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GATE 2027 – DATA SCIENCE & ARTIFICIAL INTELLIGENCE (Study Guide) by GKP_Original Version

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GKP Editorial Team
978-93-69144-01-3
2026
980
English
Softbound
210*270 mm

1 in stock

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Description

The world of engineering is evolving, and so is the GATE exam. The GATE-DA 2027 Study Guide also known as GATE DS-AI is a meticulously engineered, all-in-one resource designed for the new-age aspirant. Whether you are aiming for a specialized M.Tech in Artificial Intelligence at an IIT or a high-impact role in a modern PSU, this guide provides the exact mathematical and algorithmic depth you need to excel in the Data Science & AI (DA) paper.

What’s Inside: GATE-DA 2027 Comprehensive Guide
1. 2600+ Exam-Pattern Questions: A diverse bank of Multiple Choice (MCQs), Multiple Select (MSQs), and Numerical Answer Type (NAT) questions specifically curated for the DA/AI paper.

2. Latest Solved Papers (2024–2026): Analyze the benchmarks of the newest GATE branch with fully solved papers from its inaugural years, complete with professional explanations.

3. Digital Access to Archives: Gain exclusive online access to foundational solved papers (access details provided inside) for long-term trend analysis of data-driven questions.

4. Chapter-End Practice Exercises: Reinforce complex topics like Gradient Descent or Neural Networks immediately with topic-specific drills.

Core Subjects Covered in GATE DS-AI:
This guide is 100% aligned with the official GATE 2027 DA/AI syllabus, covering the essential pillars of modern computing:

1. Probability and Statistics: Mean, Median, Mode, Standard Deviation, Random Variables, and Distributions.

2. Linear Algebra: Vector spaces, Eigenvalues, Eigenvectors, and Matrix Decompositions.

3. Calculus and Optimization: Maxima/Minima, Gradient Descent, and Constrained Optimization.

4. Programming, Data Structures & Algorithms: Python-focused programming logic, Searching, Sorting, and Hashing.

5. Database Management & Warehousing: ER-models, Relational Algebra, SQL, and NoSQL basics.

6. Machine Learning: Supervised (Regression, Classification) and Unsupervised (Clustering) learning.

7. Artificial Intelligence: Search strategies, Logic, and Reasoning.

8. Engineering Mathematics & General Aptitude: The high-weightage sections that determine your final GATE percentile.

Why Choose This GKP GATE-DA Guide?
1. Structured Theory: Complex AI concepts like Transformers or Bayesian Networks are broken down into easy-to-digest modules with supporting diagrams.

2. Explanation-First Approach: Every solution is designed to build your data-logic and algorithmic thinking, not just provide a final answer.

3. Research & Industry Focused: Practice questions reflect the difficulty level of top-tier M.Tech admissions and data scientist recruitment tests.

4. Syllabus Integrity: 100% updated to reflect the latest changes in the official GATE 2027 DA/AI notification.

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