Math for Data science,Data analysis and Machine Learning

Overview

In this course, we will learn Math essentials for Data science,Data analysis and Machine Learning. We will also discuss the importance of Linear Algebra,Statistics and Probability,Calculus and Geometry in these technological areas.

Since data science is studied by both the engineers and commerce students ,this course is designed in such a way that it is useful for both beginners as well as for advanced level. The lessons of the course is also beneficial for the students of Computer science /artificial intelligence and those learning Python programming.

Syllabus

• Introduction to Mathematics for Data Science
Overview of Data Science, Data Analysis, and Machine Learning
Importance of Mathematics in Technological Fields
• Linear Algebra
Vectors and Matrices
Matrix Operations
Eigenvalues and Eigenvectors
Applications in Data Science
• Statistics and Probability
Descriptive Statistics: Mean, Median, Mode
Inferential Statistics: Hypothesis Testing, Confidence Intervals
Probability Fundamentals
Probability Distributions: Normal, Binomial, Poisson
Bayesian Statistics and Applications
• Calculus
Limits and Continuity
Derivatives and their Applications
Integrals and their Applications
Multivariable Calculus and Partial Derivatives
Optimization in Machine Learning
• Geometry
Coordinate Systems
Geometric Transformations
Distance Metrics and their Role in Machine Learning
• Advanced Topics
Principal Component Analysis (PCA) for Dimensionality Reduction
Singular Value Decomposition (SVD)
Introduction to Mathematical Optimization Techniques
• Python for Math and Data Science
Basic Python for Data Analysis
Using Libraries: Numpy, Pandas, Matplotlib
Implementing Mathematical Concepts using Python
• Conclusion
Synthesis of Mathematical Tools in Data Science
Future Directions and Advanced Learning Paths
• Practical Applications and Projects
Projects exploring real-world applications
Data set analysis using mathematical techniques

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Taught by

Sandeep Kumar Mathur

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Subjects

Data Science