GATE Data Science and Artificial Intelligence (DA) Syllabus Topic Map & Practice
GATE DA covers probability and statistics, linear algebra, calculus and optimisation, programming and data structures, database management, machine learning, and artificial intelligence, plus the common general aptitude section.
8 subjects · 57 topics · 363 subtopics
Official scope and learning resources
This is our practice taxonomy, not a verbatim official syllabus or a claim that every subtopic has published questions. Check the current official document before planning examination coverage.
Solved GATE DA previous year questions
195 questions with official answers and step-by-step solutions.
General Aptitude
Revise General Aptitude: concept notes, worked examples and PYQsVerbal Aptitude
- English Grammar (Tenses, Articles, Prepositions, Conjunctions)
- Verb-Noun Agreement & Parts of Speech
- Vocabulary (Words, Idioms, Phrases in Context)
- Reading Comprehension
- Narrative Sequencing
Quantitative Aptitude
- Data Interpretation (Bar, Pie, Graphs, Tables)
- Ratios, Percentages, Powers, Exponents & Logarithms
- Permutations & Combinations
- Series
- Mensuration & Geometry
- Elementary Statistics & Probability
- Simple & Compound Interest
- Alligation & Mixture
- Partnership
- Time & Work
Analytical Aptitude
- Deduction & Induction
- Analogy
- Numerical Relations & Reasoning
Spatial Aptitude
- Transformation of Shapes (Translation, Rotation, Scaling, Mirroring)
- Paper Folding, Cutting & Patterns
- 2D & 3D Patterns
Probability & Statistics
Revise Probability & Statistics: concept notes, worked examples and PYQsCounting
- Factorials
- Permutations
- Combinations
- Binomial Theorem
- Multinomial Theorem
- Inclusion-Exclusion (PIE)
- Seating Arrangements
- Circular Arrangements
- Derangements
Probability
- Sample Space & Events
- Probability Axioms
- Conditional Probability
- Multiplication Theorem
- Independent Events
- Mutually Exclusive Events
- Marginal Probability
- Joint Probability
- Total Probability
- Bayes' Theorem
Descriptive Statistics
- Mean
- Mode
- Median
- Skewness
- Kurtosis
- Range
- Interquartile Range
- Variance
- Standard Deviation
- Covariance
- Correlation
Discrete Random Variables
- PMF
- CDF (Discrete)
- Expectation (Discrete)
- Variance (Discrete)
- Conditional Distributions (Discrete)
- Conditional Expectation
- Conditional Variance
- Covariance of RVs
- Joint PMF
- Joint CDF (Discrete)
- Independent RVs (Discrete)
- Discrete Uniform
- Bernoulli
- Binomial
- Poisson
Continuous Random Variables
- CDF (Continuous)
- Expectation (Continuous)
- Variance (Continuous)
- Conditional PDF
- Conditional Distributions (Continuous)
- Conditional Expectation (Continuous)
- Conditional Variance (Continuous)
- Covariance (Continuous)
- Joint PDF
- Joint CDF (Continuous)
- Independent RVs (Continuous)
- Uniform (Continuous)
- Exponential
- Normal
- Standard Normal
- Standardization & z-Score
Statistical Inference
- Markov's Inequality
- Chebyshev's Inequality
- Central Limit Theorem
- Sample Mean
- Sample Variance
- Point Estimation
- Confidence Intervals
- Hypothesis Testing
- z-Test
- t-Test
- Chi-Square Test
- t-Distribution
- Chi-Squared Distribution
- Sampling Distributions
Calculus & Optimization
Revise Calculus & Optimization: concept notes, worked examples and PYQsFunctions
- Standard Functions
- Odd & Even Functions
- Types of Functions
- Inverse Functions
Limits
- Limits
- Standard Limits
- Limit Laws
Continuity & Differentiability
- Continuity
- Differentiability
- Limits, Continuity & Differentiability
- L'Hôpital's Rule
- Mean Value Theorem
- Differentiation
Taylor Series
- Taylor Series Theorem
- Taylor Series of Standard Functions
- Ratio Test
Maxima, Minima & Optimization
- Maxima & Minima
- Single Variable Optimization
Linear Algebra
Revise Linear Algebra: concept notes, worked examples and PYQsMatrix Algebra
- Scalars, Vectors, Matrices & Tensors
- Types of Matrices
- Matrix Addition & Subtraction
- Scalar Multiplication
- Matrix Multiplication & Conformability
- Transpose
- Symmetric & Skew-Symmetric
- Idempotent, Involutory & Nilpotent
- Orthogonal & Partitioned Matrices
- Periodic Matrices
- Trace of a Matrix
Vector Algebra
- Vector Notation & Operations
- Dot Product
- Angle Between Vectors
- Orthogonality
- Norms (L1, L2, Lp, Max)
- Euclidean Distance & Metrics
- Projection of Vectors
- Projection Matrix
Vector Spaces, Basis & Dimensions
- Vector Spaces
- Subspaces
- Linear Combinations
- Span
- Linear Independence & Dependence
- Basis & Dimension
- Rank of a Matrix
Systems of Linear Equations
- Homogeneous Systems
- Non-Homogeneous Systems
- Nullity
- Rank-Nullity Theorem
- Gaussian Elimination
- Echelon Forms
- Gauss-Jordan Elimination
- Inverse of a Matrix
Orthogonality & Projections
- Orthogonal Subspaces
- Four Fundamental Subspaces
- Projections & Least Squares
- Gram-Schmidt Orthogonalization
- Orthogonal Matrices
- QR Decomposition
LU Decomposition & Determinants
- LU Decomposition
- Determinant Calculation
- Determinant Properties
- Vector & Matrix Transformations
- Matrix of a Linear Map
Eigenvalues & Eigenvectors
- Eigenvalue Computation
- Eigenvector Computation
- Diagonalization
- Defective Matrices
- Properties of Eigenspaces
- Symmetric Matrices
- Quadratic Forms
- Positive Definite Matrices
- Spectral Theorem
Singular Value Decomposition
- SVD Formulation
- Singular Values
- Low-Rank Approximation
- Applications of SVD
Programming, Data Structures & Algorithms
Revise Programming, Data Structures & Algorithms: concept notes, worked examples and PYQsPython Syntax & I/O
- Tokens & Operators
- Data Types & Expressions
- Input & Output
- Variables & Memory Management
- Operator Precedence
Data Types & Control Statements
- Conditional Statements
- Loops (for, while)
- Strings
- Lists
- Tuples
- Sets
- Dictionaries
Functions, File & Error Handling
- Functions
- Recursion
- Lambda, Map & Filter
- Comprehensions (List, Dict, Set)
- Built-in Functions & Libraries
- File Handling
- Error & Exception Handling
Stacks & Queues
- Stack Operations & Applications
- Queue Operations & Applications
Linked Lists & Hashing
- Singly Linked Lists
- Doubly Linked Lists
- Circular Linked Lists
- Hashing & Hash Tables
- Collision Handling
Complexity Analysis
- Time Complexity
- Space Complexity
- Best, Average & Worst Case
Searching & Sorting
- Linear Search
- Binary Search
- Selection Sort
- Bubble Sort
- Insertion Sort
Divide & Conquer
- Divide & Conquer Strategy
- Merge Sort
- Quick Sort
- Recurrence of Merge & Quick Sort
Trees
- Tree Properties
- Binary Tree Traversals
- BST (Insert, Search, Delete)
- AVL Trees
Graphs
- Graph Terminology
- Graph Traversals (BFS, DFS)
- BFS Shortest Path
- Dijkstra's Algorithm
- Bellman-Ford Algorithm
- Topological Sort
- MST (Prim's, Kruskal's)
Machine Learning
Revise Machine Learning: concept notes, worked examples and PYQsRegression
- Simple Linear Regression
- Multiple Linear Regression
- Lasso Regression
- Ridge Regression
- Regression Error Metrics
Classification
- Confusion Matrix & Metrics
- Classification Error Metrics
- k-Nearest Neighbors (k-NN)
- Naive Bayes Classifier
- Logistic Regression
Decision Trees & Ensembling
- Gini Index
- Information Gain
- Decision Tree Construction
- Pruning
- Bagging
- Random Forests
- Boosting
Clustering
- k-Means Clustering
- k-Medoids Clustering
- Hierarchical Clustering
- Single & Multiple Linkage
- Agglomerative Clustering
- Divisive Clustering
- Clustering Evaluation
Model Evaluation & Validation
- Regularization & Over/Underfitting
- Bias-Variance Trade-off
- Holdout Validation
- Leave-One-Out CV
- k-Fold CV
- Stratified k-Fold CV
- Model Selection
- Nested Cross-Validation
Neural Networks
- Artificial Neural Networks
- Activation Functions
- Loss Functions
- Feed-Forward Networks
- Multi-Layer Perceptron
- Gradient Descent
- Backpropagation
Dimensionality Reduction
- Principal Component Analysis (PCA)
- Linear Discriminant Analysis (LDA)
- LDA for Classification
Support Vector Machines
- SVM Theory
- Soft Margin Classifier
- Kernel Methods
Database Management & Warehousing
Revise Database Management & Warehousing: concept notes, worked examples and PYQsER Model
- ER Model Concepts
- Attributes
- Relationships
- Weak & Strong Entities
- ER Diagrams
Relational Model
- Relational Model Concepts
- Tuples
- Domain Constraints
- Key Constraints
- Integrity Constraints
- Entity Integrity
- Keys & Super Keys
ER to Relational Mapping
- Conversion Rules & Techniques
Normalization
- Functional Dependencies
- Candidate & Super Keys
- Minimal Cover
- Lossless Decomposition
- Dependency Preservation
- 1NF, 2NF, 3NF
- BCNF
Relational Algebra
- Selection & Projection
- Rename Operation
- Set Operations
- Join & Division
- Extended Operations
- Relational Calculus (TRC)
SQL
- CRUD Operations
- Views
- ALTER Command
- Arithmetic Operations
- Aggregate Functions
- Filtering, Grouping & Nested Queries
- Joins
File Organization & Indexing
- File Organization
- Records
- Primary Indexing
- Secondary Indexing
- Clustering Indexing
- B Trees
- B+ Trees
Data Mining
- Data Types
- Similarity Measures
- Data Preprocessing
- Data Normalization
- Discretization
- Lossless & Lossy Compression
- Sampling
Data Warehousing
- Warehouse Architecture
- Data Marts & Lakes
- Warehouse Modelling
- Data Cube
- Multidimensional Schemas
- Concept Hierarchies
- Measure Types
- Cube Measure Computation
- OLAP Operations
- OLAP Indexing
- Cube Storage
Artificial Intelligence
Revise Artificial Intelligence: concept notes, worked examples and PYQsUninformed Search
- Breadth-First Search (BFS)
- Depth-First Search (DFS)
- Depth-Limited Search
- Iterative Deepening
- Uniform Cost Search
- Bidirectional Search
Informed Search
- Best-First Search
- Greedy Best-First Search
- A* Search
- A* Admissibility & Consistency
- Iterative Deepening A*
- Weighted A*
- AND/OR Graph
- AO* Search
Local Search
- Hill Climbing
- Simulated Annealing
- Genetic Algorithms
Adversarial Search
- Game Theory
- Minimax Search
- Alpha-Beta Pruning
- Heuristic Alpha-Beta Search
- Monte Carlo Tree Search
Propositional Logic
- Logical Connectives
- Logical Equivalence
- Propositional Inference
- Propositional Resolution
Predicate Logic
- First-Order Predicate Logic
- Predicate Inference
- Unification
- Predicate Resolution
- Translations
Uncertainty
- Bayesian Networks
- Conditional Independence
- d-Separation
- Bayesian Network Inference
- Variable Elimination
- Approximate Inference
- Sampling-Based Inference
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