GATE DA Coaching in Kolkata
Data Science & AI
GATE DA prep — Engineering Mathematics to AI & ML, mapped to the exact exam blueprint.
- Interactive teaching-learning + recorded class support
- PYQ & other problem solving + regular tests
- 1:1 mentorship + doubt clearing system
Selected GATE results
Mode
Target year
Course fee
800+
Class Hours
5K+
Practice Questions
120+
Assessment Tests
1:1
Mentorship Sessions
Official GATE 2027 syllabus
GATE Data Science & AI 2027 syllabus
01Probability 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.
02Linear 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.
03Calculus and Optimization+
- Functions of a single variable, limit, continuity and differentiability, Taylor series, maxima and minima, optimization involving a single variable.
04Programming, Data Structures and Algorithms+
- Programming in Python, basic data structures: stacks, queues, linked lists, trees, hash tables
- Search algorithms: linear search and binary search, basic sorting algorithms: selection sort, bubble sort and insertion sort
- divide and conquer: mergesort, quicksort
- introduction to graph theory
- basic graph algorithms: traversals and shortest path.
05Database Management and Warehousing+
- ER-model, relational model: relational algebra, tuple calculus, SQL, integrity constraints, normal form, file organization, indexing, data types, data transformation such as normalization, discretization, sampling, compression
- data warehouse modelling: schema for multidimensional data models, concept hierarchies, measures: categorization and computations.
06Machine Learning+
- Supervised Learning: regression and classification problems, simple linear regression, multiple linear regression, ridge regression, logistic regression, k-nearest neighbour, naive Bayes classifier, linear discriminant analysis, support vector machine, decision trees, bias-variance trade-off, cross-validation methods such as leave-one-out (LOO) cross-validation, k-folds cross-validation, multi-layer perceptron, feed-forward neural network
- Unsupervised Learning: clustering algorithms, k-means/k-medoid, hierarchical clustering, top-down, bottom-up: single-linkage, multiple-linkage, dimensionality reduction, principal component analysis.
07AI+
- Search: informed, uninformed, adversarial
- logic, propositional, predicate
- reasoning under uncertainty topics — conditional independence representation, exact inference through variable elimination, and approximate inference through sampling.
08General Aptitude+
- Verbal Aptitude: Basic English grammar (tenses, articles, adjectives, prepositions, conjunctions, verb-noun agreement, and other parts of speech); basic vocabulary — words, idioms, and phrases in context; reading and comprehension; narrative sequencing.
- Quantitative Aptitude: Data interpretation (data graphs, 2- and 3-dimensional plots, maps, and tables); numerical computation and estimation (ratios, percentages, powers, exponents and logarithms, permutations and combinations, and series); mensuration and geometry; elementary statistics and probability.
- Analytical Aptitude: Logic — deduction and induction; analogy; numerical relations and reasoning.
- Spatial Aptitude: Transformation of shapes (translation, rotation, scaling, mirroring, assembling, and grouping); paper folding, cutting, and patterns in 2 and 3 dimensions.
Salient Features
What you'll get in this course
800+ hours of interactive classes
Subject-wise best faculty members
Proper concept & analytical skill development
Recorded video class support for revision
3000+ problems & question discussion in class
Additional 200+ hours of problem-solving videos
Chapter-wise updated workbooks for practice
Topic-wise PYQ discussion for each subject
Systematic revision & doubt clearance
Complete mock test series with 120+ tests
Test series includes subject-wise, sectional & full-length tests
Test-paper analysis report for assessment
Course Fees
GATE Data Science & AI course fees
| BATCH | ONLINE | CLASSROOM |
|---|---|---|
| GATE 2027 | ₹19,999 | ₹41,999 |
| GATE 2028 | ₹29,999 | ₹63,999 |
| GATE 2029 | ₹41,999 | ₹80,999 |
WHERE THE CLASSROOM BATCH RUNS
IAE Academy, 227A Rash Behari Ave, Ballygunge, Kolkata 700019. Open 10:30–19:30 every day. Online batches are also available.
Career Outcomes
What you'll be able to do
A strong GATE DA rank opens the door to postgraduate admission — M.Tech, M.E., MS-by-research, or direct PhD — at the IITs, IISc, NITs, IIITs and other CFTIs.
As one of the newest GATE papers (introduced in 2024), a good DA score positions you for admission into the specialised Data Science and AI programmes now being launched across premier institutes, typically with a monthly stipend during a funded M.Tech.
A DA score is best leveraged toward postgraduate study and research — M.Tech and MS admission, research fellowships, and national laboratories whose own entrance schemes may accept a GATE score as one channel. Recruitment routes naming the DA paper itself are still scarce, as computing vacancies often specify the Computer Science paper, so check which paper an advertisement takes.
Your GATE score stays valid for three years, letting you pursue research fellowships or a research-track PhD in machine learning, AI or statistics.
With a foundation in ML, probability, statistics and optimization, you can qualify for a career as a data scientist, ML engineer or AI researcher across academia, R&D labs and the analytics industry.
Free Resources
Free GATE DA resources
Official syllabus, previous-year papers and IAE's own Briefs. Free, with no sign-up.
CCMT 2026 closing scores, GATE DA
CCMT's own 2026 scores for the 204 programme groups that accepted GATE DA (Data Science and Artificial Intelligence): each group's Round 1 opening score and its closing score after the regular rounds, by category, with every GATE paper it accepts.
ANY GATE YEARIISc cut-offs for GATE DA
The GATE DA scores IISc itself published, 2024 to 2026: the interview- or test-call cut-offs for the M.Tech programmes and research departments that printed one, and the scores at which M.Tech offers were made, six categories for 2026 (UR, OBC-NCL, EWS, SC, ST, PwD), UR for the earlier years.
ANY GATE YEARFREE STUDY MATERIAL
General Aptitude for GATE DA
206 solved previous-year questions, notes for every topic and a formula sheet. The questions are from the EC, EE, IN papers; the section and its syllabus are the same in GATE DA.
FREE STUDY MATERIAL
Data Structures and Algorithms for GATE DA
114 solved previous-year questions, notes for every topic and a formula sheet.
FREE STUDY MATERIAL
Probability and Statistics for GATE DA
34 solved previous-year questions, notes for every topic and a formula sheet.
FREE STUDY MATERIAL
Machine Learning for GATE DA
28 solved previous-year questions, notes for every topic and a formula sheet.
FREE STUDY MATERIAL
Linear Algebra for GATE DA
19 solved previous-year questions, notes for every topic and a formula sheet.
FREE STUDY MATERIAL
Calculus and Optimization for GATE DA
13 solved previous-year questions, notes for every topic and a formula sheet.
FREE STUDY MATERIAL
Database Management and Warehousing for GATE DA
23 solved previous-year questions, notes for every topic and a formula sheet.
FREE STUDY MATERIAL
Artificial Intelligence for GATE DA
17 solved previous-year questions, notes for every topic and a formula sheet.
Ratings & Reviews
What learners say
5.0
31 reviews
“IAE Academy had been instrumental in my GATE journey. The classes were interesting and the online exams were very helpful in my preparation. I would urge everyone to join IAE Academy if they wish to succeed in GATE.”
Debrupendu Gupta
IISc Bangalore
“Securing AIR 9 in GATE allowed me to pursue M.Tech at IIT Kharagpur. IAE Academy's guidance on perseverance and time management complemented my hard work, enabling me to crack the exam on my very first attempt.”
Anindita Dhara
IIT Kharagpur
“Scoring 714 and AIR 69 in my first GATE attempt — IAE Academy proved to be pivotal in my preparation. The teachers are approachable and always ready to clear doubts, and classes were scheduled so managing college was never a problem.”
Saivi Singh
IIT Bombay
FAQ
Common questions
Can I join the GATE program in my 1st year of B.Tech?+
Should I join online or offline classes?+
Is there any EMI facility or discount available?+
Ready to begin?
Enquire now or book a free counselling session with a mentor to see if this programme is right for you.