants

Based on GATE DA 2026 Analysis:

1. High‑Priority Topics:

• Machine Learning (Algorithms, Model evaluation, Neural networks)
• Probability & Statistics (Distributions, Hypothesis testing, Bayesian)
• Linear Algebra (Matrices, Eigenvalues, Transformations)
• Programming & Data Structures (Python, Algorithms)

2. Focus Areas:

• Strong mathematical foundation essential
• Fast calculation techniques
• Probability problem‑solving extensive practice
• ML algorithm implementation understanding
• Previous 5‑10 years questions (DA is relatively new)
• Regular mock tests mandatory
• Time management critical

3. Time Management:

• General Aptitude: 12‑15 minutes
• Quick easy questions: 30‑40 minutes
• Moderate questions: 80‑90 minutes
• Tough calculations: 40‑50 minutes
• Revision: 10‑15 minutes

4. Subject‑Specific Tips:

• Machine Learning: Understand algorithms deeply, not just formulas
• Probability: Practice distributions and hypothesis testing extensively
• Linear Algebra: Master matrix operations and eigenvalue problems
• Programming: Focus on Python and algorithm complexity
• DBMS: Practice SQL queries and normalization

Important Resources for GATE DA Preparation

Recommended Books:

• Machine Learning: Tom Mitchell, Andrew Ng courses
• Probability & Statistics: Sheldon Ross, Jay L. Devore
• Linear Algebra: Gilbert Strang
• Python Programming: Mark Lutz
• DBMS: Korth, Elmasri Navathe
• AI: Stuart Russell & Peter Norvig

Key Takeaways

Paper Difficulty: Moderate to Tough (Mathematics‑heavy)

Scoring Section: General Aptitude

Challenging Sections: Probability & Statistics, Machine Learning

Time Management: Extremely critical

Expected Cutoff: 29‑33 marks (General category)

Good Attempts: 35‑40 questions with high accuracy

High‑Weightage Topics: Machine Learning, Probability, Linear Algebra

Success Factor: Strong mathematical foundation essential

Frequently Asked Questions

1. Was GATE DA 2026 tougher than expected?

Yes, students found the paper moderate to tough, primarily due to mathematics‑heavy questions and extensive calculations required.

2. Which section was the most difficult?

Probability and Statistics was the most challenging section with tricky and time‑consuming problems. Machine Learning was also conceptually demanding.

3. What is a good score in GATE DA 2026?

A score of 50+ marks is considered good, 60‑70 marks is very good, and 70+ marks is excellent for top institute admissions.

4. How many questions should I attempt to qualify?

Attempt 30‑35 questions with high accuracy to safely qualify. For good colleges, aim for 40‑45 questions.

5. Which topics had highest weightage?

Machine Learning and Probability & Statistics had the highest combined weightage with approximately 30‑35 questions together.

6. Is strong mathematics mandatory for GATE DA?

Absolutely yes. The paper is heavily mathematics‑focused. Strong foundation in probability, statistics, and linear algebra is essential.

7. How important is programming for GATE DA?

Programming is moderately important with 6‑10 questions typically asked. Focus on Python and algorithm complexity.

8. Can I crack GATE DA without ML knowledge?

No. Machine Learning is the core of GATE DA with 16‑20 questions. It's impossible to score well without strong ML understanding.

9. What is the difference between GATE DA and GATE CS?

GATE DA focuses on data science, machine learning, statistics, and AI, while GATE CS focuses on core computer science topics like algorithms, OS, networks, and databases.

10. When will GATE 2026 results be declared?

GATE 2026 results are expected to be declared on March 19, 2026, as per the official schedule.

Comparison: GATE DA vs Other Papers

GATE DA 2026 Characteristics:

• Mathematics‑heavy (60‑70% math‑related)
• Machine Learning focused
• No separate Engineering Mathematics section
• Relatively new paper (started 2020)
• Growing popularity
• Fewer candidates compared to CS/EE

Unique Aspects:

• Heavy emphasis on probability and statistics
• ML algorithms tested in depth
• Python programming preferred
• Data visualization included
• Modern AI topics covered

Memory‑Based Questions (Sample)

Note: These are memory‑based questions shared by students. Exact wording may vary.

Machine Learning: Students reported questions on supervised learning algorithms, model evaluation metrics, decision trees, and neural network basics.

Probability & Statistics: Questions on probability distributions, hypothesis testing, and Bayesian methods were asked. These were particularly tricky and calculation‑intensive.

Linear Algebra: Matrix operations, eigenvalue problems, and vector space questions were featured prominently.

DBMS: SQL queries and normalization questions were straightforward with a few tricky conceptual questions.

Artificial Intelligence: Search algorithms and knowledge representation questions were relatively easier compared to other sections.

Conclusion

The GATE DA 2026 Shift 2 exam was moderately tough with heavy emphasis on mathematics, particularly probability, statistics, and machine learning. The paper rewarded candidates with strong mathematical foundations and conceptual clarity in ML algorithms.

Students who focused on high‑weightage topics like Machine Learning, Probability & Statistics, and Linear Algebra had better chances of performing well. Time management and calculation accuracy were crucial factors.