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Get ready to unlock success with our GATE Data Science and ArtificiaI Intelligence 2028. Specially curated by experts, our courses in Machine Learning and Artificial Intelligence are your gateway to academic excellence. Fast-track your career and unleash your potential - Enroll now!
Beginner to Advance156 Weeks
471 interested Geeks
Course Overview
Key Highlights:
150+ hours of recorded content
500+ hours of live content
Daily Pratice Problem provided
6 Months of 24/7 One-on-One AI Doubt Assistance
Supporting Notes/Documentation for every lecture.
Course Coverage:
Probability and Statistics
Linear Algebra
Calculus and Optimization
Programming, Data Structures and Algorithms
Database Management and Warehousing
Machine Learning
Artificial Intelligence
General Aptitude
Course Features
Expert mentors have curated an in-depth coverage of all GATE subjects.
The course includes detailed strategies to approach and excel in the GATE exam.
You will learn quick tips and effective tricks to solve problems efficiently.
Extensive practice sessions are provided to enhance your problem-solving skills.
The course is designed to strengthen your understanding of fundamental concepts.
There is thorough coverage of the entire GATE syllabus to ensure comprehensive preparation.
Learning Benefits:
Guidance from Expert Mentors
Comprehensive GATE syllabus coverage
Exclusive access to e-study materials
Online doubt-solving with AI
Quizzes, DPPs and Previous Year Questions solutions
Enroll now to excel in GATE and achieve your dream IIT or PSU!
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What you will learn
What you will learn
The finest GATE faculties and a team of Subject Matter Experts committed to providing you with the best learning and knowledge.
Weekly Study Schedules & Strategy
Concept Builder Modules
Mock Test Series, Problem Solving & Quizzes
GATE Modules covering PYQ solutions
Live Doubt Solving Sessions
Score Boosting guidance
Course Content
01Probability 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, Binomial Distribution
Continuous Random Variables and Probability Distribution Functions
Uniform, Exponential, Poisson, Normal, Standard Normal Distributions