Welcome to this platform of Learnvern.
My name is Megha Varshney, and today I am the trainer for this Statistics for Data Science course.
So, in this course you will learn what Statistics is, and why it is necessary to know it in today’s times.
We will see through the real-world examples, of how statistics is used in our daily life.
As important as it is to learn Python and Machine Learning in the domain of Data Science, it is equally important to have the knowledge of statistics.
How much is Statistics important in the field of data science and by how much? All this we will discuss in detail.
And by the end of this course, we will master Static’s basics to advance topics.
If you are an undergraduate or graduate student, and you wish to make a career in the field of Data Science then this course is for you.
If you are passionate for roles like, statistician, business analyst, market analyst or data scientist, and wish to move ahead in that field then, you can do this course and take a good job in different fields.
We have divided this course into different modules.
There are different units in every module, in which we will discuss all the important topics in detail.
I will tell you once which all are our modules, and in which way, we have divided the course.
So, our very first module is, in which we will get to know what Statistics is, and what we need it for, or why we have to learn it, in which all domains or fields Statistics is used.
We will know much about all this in detail.
Our next module is about Descriptive Statistics.
In any Data Analysis project, we have to first describe the data.
So, in this particular module, we will discuss all the important topics of different statistic’s majors like, Mean, Mode, Median or Standard deviation, Variance, Skewness, Kurtosis, Box and Whisker Plots, etc.
Third module is my very important module, which is Inferential Statistics.
In which we will know why Inferential statistics is important, or why it is most important for us to move ahead in the field of Data Science.
In this module, we will discuss in great detail about, probability and different probability distributions.
What is discrete or continuous probability distribution, what is the difference between the two.
Bernoulli distribution, Binomial distribution, uniform distribution, normal distribution, all these jargons which we find very difficult.
We will discuss all of them in great detail.
Plus, a very important theorem in statistics, which is used, is called the Central Limit Theorem.
We will get to know about, how we can use it step by step.
My fourth module is based on Hypothesis Testing.
In which, we will get to know how Hypothesis is done, what is hypothesis, what do the terms like Null and Alternate Hypothesis means, in which ways you can minimize type one or type two errors, which are these types of errors, we will get to know about all these in the fourth module.
Along with that, we have also covered topics like Correlation and Covariance.
My fifth module is based on different types of Hypothesis tests.
Like Z-test (Pronunciation: Zee test), t-test, chi-square test (Pronunciation: Chai square test), anova test, all these tests are widely used tests in the industry.
And we will understand all these, how we find the critical value, how we find p-value and what can be interview related questions.
We will discuss in great detail about all these.
Then comes my last module, which is fundamentals of Regression Analysis.
In that we will get to know what regression is, how we can form a simple linear regression and a multiple linear regression in a simple manner, and how we can find a best fit line.
This was the walk through of the complete course, in which way we are going to go ahead in this module.
At the end of each module, along with the video lecturers, you have also been given assignments and quizzes, through which you can practically test your knowledge.
In short, we will cover all the topics in this course, which are extremely useful in the current industry trend, and which makes you job ready.
So, come let’s start with our first module, which is named Getting started with Statistics.
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