The Graduate Aptitude Test in Engineering, or GATE, has long been a prestigious examination for those seeking to pursue advanced studies in engineering and related fields. In a dynamic world driven by data and artificial intelligence, GATE has adapted to the changing landscape by introducing a new paper – Data Science and Artificial Intelligence (DA) – in 2024. This move reflects the growing importance of these domains in the world of technology and academia. Join us on this journey as we unravel all there is to know about GATE DA 2024, the gateway to unlocking a future in the dynamic realms of Data Science and Artificial Intelligence.
Table of contents
Overview of GATE DA
GATE is a highly competitive examination in India, primarily taken by students who have completed or are in their final year of undergraduate studies. GATE is a gateway to pursue higher education, specifically Master’s and Ph.D. programs, in various technical and scientific fields. It’s an essential step for those aspiring to excel in their academic careers.
GATE offers a wide range of papers, each corresponding to a specific field of study. In recent years, GATE has evolved to reflect the changing technological landscape. For instance, it introduced a new paper in 2024 dedicated to Data Science and Artificial Intelligence (DA). On the other hand, Computer Science (CS) has been a longstanding and popular GATE paper.
While Data Science & Artificial Intelligence, and Computer Science share some common ground, they are distinct fields with unique focuses. Computer Science encompasses various topics, including algorithms, programming, and computer systems. In contrast, Data Science & Artificial Intelligence concentrate on data analysis, machine learning, and the development of intelligent systems.
The divergence between these fields is evident in the required specialized knowledge and skills. GATE provides opportunities for students to choose their area of expertise based on their interests and career goals, whether it’s traditional Computer Science or the emerging field of Data Science and Artificial Intelligence.
The Gate examiners conduct the Gate exam through CBE or Computer Based Examination mode. Government job seekers and those aspiring to gain acceptance by Government institutions for higher studies consider the score and ranking significant.
Besides, private institutions and different projects also prefer candidates with good GATE scores.
Important Dates
The dates to remember if you are interested in GATE 2024 are:
| Event | Date |
| Beginning of the online application process | August 30, 2023 |
| Closure of online registration and application process (no late fees will be levied) | September 29, 2023 |
| Closure of extended online registration and application process (with late fees) | October 13, 2023 |
| Window open for modifications in GATE 2024 applications | November 7 to 11, 2023 |
| GATE Admit card download | January 3, 2024 |
| GATE 2024 Examination date | February, 3, 4, 10 and 11, 2024 |
| Check responses in the exam at the Application portal | February 16, 2024 |
| Availability of answer keys on the GATE portal | February 21, 2024 |
| Challenge the answer keys on the GATE portal | February 22 to 25, 2024 |
| Results announcement for GATE 2024 | March 16, 2024 |
| Download GATE scorecards | March 23, 2024 |
Eligibility Criteria
To be eligible for the GATE (Graduate Aptitude Test in Engineering) Data Science and Artificial Intelligence (DA) exam, candidates must meet specific criteria:
- Educational Qualification: Candidates should have a Bachelor’s degree in Science (Post-Diploma/4 years after 10+2) or B.Sc. (Research) / B.S. in a relevant field. This includes degrees in Science and Engineering.
- Currently Enrolled: Candidates should be currently in the 3rd year or higher of their qualifying Bachelor’s degree program in the specified fields.
- Post-Diploma Candidates: Candidates with a Bachelor’s degree in Science (Post-Diploma) are also eligible.
GATE DA Syllabus
The GATE 2024 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.
Registration and Application Process
Candidates must first register on the website and fill in the application form.
Step 1: Click on the link (https://gate2024.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.iisc.ac.in/register).
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 2024 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 Data Science and Artificial Intelligence Marking Scheme
The GATE Data Science and Artificial Intelligence 2024 paper will be divided into two sections. The General aptitude part and core discipline. The General Aptitude part will be 15 marks, and the subject questions will be 85, making the total question paper 100.
You should attempt these questions within 180 minutes. 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:
- A ‘1-mark MCQ’ will be deducted with ⅓ mark for a wrong answer.
- A ‘2-mark MCQ’ will be deducted with a ⅔ mark for the wrong answer.
- Candidates must note no negative marking for Numerical Answer Type or NAT questions.
Also, partial marks will not be awarded in MSQ or Multiple Select Questions.
GATE Data Science and Artificial Intelligence Exam Pattern
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.
Question Type Based on Answering Method
- Multiple Choice Questions or MCQs: You must select one correct option among the present options.
- Multiple Select Questions or MSQs: You must select all the appropriate answers from the available options.
- Numerical Answer Type or NAT: You will not have any option. You will have to enter the numerical digits as the answer.
Skills Tested in GATE DA 2024
- Recall: The examiners will test candidates’ memory-based knowledge, including principles, formulas, laws, and facts.
- Comprehension: The examiners will assess candidates’ inference and concluding abilities based on the provided information. It can be a scenario or experiment or similar other comprehensive questions.
- Application: These questions will test the candidate’s ability to utilize the application skills of the obtained knowledge. It simply tests practical abilities.
- Analysis and Synthesis: The candidates must analyze the question thoroughly and use their imagination and drawing skills to conclude. Rough flow charts or images will be helpful here.
Conclusion
As we move forward in this data-driven era, GATE DA 2024 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. These blogs and courses will be helpful for a person who wants to take the exams.
All the best!
