Data Analysis in Python for Lean Six Sigma Professionals
Data Analysis in Python for Lean Six Sigma Professionals, available at $59.99, has an average rating of 4.7, with 31 lectures, based on 60 reviews, and has 292 subscribers.
You will learn about Learn Lean Six Sigma Data Analysis in Python Get Step by Step Procedure for all Six Sigma Analysis is covered No Programming Experience Needed. Course will start with Python installation One Full Fledged Lean Six Sigma Case Study with Solutions Download all Python Source Files for all the analysis This course is ideal for individuals who are Lean Six Sigma Professionals It is particularly useful for Lean Six Sigma Professionals.
Enroll now: Data Analysis in Python for Lean Six Sigma Professionals
Summary
Title: Data Analysis in Python for Lean Six Sigma Professionals
Price: $59.99
Average Rating: 4.7
Number of Lectures: 31
Number of Published Lectures: 31
Number of Curriculum Items: 31
Number of Published Curriculum Objects: 31
Original Price: $49.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn Lean Six Sigma Data Analysis in Python
- Get Step by Step Procedure for all Six Sigma Analysis is covered
- No Programming Experience Needed. Course will start with Python installation
- One Full Fledged Lean Six Sigma Case Study with Solutions
- Download all Python Source Files for all the analysis
Who Should Attend
- Lean Six Sigma Professionals
Target Audiences
- Lean Six Sigma Professionals
Why you should consider this PYTHON course?
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As a Lean Six Sigma Professional, you are already aware how to perform Six Sigma Data Analysis & Discovery using Minitab, Excel, JMP or SPSS
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Data Science is a skill in demand and you have an added advantage due to your prior Six Sigma Data Analysis proficiency
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But without able to perform all the analysis in Python, you at Big Dis-advantage
What you will Get in this Course?
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Step-by-Step Procedure starting with Python installation to perform all the below Six Sigma Data Analysis
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No Programing Experience Needed
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Learn data manipulation prior to analysis
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Exposure to various Python Packages mentioned below
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Download all Python Source Files
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One End to End Six Sigma Analysis Case Study
Course Curriculum
Six Sigma Tools Covered using Python
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Data Manipulation in Python
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Descriptive Statistics
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Histogram, Distribution Curve, Confidence levels
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Boxplot
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Stem & Leaf Plot
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Scatter Plot
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Heat Map
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Pearson’s Correlation
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Multiple Linear Regression
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ANOVA
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T-tests – 1t, 2t and Paired t
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Proportions Test – 1P, 2P
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Chi-square Test
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SPC (Control Charts – mR, XbarR, XbarS, NP, P, C, U charts)
Python Packages
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Numpy
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Pandas
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Matplotlib
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Seaborn
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Statsmodels
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Scipy
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PySPC
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Stemgraphic
Course Curriculum
Chapter 1: Welcome
Lecture 1: Introduction
Lecture 2: Six Sigma Data Analysis covered in Python in this Course
Lecture 3: Introduction to Python
Chapter 2: Getting started with Python
Lecture 1: Installing Python
Lecture 2: Getting Started with Jupyter I
Lecture 3: Getting Started with Jupyter II
Lecture 4: Data Types in Python
Lecture 5: Python Packages
Lecture 6: Numpy Basics
Lecture 7: Pandas Basics
Lecture 8: Data Clean up using Pandas
Chapter 3: Business Statistics
Lecture 1: Descriptive Statistics in Python
Lecture 2: Plotting Histogram in Python
Lecture 3: Computing Confidence Interval in Python
Lecture 4: Normality Tests in Python
Chapter 4: Graphical Analysis Methods
Lecture 1: Creating Box Plots in Python
Lecture 2: Stem & Leaf Plots in Python
Chapter 5: Assessing Process Capability
Lecture 1: Performing Process Capability in Python
Chapter 6: Performing Hypothesis Tests
Lecture 1: Perform 1 t Test in Python
Lecture 2: Perform 2 t Test in Python
Lecture 3: Perform Paired t Test in Python
Lecture 4: Perform ANOVA in Python
Lecture 5: Perform Chi-square test in Python
Lecture 6: Perform 1P Test in Python
Lecture 7: Perform 2P Test in Python
Lecture 8: Creating Scatter Diagram in Python
Lecture 9: Computing Correlation Coefficient in Python
Lecture 10: Regression in Python
Chapter 7: Statistical Process Control
Lecture 1: Plotting Control Charts in Python
Chapter 8: Clear Calls Case Study
Lecture 1: ClearCalls Case Study Overview & Python Data Analysis Source Files with solution
Lecture 2: Bonus Lecture: Details of our other courses
Instructors
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Nilakantasrinivasan Janakiraman
Customer Experience & Business Transformation Leader
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 3 votes
- 3 stars: 10 votes
- 4 stars: 25 votes
- 5 stars: 22 votes
Frequently Asked Questions
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