GATE DA (Data Science and Artificial Intelligence) Syllabus 2025 - PDF Available
Last Updated :
26 Jul, 2025
GATE 2025 DA (Data Science and Artificial Intelligence) is a new paper added by GATE Authorities last year (in 2024). With the addition of Data Science and Artificial Intelligence in GATE, students can choose one more field for their master's (ME) or postgraduate engineering (M.Tech).
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To learn and prepare for GATE refer to our page GATE DA Notes.
In this GATE Data Science and Artificial Intelligence Syllabus 2025, we have briefly explained the section-wise syllabus, eligibility criteria, exam pattern, marking scheme, exam tips and book recommendations to help students for the upcoming GATE 2025 exam.
GATE Data Science and Artificial Intelligence Syllabus 2025GATE Data Science and Artificial Intelligence Syllabus PDF 2025
IIT Roorkee has released the official syllabus for GATE DA 2025 Exam, giving candidates a clear idea of the topics and concepts they need to prepare.
Download the latest GATE Data Science and Artificial Intelligence Syllabus PDF here "GATE Data Science and Artificial Intelligence Syllabus"
GATE Data Science and Artificial Intelligence (DA) Subjects
A variety of topics are covered in the GATE Data Science and Artificial Intelligence courses that are crucial for comprehending and succeeding in the discipline. The following are some of the main GATE data science and artificial intelligence topics covered in the curriculum:
GATE DA 2025 Syllabus (Core Subjects)
The syllabus for GATE Data Science and Artificial Intelligence in 2025 is categorized into 7 sections, covering topics such as Probability and Statistics, Linear Algebra, Calculus and Optimization, Machine Learning, and AI.
We can refer to the table below for a detailed breakdown of the GATE Data Science and Artificial Intelligence Syllabus 2025.
Sections-Wise (Topics) | Sub-Topics |
|---|
| Section 1: Probability and Statistics | - Counting (Permutation 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, binomial distribution
- Continuous Random Variables and Probability Distribution Function
- Uniform, Exponential, Poisson, Normal, Standard Normal, t-Distribution
- Chi-Squared Distributions
- Cumulative Distribution Function
- Conditional PDF
- Central Limit Theorem
- Confidence Interval
- z-test
- t-test
- Chi-Squared Test
|
| Section 2: Linear Algebra | |
| Section 3: Calculus and Optimization | |
| Section 4: Programming, Data Structures and Algorithms | |
| Section 5: Database Management and Warehousing | |
| Section 6: Machine Learning | |
| Section 7: Artificial Intelligence (AI) | |
Also Check: GATE 2025 Syllabus For CSE
GATE 2025 Eligibility Criteria for DA and AI
GATE Eligibility Criteria 2025: Here you will find details about the GATE 2025 Eligibility Criteria like the exam's age restriction, nationality, relaxation, requirements, etc. To appear in the Graduate Aptitude Test in Engineering and be deemed qualified for the test, candidates must fulfill the requirements of GATE 2025. We have Summarized the eligibility criteria for the GATE 2025 Data Science and Artificial Intelligence exam below:
Criteria | Eligibility |
|---|
| Nationality | - Indian nationality candidates will be eligible.
- Candidates from other than India will be also eligible
|
|---|
| Qualification for the GATE exam | - Applicants must hold a master's degree in any relevant science field or graduation in engineering/technology or a diploma in engineering or technology.
- Applicants may also appear for GATE 2025 if they are in the pre-final or final year of their qualifying degree.
- Candidates from nations other than India who have earned or are working towards their qualifying degree: Must be in their third year or above, or have finished their Bachelor's degree in Engineering, Technology, Science, Arts, or Commerce (duration: at least 3 years).
|
|---|
| GATE Age Limit | There is no age limit for GATE 2025. |
|---|
| GATE Attempt | There is no constraint on the number of GATE attempts. |
|---|
GATE 2025 Preparation Tips for Data Science and Artificial Intelligence
Here are some tips for cracking GATE 2025 with AI and DS:
- Before you start studying, familiarize yourself with the GATE 2025 exam pattern and syllabus.
- Create a disciplined study schedule and follow it religiously.
- Determine which GATE 2025 themes are more important and focus more on them.
- Choose relevant reference sources for your research.
- Acknowledge your strengths and concentrate on strengthening your weaknesses.
- To get accustomed to the format of the question paper, take practice exams.
GATE 2025 Data Science and Artificial Intelligence Exam Pattern
For the GATE 2025 data science and artificial intelligence exam, here is the detailed exam pattern:
GATE 2025 Artificial Intelligence and Data Science(DA) Exam Pattern |
|---|
| Exam Duration | 3 hour |
| Mode of Examination | Online Computer Based Test(CBT) |
| Total Marks | 100 |
| Total Questions | 65 Questions Split in: - General Aptitude-10 questions
- Artificial Intelligence and Data Science(DA)-55 questions
|
| Types of Question | - MCQs(Multiple Choice Questions)
- MSQs(Multiple Select Questions)
- NAT(Numerical Answer Type Questions)
|
| Marks Distribution | - General Aptitude= 15 questions worth 25 marks
- Core Subject= 50 Questions worth 75 marks
|
| Negative Marking | *Applicable only to wrongly answered MCQ - -1/3 for 1 mark MCQ
- -2/3 for 2 mark MCQ
|
GATE 2025 Data Science and Artificial Intelligence Marking Scheme
please find below the revised marking scheme for gate 2025 Data Science and Artificial Intelligence:
Gate 2025 Data Science and Artificial Intelligence Marking scheme |
|---|
| SECTIONS | Total Questions | Marking |
|---|
| General Aptitude | 15 | 5 question x 1 marks - +1 marks(correct)
- -1/3 for incorrect answer
5 question x 2 marks - +2 mark (Correct)
- -2/3 (incorrect)
Total marks=25 |
|---|
| Core Discipline | 50 | 25 question x 1 marks - +1 marks(Correct)
- -1/3 (incorrect)
30 question x 2 marks - +1 mark(Correct)
- -1/3 mark(Incorrect)
Total Marks= 85 |
|---|
| | Total Questions = 65 | Total Marks= 100 |
|---|
How Do I Prepare for GATE 2025 Data Science and Artificial Intelligence?
GATE is one of the toughest competitive exams, which requires practice and preparation to crack it. There are various ways to prepare for a GATE exam. Some of them are listed below.
- Make Appropriate Plans: Before beginning to study for an exam, it is always a good idea to make appropriate plans. Make weekly, monthly, and annual plans out of the plan.
- Recognize Your Strengths and Weaknesses: Knowing your strengths and weaknesses is a necessary first step before delving deeply into anything.
- Learn Well: It is quite hard to pass the test without doing your homework. We are giving you the necessary resources to study the GATE syllabus. For GATE studies, you might consult the GATE CS Notes.
- Review Thoroughly: Whether it's for the GATE or any other exam, you must thoroughly review it to pass it. For revision, you can consult the GATE CSE brief notes and the Last Minute Notes.
- Practice Previous Year Questions: To pass any test, it is crucial to practice Previous Year Questions. We provide last year's questions for every subject, which will aid you in your preparation.
- Practice Mock Tests: Before the real exam, mock tests assist in the analysis of the exam papers. It is also incredibly helpful for any exam. To help students get ready for the test, we also offer free practice exams.
Book Recommendations to Prepare for Gate 2025 AI and DS Exam
To crack the tough exam at the gate, one should be fully prepared. You will need good Study materials for this, so we have curated the list of best books to prepare for the GATE 2025 artificial intelligence and data science exam:
Books Recommendations to Prepare for GATE DS and AI 2025 |
|---|
| Book | Author |
| Introduction to Probability | Dimitri P. Bertsekas & John N. Tsitsiklis |
| Introduction to Linear Algebra | Gilbert Strang |
| Learning Python | Mark Lutz |
| Database Management Systems | Raghu Ramakrishnan and Johannes Gehrke |
| Machine Learning for Beginners | Chris Sebastian |
| Artificial Intelligence: A Modern Approach | Stuart Russell and Peter Norvig |
| Pattern Recognition and Machine Learning | Christopher M. Bishop |
| Deep Learning | Ian Goodfellow, Yoshua Bengio, and Aaron Courville |
| Elements of Statistical Learning | Trevor Hastie, Robert Tibshirani, and Jerome Friedman |
| Speech and Language Processing | Daniel Jurafsky and James H. Martin |
| Computer Vision: Algorithms and Applications | Richard Szeliski |
| Python Machine Learning | Sebastian Raschka and Vahid Mirjalili |
| Introduction to the Theory of Computation | Michael Sipser |
| Bayesian Reasoning and Machine Learning | David Barber |
| Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow | Aurélien Géron |
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