Statistical Thinking and Data Science with R.
- Description
- Curriculum
- FAQ
- Reviews
not only you learn R in this course, but you also learn how to use statistics and machine learning to make decisions!!!
It’s been six years since I moved from Excel to R and since then I have never looked back! With eleven years between working in Procurement, lecturing in universities, training over 2000 professionals in supply chain and data science with R and python, and finally opening my own business in consulting for two years now. I am extremely excited to share with you this course. My goal is that all of you become experts in R, statistical thinking, and Machine learning. I have put all the techniques I have learned and practiced in this one sweet bundle of data science with R.
By the end of this course you will be able to :
Learn R from scratch.
What are probabilities? random experiments, random variables, and sample space?
How can we detect the outliers in data?.
How can we make our resources efficient using statistics and data?
How can we test a hypothesis that a supplier is providing better products than another supplier?
How can we test the hypothesis that a marketing campaign is significantly better than another marketing campaign?
What is the effect of the last promotion on the increase in sales?
How can we make simulations to understand what is the expected revenue coming from a business?
how can we build machine learning models for classification and regression using statistics?
what are the log odds, odds ratio, and probabilities produced from logistic regression models?
What is the right visualization for categorical and continuous data?
How to Capture uncertainty with Distributions? What is the right distribution that fits the data best?
Apply machine learning to solve problems.
Do you face one of these questions regularly? well then, this course will serve as a guide for you.
Statistics & Probabilities are the driving force for many of the business decisions we make every day. if you are working in finance, marketing, supply chain, product development, or data science; having a strong statistical background is the go-to skill you need.
Although learning R is not the main focus of this course, but we will implicitly learn R by diving deep into statistical concepts. The Crucial advantage of this course is not learning algorithms and machine learning but rather developing our critical thinking and understanding what the outcomes of these models represent.
The course is designed to take you to step by step in a journey of R and statistics, It is packed with templates, Exercises, quizzes, and resources that will help you understand the core R language and statistical concepts that you need for Data Science and business analytics. The course is :
· Practical
· Highly analytical
· Packed with quizzes and assignments.
· Excel tutorials included.
· R scripts and tutorials
· Easy to understand and follow.
· Learn by Doing, no boring lectures.
· Comprehensive
· Data-driven
· Introduces you to the statistical R language.
· Teaches you about different data visualizations of ggplot.
· Teaches you How to clean, transform, and manipulate data.
Looking forward to seeing you inside 🙂
Haytham
-
17IntroductionVideo lesson
-
18Different data structures and types in RVideo lesson
-
19Do arithmetic calculations and write functions in RVideo lesson
-
20Creating a list.Video lesson
-
21Importing Data in R and Basic explorationVideo lesson
-
22Selecting data in a data frameVideo lesson
-
23If else functionVideo lesson
-
24ConditionsVideo lesson
-
25Functions with ConditionsVideo lesson
-
26ForloopsVideo lesson
-
27Applying a function inside the loopVideo lesson
-
28For-loop on a data-frameVideo lesson
-
29Applying the function on a data frameVideo lesson
-
30AssignmentVideo lesson
-
31Assignment Section 4 answer Part 1Video lesson
-
32Assignment Section 4 answer part 2Video lesson
-
33SummaryVideo lesson
-
34IntroVideo lesson
-
35Central tendencyVideo lesson
-
36Measures of spreadVideo lesson
-
37Calculating measures of spread and centrality Part 1Video lesson
-
38Calculating measures of spread and centrality PART 2Video lesson
-
39Central tendency assignmentText lesson
-
40Detecting outliersVideo lesson
-
41Detecting outliers in RVideo lesson
-
42IntroVideo lesson
-
43Intro to dplyrVideo lesson
-
44Investigate with DplyrVideo lesson
-
45Unique invoicesVideo lesson
-
46Average Bucket value per countryVideo lesson
-
47Average items in an invoiceVideo lesson
-
48JoiningVideo lesson
-
49Changing date time to dateVideo lesson
-
50Pivot widerVideo lesson
-
51Pivot longerVideo lesson
-
52Separate and PasteVideo lesson
-
53Putting it all togetherVideo lesson
-
54Assignment : New York airlinesVideo lesson
-
55Assignment : Question 1 answerVideo lesson
-
56Assignment question 2&3 answerVideo lesson
-
57Assignment question 4,5,6Video lesson
-
58Assignment question 7Video lesson
-
59SummaryVideo lesson
-
60IntroductionVideo lesson
-
61Line plotsVideo lesson
-
62Scatter plotsVideo lesson
-
63Bar plotsVideo lesson
-
64Distribution plotsVideo lesson
-
65Box plotsVideo lesson
-
66HistogramsVideo lesson
-
67Histograms 2Video lesson
-
68AssignmentVideo lesson
-
69Assignment Solution Question 1 and 2Video lesson
-
70Assignment Solution Part 2Video lesson
-
71SummaryVideo lesson
External Links May Contain Affiliate Links read more