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What you will learn

☑ SQL - MySQL for Data science.

☑ Write complex SQL queries across multiple tables.

☑ Relational databases versus non relational databases.

☑ Learn how to code in SQL

☑ Sampling distribution with practical simulation apps and answering of important technical questions.

☑ Confidence level and Confidence interval.

☑ Distinguish and work with different types of distributions .

☑ Inferential and Descriptive statistics with collection of important quizzes and examples .

☑ One sample mean t test .

☑ Two sample means t test .

☑ How to calculate P value using manual and direct method ?

☑ What is after data analysis ?

☑ Null hypothesis and alternative hypothesis .

☑ Understand What is P value ?

☑ Data types and Why we need to study data types ?

☑ What is Type one error ?

☑ Relationship between Type one error and Alpha ( non confident probability )

☑ Is Normal distribution and t distributions are cousins ?

☑ Projects like Estimation of goals in premier league ( using confidence interval ) , and more .. and more to learn it

☑ What is "double edged sword of statistics" ?

☑ Practical significance versus statistical significance , and more and more to learn it

Description

** 300+ Lectures/Articles** lectures include

Enjoy practice 25 Apps/Projects in SQL - MySQL for data

This is the Complete 2021 Bootcamp , Two courses in ONE COURSE .

Do you like jobs in MySQL for data science ?

Do you like jobs in Machine learning ?

Do you like jobs in Marketing analyst ?

Do you like jobs in Programming for data science ?

Do you like jobs in Business analysis and business intelligence ?

*If the answer is yes , then all of the above needs MySQL and Statistics for data science .*

**Who prepared this course material ? **

This course material is prepared from highly experienced engineers worked in a leader companies like Microsoft , Facebook and google .

*After hard working from five months ago we created 300+ Lectures/Articles to cover everything related to SQL - MySQL & statistics for data science . *

In no time with simple and easy way you will learn and *love SQL for data science and statistics .*

We stress in this course to make it **very spontaneous to make all students love SQL and statistics for data science . **

**Who's teaching you in this course ?**

I'm senior developer and chief data science engineer . i worked for many projects related to expert systems and artificial intelligence .*Also i worked as Tutor and consultant trainer with a leader international companies located in USA and UK .*

I spent over five months of hard working to create ** 300+ Lectures/Articles in super high quality **to make all

I'm sharing a lot of practical experience

Why learn MySQL or SQL ?

MySQL is a popular database platform for businesses because it is extremely easy to use. It is commonly used in combination with web development and data science . You hear “it’s easy to work with” a lot in relation to computer languages, but MySQL truly is simple.

For instance, someone with little to no knowledge of MySQL can easily establish a database .

Of course, a lot of hosting providers make this process even simpler by handling all the necessary tasks for new website administrators, but it doesn’t detract from the point that MySQL is relatively easy to use.

I could not imagine data science without databases .

*What is my final goal after my students enroll in this course ? *

My final goal is to make all students and engineers love *SQL for data science and statistics .*

My big challenge in this course is to make it professional course at the same time it should be very easy and simple for all People .

Therefore you will notice that i used a lot of graphics and imaginary ideas to make you **LOVE SQL for data science and statistics **

**So, what are you waiting for? Click the “Take this course” button, and let’s begin this journey together!**

**What is course contents ? **

Starting introduction to data science and data analysis .

Understand programming basics for data science

learn SQL - MySQL basics .

Write all the

**SQL joins**Create Foreign key and primary key in MySQL databases .

Learn how to start and stop MySQL server .

Analyze data using

**Aggregate Functions .**Read and import external CSV files into MySQL database .

Export MySQL database table contents into CSV file .

Awesome Projects and examples like :How Mr. Genie helped us to find all fishes in the sea ?

Mr. Genie power versus statistics power

The double edged sword of statistics

Help fisherman to catch Tuna using sampling distribution

Ice Cola example with student's t distribution .

Estimation of goals in premier league ( using confidence interval ) .

TAKE YOUR BREATH BEFORE HYPOTHESIS TESTING

One sample mean t test .

Two sample mean t test .

Null hypothesis and alternative hypothesis .

What is P value ?

How to calculate P value using manual and direct method ?

Two mini stories for

**TWO PROJECTS**related to hypothesis testingProject one is how Sarah used "one sample mean t test" for Ice Cola factory to prove that her brother Ibrahim is innocent ?

Project two how Sarah used "two sample mean t test" for Ice Cola factory to help her brother Ibrahim to increase Ice Cola sales in winter ?

... more and more

.... and more and more course contents

#SQL #MySQL #MySQL-for-data-science #SQL-for-Data-science

Screenshots

Content

--------- Data Analysis Part 1 - Getting Started ------

Data analysis videos samples of course contents

Data Analysis Techniques - Please READ ME FIRST and slides used in this content

Data Analysis Methods - Introduction about data analysis and overview

Is programming for data science easy or hard ?

What is the main concept of data analysis ?

Machine learning should be after practical statistics

General overview about what will you learn in data science courses

Collection about important questions related to data science

Be patient for interview questions

People are panic from robot jobs

Data Analytics - Careers and robot jobs

Slides and material used in this content

Important questions about Robot jobs and my career

High demand for hiring data analysis engineer

Example about robot jobs

Robot jobs will create new jobs for you because it is a friend

It is not easy to hire data science engineer

Why do you think that learning programming is Barrier in data analysis ?

Applied Data Science - Startup point of programming

Slides and material used in this content

Collection of important questions related to programming

Should i learn programming like professional ?

Where is my start up point to learn programming ?

R language not for software developers

Programming in data analysis uses simple and easy language

Review about our questions related to programming

What is our example in programming ?

Statistics for data analysis - Example about programming and big data

Important introduction about SQL example

Run your first SQL command without any previous experience

Note the difference between SQL and English language

Python with sample activity

Review about Python and SQL in data analysis

What is big data ?

Professional answer about what is big data ?

What is OVERLOADS in a big data ?

Variety in big data

What is velocity in big data ?

Big data is something made overloads

What is after data analysis ?

Slides and material used in this content

Introduction with important questions ?

Difference between data analytics and data science

What is after data analysis ?

What is professional people in data analysis care ?

Your data is your treasure

-------- Part 2 : Descriptive statistics --------

Slides and material used in this content

Our strategy to learn practical statistics

Four main things in practical statistics

Comparison between inferential ans descriptive statistics

Slides and material used in this content

Simplified viewpoint about descriptive and inferential statistics

Data before and after descriptive statistics

Conclusions between inferential and descriptive statistics

Population and sample in inferential statistics

Simplified viewpoint about inferential statistics data

FAQ about descriptive statistics

Slides and material used in this content

What will we learn in descriptive statistics ?

Statistics between Lie and trustworthy

Waitress should be friendly or friendlier ?

Data types

Slides and material used in this content

Introduction about data types

the benefit of data types

Categorical data types

Data types ( continuous vs discrete )

Difference between numerical and categorical data

Quizzes and examples about data types

The summary about data types

Center of numerical data

Slides and material used in this content

introduction about data center

Characteristics of numerical data

Categorical data characteristics considered to be limited

Example about characteristics of categorical data

What are measures of center ?

Examples of mean

Examples of median

Examples of mode

I'm confused between mean , median and mode

Why center of the data is very important ?

Slides and material used in this content

introduction about a lot of ways to find center of the data

Football coach focus on the middle point

The Fun with football goals to find center of the data

Why we need mode and median as well as mean ?

Final review about central tendency

Data dispersion and spread

Slides and material used in this content and the next content

Concepts and data dispersion and spread

Measures of spread

What is range ?

What is interquartile range ?

What is 5 number summary ?

Example about 5 number summary

5 number summary with range and interquartile range

Remember why we need 5 number summary ?

Box plot with 5 number summary

Which one is better ? Standard deviation or range ?

Concepts about standard deviation , range and 5 number summary

The idea about how to represent your data ?

Example about using graphs with 5 number summary

Benefits of using box plot with histogram

What is standard deviation ?

Example about standard deviation

Direct methods to calculate standard deviation

Physical meaning of standard deviation

a tricky question about standard deviation

Example about center of data and standard deviation

Standard deviation with financial analysis

Choose between standard deviation and range to measure data spread

Data shape

Slides and material used in this content

Introduction about data shape

Fast review about what we learned about data aspects

Important questions related to data shape

Symmetric versus skewed distribution

Example about symmetric distribution

What is Gaussian and bell curve distribution ?

Why normal distribution ?

Normal versus standard normal distribution

Left and right skewed distribution

Remember what we studied about data shape

Outlier

Slides and material used in this content

Introduction about outlier

Fast review about what we learned

What do we mean by outlier ?

What is our rule of thump to find outlier ?

Examples to find outlier

What can i do with outlier ?

What can i do if i removed outlier ?

What professional people do with outlier ?

Normal distribution lesson 1

Slides and material used in this content

Introduction about normal distribution

Four main things in data analysis

Simplified viewpoint about normal distribution

Why normal distribution called Gaussian or bell curve distribution ?

Why normal distribution is symmetric distribution ?

Difference between normal distribution and standard normal distribution

What is the benefit of Z table ?

There is an issue if you do not have standard normal distribution

Normal distribution lesson 2

Why we need to convert normal distribution to standard normal distribution ?

Examples about convert normal to standard normal

FAQ related to normal distribution

-------- Part 3: Inferential statistics -------

Slides and material used in this content

Introduction about sampling distribution

The difference between population parameters and sample statistics

Why we need sample statistics ?

Find the mean length of all fishes in the sea

Solution one : Mr. Genie will help you find the length of all fishes

Why we need Mr. Genie ?

What is our final distribution we get it from Mr. Genie ?

Mr. Genie has power to offer TRUE population parameters ( not estimation )

Solution two : sampling distribution instead of Mr. Genie

The idea of sampling distribution

Continue Sampling distribution

External link about simulation tool for Sampling distribution

Introduction about what will we learn

Overview about sampling distribution simulation tool parts

What is our final goal from this simulation tool ?

How to take a sample for all fishes in the sea ?

Let's start working with simulation tool

Comparison between population parameters and sampling distribution

The idea of central limit theorem

Summary about population parameters and sampling distribution estimators

Example : Help fisher man to catch Tuna fishes with length over 1 meter

How to find sampling mean in our example ?

Confidence interval and level first lesson

Slides and material used in this content and the next content

Introduction about the importance of confidence interval

What do we mean by "confidence" ?

Collection of important questions related to Confidence interval

Simplified viewpoint about confidence interval and confidence level

Difference between 99 and 95 confidence level

Important definitions about confidence interval in simulation tool

What is sample error ?

Start simulation of 95 confidence interval

What is success rate ?

What is failures ?

What is the difference between confidence level and success rate ?

What happens if we changed confidence level from 95 to 99 ?

Important tips and questions in this lesson

Confidence interval second lesson

Link to Simulation tool about Confidence interval

Introduction about using confidence interval in real life scenarios

Make a decision based on High width or low width confidence interval

Trade-off between useless information and high risk in confidence interval

What effects the width of confidence interval ?

Effect of standard deviation on confidence interval

Relationship between standard error and margin of error in confidence interval

Quick Review about what we learned in confidence interval

What do we mean by we are "lucky" or "not lucky" ?

Review about our answers in confidence interval

Student's t distribution

Slides and material used in this content

Introduction

Collection of important questions about t distribution

The history and the founder of student's t distribution

Why did we call t distribution by "student" ?

What did Mr. William tell us about his findings ?

Comparison between t distribution and normal distribution

degree of freedom with t distribution

What do we mean by degree of freedom ?

The benefit of degree of freedom with t distribution

What do you think if DF > 30 ?

t score and t table

Do not use t distribution for higher values of degree of freedom

Calculate t value directly using t calculator

Remember when to use t or z distribution ?

Summary about confidence interval with t and z distribution

Examples about confidence interval

Slides and material used in this content

Example 1 : Margin of error with confidence interval 99%

Repeat the same example with CL = 95%

What is the lower limit point of CL = 90% ?

Repeat the same example with sample standard deviation

Final results with t calculator

Premier league football scorers with confidence interval

Final results with t calculator

Two important equations for Z and T distributions

Use Excel to calculate confidence interval

Slides and material used in this content

Introduction about using Excel to find confidence interval

Step 1 : Make sure that Data analysis tool pack is installed in your Excel

Get all your results about confidence interval from one click only

Comparison between manual method results and excel sheet results

The end of Confidence interval and what is next ?

--- Part 4 : TAKE YOUR BREATH BEFORE HYPOTHESIS TESTING----

Slides and material used in this content

Introduction about hypothesis testing

Principles in hypothesis testing like H0 , H1 and P value

P value is the most important thing we should focus on it

Mini story part 1 to understand what is P value ?

Complaint against Cola factory owner

analysis with H0 and H1 about Cola drink to see if the complaint is a fake

Understand how to find H0 and H1 from Cola drinks

on what basis Ibrahim will be innocent or guilty ?

What happened to Ibrahim in the court ?

Ibrahim asked his sister Sarah to help him

What is Sarah's idea to save her brother Ibrahim ?

First results from Sarah about water percentage in Excel sheet

First trial from Sarah is not valid because we need strong evidence

Another trial from Sarah using P value to get evidence

Alpha and type one error

Comparing between Alpha and P value

Why Sarah is happy if P value greater than Alpha ?

P value with weak and strong evidence .

After Sarah is happy , remember what is P value ?

Sarah asked her brother about profit share from Cola sales

Questions about what we learned from mini story part 1 ?

Calculate P value manual method

Slides and material used in this content

Introduction and steps to calculate P value

Step 1 : Find H0 and H1

Step 2 : Find Sample Size , SD and mean of sample

Fast review about how to get sample mean and SD from Excel file

Step 3: Find Degree of freedom

Step 4 : Choose between t or z distribution

Step 5 : Calculate t or Z value

Step 6 : find P value from t calculator or t table

Step 7 : Make a decision

Use Excel to calculate P value

Slides and material used in this content

Prepare your excel sheet with sample results

Write your P value equation in Excel file

Make a decision by comparing Alpha and P value

Question about one and two tail

Mini story part 2 ( Two tailed t test )

Slides and material used in this content

For the second time Ibrahim asked his sister Sarah to help him

One tail versus two tail test

The summary about one tail and two tail test

Starting Mini story part 2

Ibrahim i seeking about increase Cola sales in winter

Sarah was surprised when Ibrahim asked her to increase sales in winter

Sarah told her brother about offer free coupons for Cola drinks

Sarah is using two samples mean t test to prove idea of free cola coupons

Important things we should understand it when calculate P value in Excel

What is null hypothesis for two samples mean t test ?

What is alternative hypothesis ?

Use Excel file with two samples mean t test

P value from t calculator versus P value from Excel

Ibrahim does not understand final results from Excel file

Examples about what we learned in hypothesis testing .

Simple practice about t distribution table with different confidence level

t value for one and two tail 95% and 90% confidence interval

Understanding two tail test results in Excel

Slides and material used in this content

Explain all results from Excel file about two samples mean t test

Important graph to tell us about our evidence strength

Ibrahim is happy now after he his sister explained excel file results

Ibrahim give Sarah some money to avoid disputes with her

Let's celebrate after practical and statistical significance

Slides and material used in this content

Choose between practical significance or statistical significance ?

Statistics is a liar or trustworthy ?

I will make you love statistics

Reviews

V

Vonn17 September 2020

I left with more questions and answers. I felt at times videos were split up for no reason. Things were explained quickly and the story for hypothesis testing was weird.

J

JKrajnak29 July 2020

It seemed much like a run-on-sentence, but the reason for so many examples was explained in the last video lecture as the Instructor's goals was to make learning Statistics enjoyable, and not just deal with textbook cutout problems which would probably make the analysis boring. It was a good general run-through of many statistical topics but not necessarily in order of connected relevant areas.

N

Naomi13 July 2020

the tutor answered all my questions in different lessons like data analysis and statistics for data analysis and some lessons in statistics for data science

T

Theodore21 June 2020

null hypothesis explanation is helpful and professional with excellent examples in statistics for data science

R

Robert19 June 2020

Unpolished diamond. Persevere. Concepts which I have found very difficult to understand despite studying for a while have been explained succinctly. I just had to overlook some of the dodgy dated graphics/presentation. Thank you for the content.

M

Md.13 February 2020

Though the content and examples are good for understanding statistics with deeply but repetition, introductory short video, and poor pronunciation of speech made me bored. However, Thank you.....

A

Agunbiade28 January 2020

Although i strain my ears a bit to hear the accent of the lecturer in the videos but i still get to understand it.

S

Smruti16 January 2020

This is a very good course. The instructor has worked very hard on the presentation and examples. I will recommend this course to students who are new to statistics and are looking for a quick guide to understand the key concepts in statistics.

A

Arthur5 January 2020

I became confident that programming is something easy to learn in data analysis or statistics for data science , if anyone has issue , try to contact the instructor , he will offer great support for you .

J

Joe5 January 2020

Incredible for any one would like to learn data analysis or statistics for data science from scratch , he helped me to learn from beginner level in data analysis and statistics for data science

B

Ben5 January 2020

Very elaborate course, with each topic relating to statistics and data science repeatedly explained and with many short exercises!

M

Michael4 January 2020

Horrible audio. Variations in how loud it is. You can hear care horns honking in the background (I listen while I drive). And he's all over the place in the material. It was really difficult to listen to.

W

Walter26 December 2019

Video quality is excellent , i see that instructor spent a lot of time to make video editing with background green screen to make us love data analysis and statistics for data science

C

Carnell18 December 2019

Level 1 started with great introduction about data analysis - statistics for data science , level 2 started with practical statistics and level 3 started in more advanced topics about testing methods in statistics for data science , really great course contents in statistics for data science

C

Carl18 December 2019

By practicing course examples and projects , i became in an excellent level in data analysis - statistics for data science

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