Master Complete Statistics For Computer Science - I

Course In Probability & Statistics Important For Machine Learning, Artificial Intelligence, Data Science, Neural Network

3.80 (259 reviews)

Udemy

platform

English

language

Engineering

What you will learn

Random Variables

Discrete Random Variables and its Probability Mass Function

Continuous Random Variables and its Probability Density Function

Cumulative Distribution Function and its properties and application

Special Distribution

Two - Dimensional Random Variables

Marginal Probability Distribution

Conditional Probability Distribution

Independent Random Variables

Function of One Random Variable

One Function of Two Random Variables

Two Functions of Two Random Variables

Statistical Averages

Measures of Central Tendency (Mean, Median, Mode, Geometric Mean and Harmonic Mean)

Mathematical Expectations and Moments

Measures of Dispersion (Quartile Deviation, Mean Deviation, Standard Deviation and Variance)

Skewness and Kurtosis

Expected Values of Two-Dimensional Random Variables

Linear Correlation

Correlation Coefficient and its properties

Rank Correlation Coefficient

Linear Regression

Equations of the Lines of Regression

Standard Error of Estimate of Y on X and of X on Y

Characteristic Function and Moment Generating Function

Bounds on Probabilities

Why take this course?

In today’s engineering curriculum, topics on probability and statistics play a major role, as the statistical methods are very helpful in analyzing the data and interpreting the results.

When an aspiring engineering student takes up a project or research work, statistical methods become very handy.

Hence, the use of a well-structured course on probability and statistics in the curriculum will help students understand the concept in depth, in addition to preparing for examinations such as for regular courses or entry-level exams for postgraduate courses.

In order to cater the needs of the engineering students, content of this course, are well designed. In this course, all the sections are well organized and presented in an order as the contents progress from basics to higher level of statistics.

As a result, this course is, in fact, student friendly, as I have tried to explain all the concepts with suitable examples before solving problems.

This 150+ lecture course includes video explanations of everything from Random Variables, Probability Distribution, Statistical Averages, Correlation, Regression, Characteristic Function, Moment Generating Function and Bounds on Probability, and it includes more than 90+ examples (with detailed solutions) to help you test your understanding along the way. "Master Complete Statistics For Computer Science - I" is organized into the following sections:

Introduction
Discrete Random Variables
Continuous Random Variables
Cumulative Distribution Function
Special Distribution
Two - Dimensional Random Variables
Random Vectors
Function of One Random Variable
One Function of Two Random Variables
Two Functions of Two Random Variables
Measures of Central Tendency
Mathematical Expectations and Moments
Measures of Dispersion
Skewness and Kurtosis
Statistical Averages - Solved Examples
Expected Values of a Two-Dimensional Random Variables
Linear Correlation
Correlation Coefficient
Properties of Correlation Coefficient
Rank Correlation Coefficient
Linear Regression
Equations of the Lines of Regression
Standard Error of Estimate of Y on X and of X on Y
Characteristic Function and Moment Generating Function
Bounds on Probabilities

Reviews

Stefano

June 30, 2023

A course entirely for scholars. Good series of examples copied by the usual academic exercises but few practical and realistic examples on each topic explained. Many probability distributions treated without focusing on their use, what they represent, at least some graphics and table (non -existent here) and where these distributions are more in nature, in the science, in the field of engineering. A long and flat course, demonstrations of what has already been shown. Often boring reading of all the steps, not to mention the reading of the tables, cell cell ... ridiculous. A few more colorful slides would improve things and make the course more captivating. The images are worth much more than a thousand words. Now, what do I do with all these beautiful formulas? By the way, hundreds of slides who have to download individually ... but are we really practical and serious?

Yahaya

June 25, 2023

The course is one of best courses for anyone who wants to study computer science and machine learning. Thank you very much.

Dua

June 18, 2023

this course helps a lot in my studies it clears my concept and gives me better understanding of the subject

Chris

March 25, 2023

This course is just slide after slide after slide with the Instructor reading. The audio quality and the slide quality varies. Students don't seem very involved - 3 posts in the Q/A after several years and that's all. The second lecture goes through how to enrol in the course and the Coupon etc which seems strange as to see the lecture I am already on the course! This course - as is stated - is not for beginners, which is fine - it is just all very dry.

Michele

November 22, 2022

He just reads from slides and doesnt actually explain anything he does. Also he expects that everyone can read his strange notations and doesn't even explain what those notations mean. really disappointed

Abdalla

September 10, 2021

I think it is a little bit complicated, and I’m in the beginning of the course who knows in the end of the course my opinion will change

Oluwamayowa

September 17, 2020

Yes, it was wonderful, its been long I left this course, wow! Thanks for this course. I wish I had join this class since, but this nice, the examples are sufficiently satisfactory.

Jill

August 9, 2020

It is discouraging that the class is simply reading the material on the screen, rather than explaining it. I might as well just fast forward to the end of each section and read the screen and not waste the time having it read to me. Hopefully this is not the case throughout the whole course.

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