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📐 Welcome to the Mathematics for Data Science Complete Course for Beginners in Urdu/Hindi! 🎓 This course is a one-stop solution for anyone looking to understand the essential mathematics needed for data science, all explained in simple, easy-to-understand language. From basic concepts to advanced mathematical tools used in data analysis, machine learning, and AI, this video covers it all in-depth. Perfect for beginners in data science, programming, and anyone interested in building a solid mathematical foundation for tech careers! 🧮 Course Chapters: We cover a wide range of topics, ensuring you understand each concept thoroughly with practical examples: Introduction to Mathematics and Number Theory Modular Arithmetic and Algebra Basics Linear Algebra Essentials: Vectors, matrices, transformations Advanced Topics: Gaussian elimination, eigenvalues, eigenvectors, LU decomposition, SVD, and Python applications for data science. 🌟 Why This Course? Structured Learning: This course provides a clear, chapter-by-chapter breakdown of key mathematical concepts for data science. Hands-on Python Examples: Learn to apply linear algebra and system-solving techniques directly in Python. Concepts in Urdu/Hindi: Delivered in a language you’re comfortable with, making learning easier and more effective. This course covers critical mathematical tools that data scientists, AI practitioners, and machine learning enthusiasts use to tackle complex real-world problems. So get ready to master the math behind data science and take your skills to the next level! Chapters: 00:00:00 What is Mathematics? 00:20:49 Branches of Mathematics 00:38:24 Number Theory 01:04:53 What did you learn? 01:05:41 Number Theory in Details 01:12:56 Application of Number Theory 01:26:11 Pros. of Number Theory 01:34:57 Factors and Multiples 01:44:04 Divisibility Rules 01:58:18 GCD and LCM 02:05:33 Modular Arithmetic 02:19:52 Modulus 02:20:27 Types of Numbers 02:35:33 What is Algebra? 02:49:56 Importance of Algebra 02:52:34 How to learn Algebra? 02:55:38 Types of Algebra 03:05:59 History of Algebra 03:12:32 Algebra and Data Science 03:23:57 Pre-algebra Introduction 03:32:13 Basics of Pre-algebra 03:43:34 Fractions and Decimals I 03:59:45 Fractions and Decimals II 04:12:01 Ratios and Proportions 04:27:20 Percentages 04:46:52 Solving Equations 05:02:53 Units and Geometry 05:12:23 Data Analysis Basics in Pre-algebra 05:18:09 Problem Solving in pre-algebra 05:22:00 Exercises for Pre-algebra 05:24:46 Elementary Algebra 05:33:49 Mathematics Playlist an additional resource 05:38:51 Tasks for Linear Algebra 05:40:58 Vector 06:02:42 Matrices in Machine Learning 06:12:25 Next Tasks assignment 06:15:15 Linear Algebra Introduction 06:21:33 Cartesian coordinates 06:31:57 Unit Vectors 06:39:56 Scalars and Scaling Vector 06:45:09 Vector Addition 06:54:44 Vector Spans and Linear Dependence 07:12:31 x and y intercepts 07:33:37 Dot product of vectors 07:38:37 cross product of vectors 07:48:14 Vector spaces 07:52:56 Vector Transformation 08:16:30 Linear Transformation and matrices 08:40:38 Matrices 08:47:30 Shear transformation 08:56:12 Why do we need transformations? 08:59:22 Matrix multiplication and composition 09:16:55 Matrix and Types 09:23:36 Other types of Matrices 09:33:51 Addition and Subtraction of Matrices 09:37:12 Multiplication of Matrices 09:42:40 Multiplication is important to learn 09:43:43 Determinant of Matrix 09:53:59 Inverse of a Matrix 10:17:09 System of Equations 10:25:45 Types of linear equations 10:29:47 How to represent System of Equations 10:48:25 Matrix form for system of equations 10:59:42 Assignment Alert 11:01:38 Solving system of equations 11:07:27 Graphical Method of solving equations 11:31:21 Substitution method of solving equations 11:45:24 Elimination method of solving equations 11:54:46 Matrix Inversion method of solving equations 12:05:33 Advance methods of solving equations 12:21:58 Assignment Alert 12:23:09 System of Equations and advance methods 12:25:59 Gaussian Elimination Method I 12:52:05 Gaussian Elimination Method II 13:00:52 Gaus Jordan Elimination Method 13:09:09 LU Decomposition Method 13:20:16 Singular Value Decomposition 13:59:06 Gaussian Elimination method and Row Operations 14:04:04 Eigenvalues and Eigenvectors 14:20:20 Singular Value Decomposition in Python 14:30:58 Linear Algebra Notes 14:36:39 Solving System of Equations in Python 14:45:10 Solving System of Complex Equations in Python 14:50:12 Draw a vector in Python 14:54:49 Linear Transformation on vectors in 2D 15:02:02 Shear Transformation in Python 15:06:05 SVD in python 15:15:03 Learn Python from this course 15:15:41 Register for Python ka Chilla Latest Course
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