Lean Six Sigma Green Belt Online Course with Python
Last updated 2/2026
Created by Dr. Nilakantasrinivasan J, Canopus Business Management Group
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 179 Lectures ( 17h 43m ) | Size: 7.35 GB
Prepare for Six Sigma Green Belt Certification & Perform Data Analysis Using Python - No Programming Experience Needed
What you'll learn
✓ Prepare for Lean Six Sigma Green Belt Certification
✓ Able to perform various Lean Six Sigma Dat Analysis using Python
✓ No Programming Experience Needed - Python Data Analysis will be covered step by step in videos
✓ Easily solve real life business & home related problems using Lean Six Sigma Techniques
Requirements
● None
Description
New in 2023
New Lecture added (Lecture 3) - Is Lean Six Sigma Relevant in the Age of AI and Industry 4.0
New Lecture added (Lecture 12) - Cost of Poor Quality
New Resource Added (Lecture 68) - Sample Size Cheat Sheet added in resources
Why you should consider the FIRST LEAN SIX SIGMA GREEN BELT CERTIFICATION COURSE USING PYTHON?
• There is no need to emphasize the importance of Data Science or Lean Six Sigma in today's Job Market
• Python is the most popular and trending tool for Data Science now
• Lean Six Sigma involves a lot of Data Analysis & Statistical Discovery
• Traditionally Lean Six Sigma Data Analysis uses Minitab & Excel
• IN CURRENT SCENARIO, if you are NOT learning Lean Six Sigma Green Belt Data Analysis using Python, it's obvious what you are missing!
GET THE BEST OF LEAN SIX SIGMA GREEN BELT CERTIFICATION & DATA SCIENCE WITH PYTHON IN ONE COURSE & AT ONE SHOT
What to Expect in this Course?
• Prepare for ASQ / IASSC CSSGB Certification
• 176 Lectures / 17 Hours of Content
• Data Analysis in Python with Step by Step Procedure for All Six Sigma Analysis - No Programming Experience Needed
• Data Manupulation in Python
• Descriptive Statistics
• Histogram, Distribution Curve, Confidence levels
• Boxplot
• Stem & Leaf Plot
• Scatter Plot
• Heat Map
• Pearson's Correlation
• Multiple Linear Regression
• ANOVA
• T-tests - 1t, 2t and Paired t
• Proportions Test - 1P, 2P
• Chi-square Test
• SPC (Control Charts - mR, XbarR, XbarS, NP, P, C, U charts)
• Python Packages - Numpy, Pandas, Matplotlib, Seaborn, Statsmodels, Scipy, PySPC, Stemgraphic
• Full Fledged Lean Six Sigma Case Study with Solutions (in Python Scripts)
• More than 100 Resources to Download (including Python Source Files for all the analysis
• Practice questions - 19 Crossword puzzle questions on various six sigma topics included
Who this course is for
■ Operation Managers
■ Customer Service Managers
■ IT Professionals
■ Python Programmers who wish to learn Lean Six Sigma
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