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$29
  • Master the fundamentals of statistics for data science & data analytics
  • Master descriptive statistics & probability theory
  • Machine learning methods like Decision Trees and Decision Forests
  • Probability distributions such as Normal distribution, Poisson Distribution and more
  • Hypothesis testing, p-value, type I & type II error
  • Logistic Regressions, Multiple Linear Regression, Regression Trees
  • Correlation, R-Square, RMSE, MAE, coefficient of determination and more

Are you aiming for a career in Data Science or Data Analytics?

Good news, you dFon't need a Maths degree - this course is equipping you with the practical knowledge needed to master the necessary statistics.

It is very important if you want to become a Data Scientist or a Data Analyst to have a good knowledge in statistics & probability theory.

Sure, there is more to Data Science than only statistics. But still it plays an essential role to know these fundamentals ins statistics.

I know it is very hard to gain a strong foothold in these concepts just by yourself. Therefore I have created this course.

Why should you take this course?

  • This course is the one course you take in statistic that is equipping you with the actual knowledge you need in statistics if you work with data

  • This course is taught by an actual mathematician that is in the same time also working as a data scientist.

  • This course is balancing both: theory & practical real-life example.

  • After completing this course you ll have everything you need to master the fundamentals in statistics & probability need in data science or data analysis.

What is in this course?

This course is giving you the chance to systematically master the core concepts in statistics & probability, descriptive statistics, hypothesis testing, regression analysis, analysis of variance and some advance regression / machine learning methods such as logistics regressions, polynomial regressions , decision trees and more.

In real-life examples you will learn the stats knowledge needed in a data scientist's or data analyst's career very quickly.

If you feel like this sounds good to you, then take this chance to improve your skills und advance career by enrolling in this course.

  • Absolutely no previous experience required. We will learn everything right from the basics and then work our way up step by step
  • Eagerness and motivation to learn
  • Anybody that wants to master statistics & probabilities for data science & data analysis
  • Anybody who wants to pursue a career in Data Science
  • Professionals and students who want to understand the necessary statistics for data analysis
View More...
  • Section 1 : Let's get Started 4 Lectures 00:11:39

    • Lecture 1 :
    • Lecture 2 :
    • What will you learn in this course
    • Lecture 3 :
    • How to get the most out of this course
    • Lecture 4 :
    • Resources
  • Section 2 : Descriptive Statistics 13 Lectures 00:48:23

    • Lecture 1 :
    • Descriptive Statistics intro
    • Lecture 2 :
    • Mean
    • Lecture 3 :
    • Median
    • Lecture 4 :
    • Mode
    • Lecture 5 :
    • Mean or Median?
    • Lecture 6 :
    • Skewness
    • Lecture 7 :
    • Practice: Skewness
    • Lecture 8 :
    • Solution: Skewness
    • Lecture 9 :
    • Range & IQR
    • Lecture 10 :
    • Sample vs. Population
    • Lecture 11 :
    • Variance & Standard deviation
    • Lecture 12 :
    • Impact of Scaling & Shifting
    • Lecture 13 :
    • Statistical Moments (+Screenshot attached)
  • Section 3 : Distribution 5 Lectures 00:42:25

    • Lecture 1 :
    • Practise: Normal distribution
    • Lecture 2 :
    • Z-Scores
    • Lecture 3 :
    • Normal distribution
    • Lecture 4 :
    • What is a distribution?
    • Lecture 5 :
    • Solution: Normal distribution
  • Section 4 : Probability Theory 27 Lectures 03:13:39

    • Lecture 1 :
    • Introduction
    • Lecture 2 :
    • Probability Basics
    • Lecture 3 :
    • Calculating simple Probabilities
    • Lecture 4 :
    • Practice: Simple Probabilities
    • Lecture 5 :
    • Quick solution: Simple Probabilites
    • Lecture 6 :
    • Detailed solution: Simple Probabilities
    • Lecture 7 :
    • Rule of addition
    • Lecture 8 :
    • Practice: Rule of addition
    • Lecture 9 :
    • Quick solution: Rule of addition
    • Lecture 10 :
    • Detailed solution: Rule of addition
    • Lecture 11 :
    • Rule of multiplication
    • Lecture 12 :
    • Practice: Rule of multiplication
    • Lecture 13 :
    • Solution: Rule of multiplication
    • Lecture 14 :
    • Bayes Theorem
    • Lecture 15 :
    • Bayes Theorem - Practical example
    • Lecture 16 :
    • Expected value
    • Lecture 17 :
    • Practice: Expected value
    • Lecture 18 :
    • Solution: Expected value
    • Lecture 19 :
    • Law of Large Numbers
    • Lecture 20 :
    • Central Limit Theorem - Theory
    • Lecture 21 :
    • Central Limit Theorem - Intuition
    • Lecture 22 :
    • Central Limit Theorem - Challenge
    • Lecture 23 :
    • Central Limit Theorem - Exercise
    • Lecture 24 :
    • Central Limit Theorem - Solution
    • Lecture 25 :
    • Binomial distribution
    • Lecture 26 :
    • Poisson distribtuion
    • Lecture 27 :
    • Real life problems
  • Section 5 : Hypothesis Testing 12 Lectures 01:16:44

    • Lecture 1 :
    • Hypothesis introduction
    • Lecture 2 :
    • What is an hypothesis?
    • Lecture 3 :
    • Significance level and p-value
    • Lecture 4 :
    • Type I and Type II errors
    • Lecture 5 :
    • Confidence intervals and margin of error
    • Lecture 6 :
    • Excursion: Calculating sample size & power
    • Lecture 7 :
    • Performing the hypothesis test
    • Lecture 8 :
    • Practice: Hypothesis test
    • Lecture 9 :
    • Solution: Hypothesis test
    • Lecture 10 :
    • t-test and t-distribution
    • Lecture 11 :
    • Proportion testing
    • Lecture 12 :
    • Important p-z pairs
  • Section 6 : Regression 14 Lectures 01:00:40

    • Lecture 1 :
    • Regression Introduction
    • Lecture 2 :
    • Linear Regression
    • Lecture 3 :
    • Correlation coefficient
    • Lecture 4 :
    • Practice: Correlation
    • Lecture 5 :
    • Solution: Correlation
    • Lecture 6 :
    • Practice: Linear Regression
    • Lecture 7 :
    • Solution: Linear Regression
    • Lecture 8 :
    • Residual, MSE & MAE
    • Lecture 9 :
    • Practice: MSE & MAE
    • Lecture 10 :
    • Solution: MSE & MAE
    • Lecture 11 :
    • Coefficient of determination
    • Lecture 12 :
    • Root Mean Square Error
    • Lecture 13 :
    • Practice: RMSE
    • Lecture 14 :
    • Solution: RMSE
  • Section 7 : Advance Regression and Machine Learning Algorithm 8 Lectures 01:01:26

    • Lecture 1 :
    • Multiple Linear Regression
    • Lecture 2 :
    • Overfitting
    • Lecture 3 :
    • Polynomial Regression
    • Lecture 4 :
    • Logistic Regression
    • Lecture 5 :
    • Decision Trees
    • Lecture 6 :
    • Regression Trees
    • Lecture 7 :
    • Random Forests
    • Lecture 8 :
    • Dealing with missing data
  • Section 8 : ANOVA( Analysis of Variance) 5 Lectures 00:34:08

    • Lecture 1 :
    • ANOVA - Basics & Assumptions
    • Lecture 2 :
    • One-way ANOVA
    • Lecture 3 :
    • F-Distribution
    • Lecture 4 :
    • Two-way ANOVA – Sum of Squares
    • Lecture 5 :
    • Two-way ANOVA – F-ratio & conclusions
  • How do i access the course after purchase?

    Once you purchase a course (Single course or Subscription), you will be able to access the courses instantly online by logging into your account. Use the user name & password that you created while signing up. Once logged in, you can go to the "My Courses" section to access your course.
  • Are these video based online self-learning courses?

    Yes. All of the courses comes with online video based lectures created by certified instructors. Instructors have crafted these courses with a blend of high quality interactive videos, lectures, quizzes & real world projects to give you an indepth knowledge about the topic.
  • Can i play & pause the course as per my convenience?

    Yes absolutely & thats one of the advantage of self-paced courses. You can anytime pause or resume the course & come back & forth from one lecture to another lecture, play the videos mulitple times & so on.
  • How do i contact the instructor for any doubts or questions?

    Most of these courses have general questions & answers already covered within the course lectures. However, if you need any further help from the instructor, you can use the inbuilt Chat with Instructor option to send a message to an instructor & they will reply you within 24 hours. You can ask as many questions as you want.
  • Do i need a pc to access the course or can i do it on mobile & tablet as well?

    Brilliant question? Isn't it? You can access the courses on any device like PC, Mobile, Tablet & even on a smart tv. For mobile & a tablet you can download the Learnfly android or an iOS app. If mobile app is not available in your country, you can access the course directly by visting our website, its fully mobile friendly.
  • Do i get any certification after completing the course?

    Yes. Once you succesfully complete any course on Learnfly marketplace, you get a certiifcate of course completion emailed to you within 24 hours with your name & the Learnfly badge. You can definately brag about it & share it on your social media or with friends as one of your achievement. Click here to view the sample certificate Click Here
  • For how long can i access my course after the purchase?

    If you buy a single course, that course is accessible to you for a lifetime. If you go for a premium subcription, you can access all the courses on Learnfly marketplace till your subscription is Active.
  • Whats the difference between Single Course Purchase & Go Premium option?

    With Single Course Purchase, you only get an access of one single course. Whereas, with premium monhtly or annual subscription, you can access all the existing or new courses on learnfly marketplace. You can decide what option suits you the best and accordingly you can make your purchase.
  • Is there any free trial?

    Currently, we don't have any free trial but it may be available in near future.
  • What is the refund policy?

    We would hate you to leave us. However, if you are not satisfied, you can ask for a full refund within 30 days & we will be happy to assist you further.

Nikolai Schuler ,

I am a mathematician working as a data scientist and BI consultant. I am helping people all over the world with the tools and skills of data science and business intelligence such as Power BI and Statistics. I found it not that easy to find courses that are high quality and easy to understand in the same time. Therefore I decided to create these courses that are high quality on the one hand and easy to learn with on the other hand. These courses now have reached people in more than 100 countries and I am really glad to help spreading these IT skills and enable people to pursue the career they are after. As I am a data specialist on the one hand but also introducing ordinary users to Power BI and other tools on the other hand, I understand the common hurdels most people have. Data and teaching are my passions and therefore I am really looking forward to level up your IT skills as well!
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