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Learn, Understand, Discuss. "GO" for the Best.
Instructor: Sachin Mittal (MTech IISc Bangalore, Ex-Amazon Scientist, GATE AIR 33)
GO Classes Complete Discrete Mathematics and Engineering Mathematics Courses are FREE for all learners. Sign up and start learning.
Important Links (Click Below):
Discrete Mathematics Complete Course (FREE for ALL)
Engineering Mathematics Complete Course (FREE for ALL)
Enroll here for GO Classes GATE Complete Course
Enroll here for GO+Goclasses TEST SERIES
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Join GO Classes public Telegram Group for Doubt Discussions
Features of the course:
1. Quality Content: No Rote-learning. No poor understanding. No By-hearting of formulas, tables or theorems. Understand everything with proofs, intuitions, and ideas.
2. No Prerequisites: Every concept is taught from basics, without assuming any prior knowledge whatsoever.
3. Daily Homework: Practice material, with solutions, for Every Lecture to test your understanding of concepts of the respective lecture.
4. Summary Lectures: Short videos which summarise every concept and detail of the course. Helps in quick revision.
5. Quality Practice Sets: Practice Sets from standard resources, with solutions, containing a lot of quality questions for practice.
6. Weekly Quizzes: Every week, there will be a Live Quiz, containing 15-20 questions, to evaluate your understanding of concepts taught in the previous week. The Quiz questions can be seen and solved even after the live quiz is over. The weekly quizzes can be accessed by complete course enrolled students.
7. Doubt Resolution: All your doubts will be resolved directly by the faculty. There is a dedicated Telegram group for Enrolled Students of Goclasses where our faculties resolve students' doubts. So, our students don't have to go anywhere else for asking doubts.
Enrol Now.
Enroll here for GO Classes. GATE CSE Complete Course
| Linear Algebra | |||
| Lecture 1A - Why Study Linear Algebra | |||
| Lecture 1B - Linear Algebra for GATE & Interviews | |||
| Annotated Notes - Lecture 1A-1B | |||
| Lecture 1C - Linearly Independent and Linearly Dependent | |||
| Annotated Notes - Lecture 1C | |||
| Lecture 2A - Filling the Space Part 1 | |||
| Lecture 2B - Filling the Space Part 2 | |||
| Lecture 2C - Summary So far | |||
| Lecture 2D - Multiplying a Matrix & a Vector | |||
| Annotated Notes - Lecture 2 | |||
| Homework 1 - Linear Dependence & Independence | |||
| Lecture 3A - Homework 1 Discussion | |||
| Annotated Notes - Lecture 3A - Homework 1 Discussion | |||
| Lecture 3B - Why Solve System Of Linear Equations | |||
| Lecture 3C - Writing as Ax=b, Geometric Interpretation and Possible Solutions | |||
| Lecture 3D - Understanding Ax=b intuitively | |||
| Lecture 3B-D Annotated Notes | |||
| 4A. Multiplying 2 Matrices | My Walmart Interview Question | |||
| 4B. GATE 2016 Question | |||
| 4C. GATE 2014 Question | |||
| 4D. Two conceptual questions | |||
| 4E. Linear Combination of Independent vectors is unique | |||
| 4F. GATE 2017 Question | |||
| Lecture 4 Annotated Notes | |||
| 5A. Echelon Form and Pivot Columns | |||
| 5B. Gaussian Elimination | |||
| 5C. Rank | GATE 1994 Question | Rank Nullity Theorem | |||
| 5D. Finally Solving Ax=b | Five Different Questions | |||
| 5E. More than one free variable in 𝐴𝑥=0 solution | |||
| Lecture 5 Annotated Notes | |||
| 6A. GATE 2021 Question | Free variables in Non homogeneous | |||
| 6B. Solutions based on Rank(A) and Rank(A|b) | |||
| 6C. Few Questions related to rank(A) and Number of solutions | |||
| 6D. [OPTIONAL] Linearly Independent Columns with Gaussian Elimination | |||
| 6E. [Optional] Row Reduced Echelon Form | |||
| Lecture 6 Annotated Notes | |||
| Lecture 7A. Determinant | |||
| Lecture 7B. Inverse of a Matrix | |||
| Lecture 7C. Crammer's rule | |||
| Annotated Notes Lecture 7 A-C Determinant Inverse and Cramer's Rule | |||
| Lecture 8A. Introduction to Eigenvalues and Eigenvectors | |||
| Lecture 8B. Characteristic Equation | |||
| Lecture 8C. Solving for Eigenvalues and Eigenvectors | |||
| Annotated Notes Lecture 8A-C EigenValues and EigenVectors | |||
| Lecture 9A. Linearly Independent Eigen vectors with repeating eigenvalues | |||
| Lecture 9B. Three Different Examples With Repeating Lambda | |||
| Lecture 9C. Symmetric Matrices has n LI Eigen Vectors | |||
| Lecture 9D. Two Magical Properties | |||
| Annotated Notes Lecture 9A-D Eigen Vectors | |||
| Lecture 10A. Rank and Eigen Values | |||
| Lecture 10B. Examples on Rank and Eigen Values | |||
| Lecture 10C. CAYLEY-HAMILTON THEOREM | |||
| Lecture 10D. Eigen Values of AB and BA | |||
| Lecture 10E. Eigen Values of Powers of A | |||
| Annotated Notes Lecture 10A-E Rank and EigenValues | |||
| Lecture 10F. (Three Tough/Interesting GATE PYQs) | |||
| Annotated Notes Lecture 10F GATE PYQs Linear Algenra | |||
| Lecture 11A. LU Decomposition | |||
| Lecture 11B. Type Of Matrices | |||
| Annotated Notes Lecture 11A -B | |||
| LIVE Practice Questions on Linear Dependent Vectors | |||
| Annotated Notes Practice Questions on Linear Dependent Vectors | |||
| LIVE Practice Questions on Solutions of Ax = b | |||
| Annotated Notes Practice Questions on Ax=b | |||
| Weekly Quiz and Solution | |||
| Probability | |||
| Lecture 1A. Probability Definition, Sample Space and Events | |||
| Lecture 1B. Inclusion Exclusion Principle, Demorgan's Law | |||
| Lecture 1 Annotated Notes | |||
| Lecture 2A. Conditional Probability Introduction | |||
| Lecture 2B. Conditional Probability Examples | |||
| Lecture 2C. Introduction to Tree Diagram | |||
| Annotated Notes Lecture 2 Conditional Probability | |||
| Lecture 3A. Total Probability | |||
| Lecture 3B. Conditional Probability Examples | |||
| Annotated Notes Lecture 3A-3B | |||
| Lecture 3C: GATE PYQs Tree Method | |||
| Annotated Notes Lecture 3C GATE PYQs Tree Method | |||
| Lecture 3D: GATE PYQs and Bayes Theorem | |||
| Annotated Notes Lecture 3D: GATE PYQs and Bayes Theorem | |||
| [Optional] My LinkedIn Interview | |||
| Annotated Notes [Optional] My Linkedin Interview | |||
| Lecture 4A. independence of events | |||
| Lecture 4B. Conditional Independence | |||
| Annotated Notes Lecture 4A-B Independence and Conditional Independence | |||
| Lecture 4C. Independence Does not imply Conditional Independence | |||
| Annotated Notes Lecture 4C. Independence Does not imply Conditional Independence | |||
| Lecture 4D. Random Variables Introduction | |||
| Annotated Notes Lecture 4d. Random Variables Introduction | |||
| Lecture 5A. Practice Questions on Random Variables | |||
| Annotated Notes Lecture 5A. Practice Questions on Random Variables | |||
| Lecture 5B. More Practice Questions on Random Variables | |||
| Annotated Notes Lecture 5B. Practice Questions on Random Variables | |||
| Weekly Quiz 8 - Conditional Probability | |||
| LIVE Session 5: Weekly Quiz 8 (Conditional Prob) Discussion | |||
| Live Session 5 Annotated Notes | |||
| Lecture 6A. Types of Random Variables | |||
| Lecture 6b. Probability Mass Function Questions Part 1 | |||
| Lecture 6c. Probability Mass Function Questions Part 2 | |||
| Annotated Notes Lecture 6 Probability | |||
| Lecture 7a. Expectation of Discrete Random Variable | |||
| Lecture 7b Expectation vs Average | |||
| Lecture 7c.[Optional] Expectation as center of mass | |||
| Lecture 7d. MIT Question and GATE 2021 Question | |||
| Lecture 7e. Expectation of Random Variable which is a Function of Random Variable | |||
| Lecture 7 Annotated Notes | |||
| LIVE Session 6 | |||
| Live Session 6 Annotated Notes | |||
| Lecture 8a. Question number 8 | |||
| Lecture 8b. Question number 9, 10, 11 | |||
| Lecture 8c. Question number 12, 13 | |||
| Lecture 8 Annotated Notes | |||
| Lecture 9a. Cumulative Distribution Function | |||
| [LIVE] Lecture 9b - Variance Intuition and Formula | |||
| [LIVE] Lecture 9c- Variance Main Formula and Questions | |||
| [LIVE] Lecture 9d- Variance Questions | |||
| Lecture 9 Annotated Notes | |||
| [LIVE] Lecture 10a: Discrete random variable (Bernoulli and Binomial RVs) | |||
| [LIVE] Lecture 10b. MIT Question on Binomial RV | |||
| [LIVE] Lecture 10c. Optional and Skip - Question on Plot of PMF | |||
| [LIVE] Lecture 10d. Poisson RV | |||
| 10d. Discrete Uniform RV Introduction | |||
| [LIVE] Lecture 10 Annotated Notes | |||
| Lecture 11a. Introduction to Continuous Distributions | Intuition about PDF | |||
| Lecture 11b. Continuous Uniform Distribution | |||
| Lecture 11c. Normal Distribution | |||
| Lecture 11d. Normal Distribution - 2 | |||
| Lecture 11E. Exponential Distribution | |||
| Lecture 11 Annotated Notes | |||
| Lecture 12. Statistics - Mean Mode Median | |||
| Lecture 12 Annotated Notes | |||
| LIVE Practice Questions on Linear Dependent Vectors and Solutions of Ax = b | |||
| Calculus (GATE 2025) | |||
| Lecture 1: Finding Limit of a function | |||
| Annotated Notes Lecture 1 Limits and Indeterminant Form | |||
| Lecture 2: Methods to Evaluate the Limit of a function | |||
| Annotated Notes Lecture 2 Evaluating Limits | |||
| Lecture 3: Limits L'Hôpital's rule and Other Indeterminate forms of powers | |||
| Annotated Notes Lecture 3 L hopital rule and Evaluating Power forms in Indeterminate form | |||
| Homework Limit Calculus GATE CSE PYQs | |||
| Lecture 4: Continuity and Introduction to Differentiability | |||
| Annotated Notes Lecture 4 Continuity and Differentiability | |||
| Lecture 5: Maxima and Minima | |||
| Lecture 6: Integration | |||
| Annotated Notes Lecture 6 Integration | |||
| Calculus (Old Videos) | |||
| About this series | |||
| Limits in Calculus | Calculus | Engineering Mathematics | GATE | GO Classes | GATE Overflow | |||
| Continuity in Calculus | Calculus | Engineering Mathematics | GATE | GO Classes | GATE Overflow | |||
| Differentiability in Calculus | Calculus | Engineering Mathematics | GATE | GO Classes | |||
| Maxima Minima in Calculus | Calculus | Engineering Mathematics | GATE | GO Classes | |||
| Intermediate Value Theorem | Calculus | Engineering Mathematics | GATE Computer Science | |||
| Rolle's Theorem and Examples | Calculus | Engineering Mathematics | GATE Computer Science | |||
| Integration with ALL GATE PYQs | Tic Tac Toe method | Engineering Mathematics | GO Classes | |||
| Limits Annotated Notes | |||
| Continuity Annotated Notes | |||
| Differentiability Annotated Notes | |||
| Maxima and Minima Annotated Notes | |||
| Intermediate Value Theorems Annotated Notes | |||
| Annotated Notes Rolle theorem | |||
| Integration Annotated Notes | |||
| LIVE Session 1: Limit and Continuity | |||
| LIVE Session 1 Annotated Notes | |||
| LIVE Session 2: Differentiability | |||
| LIVE Session 2 Annotated Notes | |||
| LIVE Session 3: Double Derivative and Mean Value Theorems | |||
| LIVE Session 3 Annotated Notes | |||
| LIVE Session 4: Integration | |||
| LIVE Session 4 Annotated Notes | |||
| Calculus Quiz - Weekly Quiz 14 | |||
| Weekly Quiz 14 - Calculus | |||
| Annotated Notes - Calculus Quiz Discussion | |||
| Students' Hand Written Notes | |||
| Notes by Quantum City (AIR 107, GATE CS 2024, Shreyas Rathod) - Engineering Mathematics Notes | |||
| Linear Algebra Notes - by Aditya | |||
| Probability Notes - by Aditya | |||
| Handwritten Notes by Karan Agrawal (AIR 102 GATE CS 2024) - Linear Algebra | |||
| Handwritten Notes by Karan Agrawal (AIR 102 GATE CS 2024) - Probability | |||
| Handwritten Notes - Harshit Srivastava(AIR 168 GATE CSE & AIR 96 DA 2025) | |||
| 1.0 Linear Algebra I | |||
| 2.0 Probability | |||
| Limits | |||
| 3.0 Calculus | |||
| Linear Algebra(Himanshu Dutta - AIR 16 GATE 2024) | |||
| Probability((Himanshu Dutta - AIR 16 GATE 2024) | |||
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