- Courses
- Tutorials
- Jobs
- Practice
- Contests
08069289001GATE Data Science and Artificial Intelligence 2024
-1669185704.svg){kind=small}
8k+ interested GeeksCourse Description
Unlock success with our GATE Data Science and ArtificiaI Intelligence 2024. 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!
100+ hours
2 Seats Left
Payday Exclusive Offer: Save Additional 25% | Use Coupon: SPENDSMART
In case of any queries reach us via Call/WhatsApp on +91-7903436178
Course Overview
Course Overview
Embark on a transformative learning journey with our specially designed GATE Data Science and ArtificiaI Intelligence 2024 course! Our expert mentors have skillfully combined self-paced learning modules and Live Classes to empower you for GATE 2024 and other competitive exams. This holistic course offers a blend of Strategy, Tips and tricks, Problem-Solving, and Core concept-building sessions that comprehensively cover the entire GATE syllabus.
Whether you're just starting your preparation or looking to brush up on specific topics, our course is tailored to meet the needs of learners at every stage. Dont miss out on this golden opportunity to accelerate your GATE journey. Enroll now to claim your spot.
Key Highlights:
- Expert-Led Live Classes: Get real-time instruction and mentorship from experts in the field of Data Science and AI.
- Comprehensive Coverage: Enjoy a well-rounded curriculum that covers all topics, from Probability and Stats to Machine Learning and AI, in alignment with the official GATE syllabus.
- Self-Paced Modules: Flexibility at its bestbalance live sessions with self-study modules on Probability, ML, DBMS, DSA, etc
- Weekend Concept Booster Sessions: Take part in special weekend sessions aimed at solidifying your grasp on complex topics.
- Instant Doubt Solving: Get real-time answers to your queries in dedicated doubt-solving sessions led by IIT toppers.
- Real-World Assignments: Apply your theoretical knowledge to practical assignments for hands-on experience in Data Science and AI.
What you will learn
What you will learn
- Get a solid grasp on Mathematics concepts like Probability, Statistics, Calculus and Linear Algebra to build a strong foundation for Data Science and AI.
- Acquire hands-on programming skills in Python, an essential language for Data Science and AI applications.
- Gain proficiency in Data Structures like stacks, queues, and trees, and learn essential sorting and searching algorithms.
- Become skilled in relational databases, SQL, and data warehousing to effectively manage and utilize data.
- Delve into supervised and unsupervised learning methods such as linear regression, decision trees, and k-means clustering.
- Explore AI topics from basic search algorithms to advanced adversarial learning, gaining a rounded skill set.
Course Content
- Permutations and Combinations
- Probability Axioms
- Sample Space and 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 Distribution
- Bernoulli Distribution
- Binomial Distribution - Continuous Random Variables and Probability Distribution Functions
- Uniform Distribution
- Exponential Distribution
- Poisson Distribution
- Normal Distribution
- Standard Normal Distribution
- t-Distribution
- Chi-Squared Distributions - Cumulative Distribution Function
- Conditional Probability Density Function
- Central Limit Theorem
- Confidence Interval
- z-Test
- t-Test
- Chi-Squared Test
- 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 and Nullity
- Projections
- LU Decomposition
- Singular Value Decomposition
- Functions of a Single Variable
- Limit, Continuity, and Differentiability
- Taylor Series
- Maxima and Minima
- Optimization Involving a Single Variable
- Programming in Python
- Basic Data Structures
- Stacks
- Queues
- Linked Lists
- Trees
- Hash Tables - Search Algorithms
- Linear Search
- Binary Search - Basic Sorting Algorithms
- Selection Sort
- Bubble Sort
- Insertion Sort - Divide and Conquer
- Merge Sort
- Quick Sort - Introduction to Graph Theory
- Basic Graph Algorithms
- Traversals
- Shortest Path