Udemy
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  •  
Development
Web Development Data Science Mobile Development Programming Languages Game Development Database Design & Development Software Testing Software Engineering Development Tools No-Code Development
Business
Entrepreneurship Communications Management Sales Business Strategy Operations Project Management Business Law Business Analytics & Intelligence Human Resources Industry E-Commerce Media Real Estate Other Business
Finance & Accounting
Accounting & Bookkeeping Compliance Cryptocurrency & Blockchain Economics Finance Finance Cert & Exam Prep Financial Modeling & Analysis Investing & Trading Money Management Tools Taxes Other Finance & Accounting
IT & Software
IT Certification Network & Security Hardware Operating Systems Other IT & Software
Office Productivity
Microsoft Apple Google SAP Oracle Other Office Productivity
Personal Development
Personal Transformation Personal Productivity Leadership Career Development Parenting & Relationships Happiness Esoteric Practices Religion & Spirituality Personal Brand Building Creativity Influence Self Esteem & Confidence Stress Management Memory & Study Skills Motivation Other Personal Development
Design
Web Design Graphic Design & Illustration Design Tools User Experience Design Game Design Design Thinking 3D & Animation Fashion Design Architectural Design Interior Design Other Design
Marketing
Digital Marketing Search Engine Optimization Social Media Marketing Branding Marketing Fundamentals Marketing Analytics & Automation Public Relations Advertising Video & Mobile Marketing Content Marketing Growth Hacking Affiliate Marketing Product Marketing Other Marketing
Lifestyle
Arts & Crafts Beauty & Makeup Esoteric Practices Food & Beverage Gaming Home Improvement Pet Care & Training Travel Other Lifestyle
Photography & Video
Digital Photography Photography Portrait Photography Photography Tools Commercial Photography Video Design Other Photography & Video
Health & Fitness
Fitness General Health Sports Nutrition Yoga Mental Health Dieting Self Defense Safety & First Aid Dance Meditation Other Health & Fitness
Music
Instruments Music Production Music Fundamentals Vocal Music Techniques Music Software Other Music
Teaching & Academics
Engineering Humanities Math Science Online Education Social Science Language Teacher Training Test Prep Other Teaching & Academics
AWS Certification Microsoft Certification AWS Certified Solutions Architect - Associate AWS Certified Cloud Practitioner CompTIA A+ Cisco CCNA Amazon AWS CompTIA Security+ AWS Certified Developer - Associate
Graphic Design Photoshop Adobe Illustrator Drawing Digital Painting InDesign Character Design Canva Figure Drawing
Life Coach Training Neuro-Linguistic Programming Mindfulness Personal Development Meditation Personal Transformation Life Purpose Emotional Intelligence CBT
Web Development JavaScript React CSS Angular PHP WordPress Node.Js Python
Google Flutter Android Development iOS Development Swift React Native Dart Programming Language Mobile Development Kotlin SwiftUI
Digital Marketing Google Ads (Adwords) Social Media Marketing Google Ads (AdWords) Certification Marketing Strategy Internet Marketing YouTube Marketing Email Marketing Retargeting
Microsoft Power BI SQL Tableau Business Analysis Business Intelligence MySQL Data Analysis Data Modeling Data Science
Business Fundamentals Entrepreneurship Fundamentals Business Strategy Online Business Business Plan Startup Freelancing Blogging Home Business
Unity Game Development Fundamentals Unreal Engine C# 3D Game Development C++ 2D Game Development Unreal Engine Blueprints Blender
30-Day Money-Back Guarantee
Teaching & Academics Engineering Statistics

Master Complete Statistics For Computer Science - I

Course In Probability & Statistics Important For Machine Learning, Artificial Intelligence, Data Science, Neural Network
Rating: 4.2 out of 54.2 (86 ratings)
32,032 students
Created by Shilank Singh
Last updated 9/2020
English
30-Day Money-Back Guarantee

What you'll 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

Requirements

  • Knowledge of Applied Probability
  • Knowledge of Calculus

Description

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

Who this course is for:

  • Current Probability and Statistics students
  • Students of Machine Learning, Artificial Intelligence, Data Science, Computer Science, Electrical Engineering , as Statistics is the prerequisite course to Machine Learning, Data Science, Computer Science and Electrical Engineering
  • Anyone who wants to study Statistics for fun after being away from school for a while.

Course content

25 sections • 156 lectures • 21h 20m total length

  • Preview02:38
  • Preview06:35
  • Preview09:24

  • Discrete Random Variables - Concept
    03:20
  • Discrete Random Variables - Solved Example 1 and 2
    09:56
  • Discrete Random Variables - Solved Example 3
    06:05
  • Discrete Random Variables - Solved Example 4
    09:16
  • Discrete Random Variables - Solved Example 5
    09:05

  • Continuous Random Variables - Concept
    05:37
  • Continuous Random Variables - Solved Example 1 and 2
    11:49
  • Continuous Random Variables - Solved Example 3
    09:08
  • Continuous Random Variables - Solved Example 4
    04:30
  • Continuous Random Variables - Solved Example 5
    09:00
  • Continuous Random Variables - Solved Example 6
    05:00
  • Continuous Random Variables - Solved Example 7
    06:56
  • Continuous Random Variables - Solved Example 8
    06:56

  • Cumulative Distribution Function - Concept
    02:43
  • Cumulative Distribution Function - Solved Example 1
    08:02
  • Cumulative Distribution Function - Solved Example 2
    06:16
  • Cumulative Distribution Function - Solved Example 3
    03:57
  • Cumulative Distribution Function - Solved Example 4
    08:26
  • Cumulative Distribution Function - Solved Example 5
    03:47
  • Cumulative Distribution Function - Solved Example 6
    13:28

  • Special Discrete Distribution
    02:45
  • Special Continuous Distribution
    04:47
  • Special Distribution - Solved Example 1
    08:30
  • Special Distribution - Solved Example 2
    05:49

  • Two - Dimensional Random Variables - Concept
    06:27
  • Cumulative Distribution Function - Concept
    03:23
  • Marginal Probability Distribution - Concept
    05:38
  • Conditional Probability Distribution - Concept
    06:14
  • Two - Dimensional Random Variables - Solved Example 1
    11:01
  • Two - Dimensional Random Variables - Solved Example 2
    09:56
  • Two - Dimensional Random Variables - Solved Example 3
    20:45
  • Two - Dimensional Random Variables - Solved Example 4
    08:26
  • Two - Dimensional Random Variables - Solved Example 5
    16:46
  • Two - Dimensional Random Variables - Solved Example 6
    06:14
  • Two - Dimensional Random Variables - Solved Example 7
    09:08
  • Two - Dimensional Random Variables - Solved Example 8
    07:57
  • Two - Dimensional Random Variables - Solved Example 9
    11:23
  • Two - Dimensional Random Variables - Solved Example 10
    14:56
  • Two - Dimensional Random Variables - Solved Example 11
    03:07

  • Random Vectors - Concept
    05:55

  • Function of One Random Variable - Concept
    10:06
  • Function of One Random Variable - Solved Example 1 and 2
    08:41
  • Function of One Random Variable - Solved Example 3
    07:21
  • Function of One Random Variable - Solved Example 4 and 5
    07:40
  • Function of One Random Variable - Solved Example 6
    06:49
  • Function of One Random Variable - Solved Example 7
    09:39
  • Function of One Random Variable - Solved Example 8 and 9
    07:38
  • Function of One Random Variable - Solved Example 10
    06:26
  • Function of One Random Variable - Solved Example 11
    06:02
  • Function of One Random Variable - Solved Example 12
    08:08
  • Function of One Random Variable - Solved Example 13
    05:34
  • Function of One Random Variable - Solved Example 14
    10:13

  • One Function of Two Random Variables - Result 1, Solved Example 1
    07:53
  • One Function of Two Random Variables - Result 1, Solved Example 2
    03:28
  • One Function of Two Random Variables - Result 1, Solved Example 3
    09:49
  • One Function of Two Random Variables - Result 2, Solved Example 1
    05:18
  • One Function of Two Random Variables - Result 3, Solved Example 1
    07:11

  • Two Functions of Two Random Variables - Concept, Solved Example 1
    14:51
  • Two Functions of Two Random Variables - Solved Example 2
    07:52
  • Two Functions of Two Random Variables - Solved Example 3
    06:19
  • Two Functions of Two Random Variables - Solved Example 4
    07:07
  • Two Functions of Two Random Variables - Solved Example 5
    08:57
  • Two Functions of Two Random Variables - Solved Example 6
    08:11

Instructor

Shilank Singh
Maths & Stats Tutor
Shilank Singh
  • 4.0 Instructor Rating
  • 179 Reviews
  • 43,611 Students
  • 5 Courses

Hello students, I am Shilank Singh. I was born and raised in Mumbai, India. My interest in maths developed at an early age when I started attending pre-school. I attended Indian Institute of Technology, Delhi and post graduated in 2013 with a degree M.Sc. in Mathematics. In the fall of 2013, I was hired to teach Engineering Mathematics at Mumbai University and I have taught there for three years. Currently, I live in New Delhi and work as a Maths and Statistics Tutor over here since January, 2017.

  • Udemy for Business
  • Teach on Udemy
  • Get the app
  • About us
  • Contact us
  • Careers
  • Blog
  • Help and Support
  • Affiliate
  • Impressum Kontakt
  • Terms
  • Privacy policy
  • Cookie settings
  • Sitemap
  • Featured courses
Udemy
© 2021 Udemy, Inc.