Math for Data Science and Machine Learning

Learn math for data science, machine learning, linear algebra, calculus, probability theory, discrete Math, Statistics.

3.65 (91 reviews)
Udemy
platform
English
language
Engineering
category
instructor
Math for Data Science and Machine Learning
14,818
students
6.5 hours
content
Aug 2022
last update
$19.99
regular price

What you will learn

Introduction to matrix

Gauss's elimination method

Properties of matrix and determinants

Echelon and reduce echelon form

Vector spaces

Linearly dependent and independent set of vectors in vector spaces

Basis of a vector space

linear transformation and related example and exercises

Inner product spaces

Eigen values and eigen vectors

Introduction to ODE's and PDE's

Probability and statistics

What is a sample space?

Mean, median and mode for grouped and ungrouped data

Poison, gamma and uniform distributions

And many more probability and statistics related tutorials

Gram's Schmidt orthonormal process

Pi chart, bar graph, line graph and histogram

Permutations and Combinations

Sets and Venn Diagram

Why take this course?

  • < Step-by-step explanation of more than 6.5 hours of video lessons on Math for Data Science and Machine Learning>

  • <Instant reply to your questions asked during lessons>

  • <Weekly live talks on Math for Data Science and Machine Learning. You can raise your questions in a live session as well>

  • <Helping materials like notes, examples, and exercises>

  • <Solution of quizzes and assignments>

In this course, we will learn math for data science and machine learning. We will also discuss the importance of Math for data science and machine learning in practical words. Moreover, Math for data science and machine learning course is a bundle of two courses in linear algebra and probability and statistics. So, students will learn the complete contents of probability and statistics and linear algebra. It is not like you will not complete all the contents in this 7 hours video course. This is a beautiful course and I have designed this course according to the need of the students.

WHERE THIS COURSE IS APPLICABLE?

Linear algebra and probability and statistics are usually offered for students of data science, machine learning, python, and IT students. So, that's why I have prepared this dual course for different sciences.

METHODOLOGY

I have taught this course multiple times in my university classes. It is offered usually in two different modes like it is offered as linear algebra for 100 marks paper and probability and statistics as another 100 marks paper for two different or in the same semesters. I usually focus on the method and examples while teaching this course. Examples clear the concepts of the students in a variety of ways, they can understand the main idea that the instructor wants to deliver if they feel typical the method of the subject or topics. So, focusing on examples makes the course easy and understandable for the students.

2 IN 1 STUFF

Many instructors (not kidding anyone but it is reality) put the 30 + hours just on one topic like linear algebra, which I think is useless. Students don't have the time to see the huge videos. So, that's why I am giving the two kinds of stuff in one stuff (2 in 1), linear algebra and probability and statistics. The complete course is very highly recognized and all the videos are high-definition videos.

LINEAR ALGEBRA SECTIONS INCLUDE

In linear algebra, the students will master the concepts of matrix and determinant, solution of nonlinear equations by different methods, vector spaces, linearly dependent and independent sets of vectors, linear transformation, and Gram's Schmidt normalization process.

PROBABILITY AND STATISTICS SECTIONS INCLUDE

While in Probability and Statistics, the students will learn sample spaces, distributions, mean, median, mode, and range. They will also learn the other contents of probability and statistics in a detailed way. 

THE COMPLETE DETAIL OF THE CONTENTS

To see the complete contents, please visits the contents sections of this course. The videos are relatively long videos that start from 10 minutes and end in 50 minutes. And the course has been designed on PowerPoint slides. All the concepts have been illustrated with the mouse cursor on the slides. Just follow the voice-over and the mouse cursor to understand the concepts.


Screenshots

Math for Data Science and Machine Learning - Screenshot_01Math for Data Science and Machine Learning - Screenshot_02Math for Data Science and Machine Learning - Screenshot_03Math for Data Science and Machine Learning - Screenshot_04

Reviews

Anirban
April 9, 2022
All the concepts not cleared. On the screen lot of things appeared but some of the things got skipped from your end.
Farhaan
June 23, 2021
Some things are not mentioned in the course for eg. Instructor never tells us What is conjugate of matrice. Some times the what is being displayed on screen is contrary to what the instructor is saying. This is making the video confusing to understand
Abhishek
June 15, 2021
very good, but little audio problem in the video, i had to use skull candy wireless & jbl bt to listen to your teachings Guru JI. can u suggest some fix ? Thank u Guru ji, aap bachpan se maths teacher hote toh aaj mein doctor hota. aap bahut acha padhate ho guru ji. Namastey Guru JI.
Steven
November 20, 2020
I have taken many courses from Dr. Chauhdry and continue to be very pleased. If you want complex content made easy, he is your instructor. If you want glitz and fancy graphics, maybe not. However, since I am an elderly gentleman with a thirst for Data Science and a holder of advanced degrees in Mathematics and Statistics as well as certificates of completion in Data Science, I am not looking for glitz but content. Also, I taught at the university level in the 1970's where there was just a blank chalkboard and a piece of chalk. I remember for Christmas one year my wife got me a fancy chalk holder. That was glitz. I was a mathematician teaching at a school that prided itself on its Engineering School. We were able to teach students with chalk and a board to engineer many useful and lasting structures for mankind. Dr. Chauhdry continues to be my go-to instructor for advanced mathematics. This course is very simple review for me, but since I had purchased it I wanted to give it a run through to refresh as I am concurrently taking a couple of deep-dive linear algebra courses in preparation for a much serious study of ML and AI.
Adson
April 5, 2020
I highly recommend the course! Sereral important topics in machine learning, thought with great clarity.

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2722350
udemy ID
12/26/2019
course created date
2/7/2020
course indexed date
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