GATE has been a pivotal exam for advanced studies in engineering and technology. Last year, the GATE DA paper was introduced, establishing Data Science and AI as distinct fields, separate from Computer Science. GATE DA 2025 builds on this initiative, offering specialized opportunities in Data Science, AI, and Big Data. Let’s explore everything about GATE DA 2025, including important dates, previous year cutoffs, and more.
The Graduate Aptitude Test in Engineering (GATE) is a pivotal examination in India, serving as a gateway for postgraduate studies and recruitment in technical fields. In 2024, recognizing the distinct and growing importance of Data Science and Artificial Intelligence (AI), GATE introduced a dedicated paper for these disciplines, separating them from the traditional Computer Science (CS) paper.
The dates to remember if you are interested in GATE 2025 are:
Event | Date |
Beginning of the online application process | August 28, 2024 |
Closure of online registration and application process (no late fees will be levied) | October 3, 2024 |
Closure of extended online registration and application process (with late fees) | October 11, 2024 |
Window open for modifications in GATE 2024 applications | October 31, 2024 to November 20, 2024 |
GATE Admit card download | January 2, 2025 |
GATE 2024 Examination date | February 1, 2, 15 & 16, 2025 |
Check responses in the exam at the Application portal | February 2025 |
Availability of answer keys on the GATE portal | February 2025 |
Challenge the answer keys on the GATE portal | February 2025 |
Results announcement for GATE 2024 | March 19, 2025 |
Download GATE scorecards | March 28 to May 31, 2025 |
To be eligible for the GATE (Graduate Aptitude Test in Engineering) Data Science and Artificial Intelligence (DA) exam, candidates must meet specific criteria:
As mentioned, the examiners will divide 100 marks into two sections to test their abilities. They will categorize the questions into two types based on the answering method and the knowledge.
GATE DA 2025 is a Computer-Based Test (CBT) where students must go to their respective examination centres.
The exam is 3 hours (180 minutes).
There are 2 sections: General Aptitude (GA) and Candidate’s Selected Subject.
The test will include 10 questions from GA and 55 questions specific to the candidate’s chosen subject. Thus, the total number of questions is 15 + 85 = 100.
The questions can carry either 1 or 2 marks. Furthermore, there is a negative marking for incorrect answer choices. But no marks will be deducted if you leave the answer blank.
The negative marking goes like this:
Also, partial marks will not be awarded in MSQ or Multiple Select Questions.
The exam date according to the papers.
GATE 2025 Exam Day and Date | Timings | GATE 2025 Test Papers |
---|---|---|
February 1, 2025 (Saturday) | 9:30 AM to 12:30 PM | CS1, AG, MA |
2:30 PM to 5:30 pm | CS2, NM, MT, TF, IN | |
February 2, 2025 (Sunday) | 9:30 AM to 12:30 PM | ME, PE, AR |
2:30 PM to 5:30 PM | EE | |
February 15, 2025 (Saturday) | 9:30 AM to 12:30 PM | CY, AE, DA, ES, PI |
2:30 PM to 5:30 PM | EC, GE, XH, BM, EY | |
February 16, 2025 (Sunday) | 9:30 AM to 12:30 PM | CE1, GG, CH, PH, BT |
2:30 PM to 5:30 PM | CE2, ST, XE, XL, MN |
The GATE 2025 DA syllabus encompasses diverse subjects; these topics encapsulate the fundamental knowledge required to excel in data science and AI. Lets have a look at the prescribed syllabus:
Subjects | Subtopics |
---|---|
Probability and Statistics | Counting (Permutations and Combinations) Probability Axioms Sample Space Events Independent Events Mutually Exclusive Events Marginal, Conditional, and Joint Probability Bayes’ Theorem Conditional Expectation and Variance Mean, Median, Mode, and Standard Deviation Correlation and Covariance Random Variables Discrete Random Variables and Probability Mass Functions (Uniform, Bernoulli, and Binomial Distribution) Continuous Random Variables and Probability Distribution Functions (Uniform, Exponential, Poisson, Normal, Standard Normal, t-Distribution, Chi-Squared Distributions) Cumulative Distribution Function Conditional Probability Density Function Central Limit Theorem Confidence Interval z-Test t-Test Chi-Squared Test |
Linear Algebra | Vector Space Subspaces Linear Dependence and Independence of Vectors Matrices Projection Matrix Orthogonal Matrix Idempotent Matrix Partition Matrix and Their Properties Quadratic Forms Systems of Linear Equations and Solutions Gaussian Elimination Eigenvalues and Eigenvectors Determinant Rank Nullity Projections LU Decomposition Singular Value Decomposition |
Calculus and Optimization | Functions of a Single Variable Limit Continuity and Differentiability Taylor Series Maxima and Minima Optimization Involving a Single Variable |
Programming, Data Structures, and Algorithms | Programming in Python Basic Data Structures: Stacks, Queues, Linked Lists, Trees, and Hash Tables Search Algorithms: Linear Search and Binary Search Basic Sorting Algorithms: Selection Sort, Bubble Sort, Insertion Sort Divide and Conquer Techniques: Mergesort, Quicksort Introduction to Graph Theory Basic Graph Algorithms: Traversals and the Shortest Path |
Database Management and Warehousing | ER-Model (Entity-Relationship Model) Relational Model: Relational Algebra, Tuple Calculus SQL (Structured Query Language) Integrity Constraints Normal Form File Organization Indexing Data Types Data Transformation: Normalization, Discretization, Sampling, and Compression Data Warehouse Modeling: Schema for Multidimensional Data Models Concept Hierarchies Measures: Categorization and Computations |
Machine Learning | Supervised and Unsupervised Learning Regression and Classification Problems Simple Linear Regression Multiple Linear Regression Ridge Regression Logistic Regression k-Nearest Neighbors Naive Bayes Classifier Linear Discriminant Analysis Support Vector Machine Decision Trees Bias-Variance Trade-off Cross-validation Methods: Leave-One-Out (LOO) Cross-validation, k-Folds Cross-validation Multi-layer Perceptron Feed-forward Neural Network Clustering Algorithms k-Means and k-Medoid Clustering Hierarchical Clustering Dimensionality Reduction Principal Component Analysis (PCA) |
Artificial Intelligence (AI) | Search: Informed Search, Uninformed Search, Adversarial Search Logic: Propositional Logic, Predicate Logic Reasoning under Uncertainty Topics Conditional Independence Representation Exact Inference through Variable Elimination Approximate Inference through Sampling |
Here is the link for the elaborate syllabus.
Candidates must first register on the website and fill in the application form.
Step 1: Click on the link (https://gate2025.iisc.ac.in/), scroll down, and click on the ‘login’ button.
Step 2: Once redirected, scroll down to ‘register here’ again. Alternatively, you can visit the link directly (https://goaps.iitr.ac.in/login).
Step 3: Fill in your details and click on ‘confirm.’ You will get a confirmation message displayed. Cross-check the name spelling and go ahead.
Step 4: Further blank columns will open to fill in the details like email address, phone number, password, and captcha code. Click on the ‘register’ option.
Step 5: You will get a confirmation message. Now, receive credentials on email and mobile number. Move ahead to log in and fill in the details.
Step 6: Once you log in, check the declaration box. Tick the box after reviewing the information brochure and click ‘Start filling out the GATE 2025 application form’.
Step 7: Fill in all the details for the exhibited sections, followed by paying the timely fees to be eligible for appearing for the exam.
GATE DA has been recognized by several premier institutions in India for their postgraduate programs. Here’s an overview of some top colleges accepting GATE DA:
As we move forward in this data-driven era, GATE DA 2025 stands as a beacon of opportunity for those who aspire to shape the future through Data Science and Artificial Intelligence. It offers a platform to embark on a rewarding academic and professional journey, unlocking doors to exciting careers in these rapidly evolving fields. Analytics Vidhya’s blog and Free Courses cover many topics in the GATE DA syllabus.
All the best!