Six Sigma Certification with Business Analytics- Henry Harvin® in Agra

Module 1: Evaluation & Introduction to Lean Six Sigma
- History & Evolution of Six Sigma
- Six Sigma & Lean Definition
- COPQ
- Variation
- DMAIC Phases
- Six Sigma Roles & Responsibilities
Module 2: Define
- Project Charter
- Project Charter Contents
- Process Mapping
- SIPOC
- Identifying Customers & VOC
- Establishing VOC to CTQ
- KANO Model
- RACI Model
Module 3: Measure
- What is Data?
- Data Classification & Type
- Data collection plan
- Sampling & Sampling Strategies
- Mean
- Median
- Mode
- Range
- Variance
- Standard Deviation
- Case Study – Basic Statistics
- Normal Distribution
- Testing Normality
- Histogram
- Dot Plot
- Box Plot
- Time Series Plot
Module 4: Analyze
- Measurement System Analysis
- Accuracy & Precision
- Repeatability
- Reproducibility
- Gage R & R study
- Process Capability
- Capability Formulas
- DPMO, DPU, DPO
- Rolled Throughput Yield
- 7 QC Tools
- Central Limit Theorem
- Hypothesis testing
- Alpha risk
- Beta Risk
- t-test
Module 5: Improve
- Improvement Strategy
- Regression
- Correlation
- Scatter Plot
- Brainstorming
- 5S
- FMEA
- Piloting Solutions
- Automation
- Regression
- Correlation
- Scatter Plot
- Brainstorming
- Automation
- Mistake Proofing
Module 6: Control
- Statiscal Process Control
- SPC Selection Process
- Control Plan
Module 7: Analytics - General
- What is Analytics (BI, BA, Levels, etc)
- Why Analytics (Appl in various domains..)
- Different Roles in Analytics
- Tools and Techniques in Analytics
- Data Science, Data Mining, Statistics, Machine Learning, Supervised and Non-Supervised Techniques
- CRISP Modeling Framework
- Scales of Measurements
Module 8: Python Environment
- Anaconda - Download & Setup
- IDEs - Jupyter, Spyder, PyCharm
- Git - Setup and Configuration with IDEs
- Creating and Managing Analytics/ ML Projects
Module 9: Basic Programming and Data Structures
- Basic Data Structures & Programming Constructs
- Libraries
- NumPy
- Pandas
- Matplotlib
Module 10: Pre-Process and Descriptive Summary
- Pre Processing Data
- Group Summaries
- Crosstab, Pivot and Reshape data
- Managing Missing Values
- Outliers Detection
- Various types of Joins, merge
- Managing indexes in pandas
- Partitioning data into train and test set
- Scaling of Data (useful for Clustering)
Module 11: Statistics
- Basic Statistics (mean, median, mode)
- Other Statistics (sd, var, quantile, skewness, kurtosis)
- Hypothesis Tests (t-test, Chi-sq tests, etc)
- Probability Distributions (normal, binomial, etc)
- Sampling Techniques
Module 12: Graphical Representation of Data
- Selection of Graph
- Basic Graphs (histogram, Bar Plot, boxplot, pie, etc)
- Libraries (Matplotlib, seaborn, plotline)
- Managing plot parameters(size, title, axis, legend, etc)
- Advanced Graphs (correlation, heatmap, mosaic, etc)
- Exporting graphs
Module 13: Modeling Techniques & Linear Regression
- Modeling Techniques
- Simple Linear Regression
- Multiple Linear Regression
- Libraries - sklearn, statsmodels
- Predict DV on IVs
- Metrics of Linear Regression(R2, RMSE, p-values)
- Applications of Linear Regression
- Assumptions of Linear Regression
Module 14: Logistic Regression
- Difference between Linear and Logistic
- Logistic Regression
- Metrics of Logistic Regression (confusion matrix, ROC curve)
- Predict the probability of DV on IV
- Applications of Logistic Regression
Module 15: Classification
- Difference between classification and regression decision trees from CART models
- Understanding tree from the plot
- Classification Tree - predict class, plot, accuracy
- Regression Tree - predict numerical value, plot, RMSE
- Improving tree accuracy using Random Forests
- Bagging and Boosting
- Applications of Decision Tree
- KNN (k-nearest neighbors)
- Neural Networks
- Gradient Descent
- SVM (Support Vector Machine)
Module 16: Cluster Analysis
- Clustering for Grouping Data
- Types - Hierarchical & Non-Hierarchical
- K Means - output metrics (iter, error, plot)
- Hierarchical (Agglomerative & Divisive) - Dendrogram, Visual plot
- Extracting the data in clusters, Cluster Centers
- Applications of Clustering
Module 17: Association Rule Analysis
- Applying AR to the grocery store for Market Basket Analysis
- Metrics- Support, Confidence, Lift
- Frequent Itemsets and Rules; Filtering rules
- Applications of AR
Module 18: Text Mining
- Managing Unstructured Data; Unstructured to Structured Data
- Extracting Tweets from Twitter
- Extracting words for Sentiment Analysis
- WordCloud to visualize the frequency of occurrence of words in the text
- Applications of Text Mining

Know the complete offerings of our Lean Six Sigma Combo (Six Sigma Green Belt + Python Business Analyst)

Lean Six Sigma Combo ( Six Sigma Green Belt + Python Business Analyst) Course in Agra

20 Jan 2025

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Know the complete offerings of our Lean Six Sigma Combo (Six Sigma Green Belt + Python Business Analyst) in Agra

About Lean Six Sigma Combo (Six Sigma Green Belt + Python Business Analyst) in Agra

Lean Six Sigma Combo (Six Sigma Green Belt + Python Business Analytics) Course

Agota™ Framework

Trainers at Henry Harvin®

Alumni Status

Gold Membership Benefits

Key Highlights

Recognitions of Henry Harvin® Education

Career Benefits

Key Highlights

60 Hours of Instructor-Led Sessions

20 Hours of Live Interactive Doubt Solving Sessions

10 Hours of Live Master Sessions by Industry Experts

192 Hours of Self-Paced Learning

Job-Ready Portfolio of 6 Capstone Projects

142 Auto-Graded Assessments

12+ Industry Case Studies

90 Guided Hands-On Exercises

6+ Assignments and Mini Projects

1 Mock Interview and 1 Hackathon

Get 1-Year Gold Membership of Henry Harvin® Quality Management Academy

Get a guaranteed Internship with Henry Harvin® and in top MNCs like J.P. Morgan, Accenture & many more via Forage

Get 3 in 1 Placement support through Placement Drives, Premium access to Job portal & Personalized Job Consulting

10 Hours of Mentorship by Industry Experts

Earn Certification of Course from Henry Harvin®, Govt of India recognized & Award-Winning Institute and NSDC Certification

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Access the best jobs in the industry

Agota™ Framework

Curriculum For Lean Six Sigma Combo (Six Sigma Green Belt + Python Business Analyst) in Agra

Module 1: Evaluation & Introduction to Lean Six Sigma

Module 2: Define

Module 3: Measure

Module 4: Analyze

Module 5: Improve

Module 6: Control

Module 7: Analytics - General

Module 8: Python Environment

Module 9: Basic Programming and Data Structures

Module 10: Pre-Process and Descriptive Summary

Module 11: Statistics

Module 12: Graphical Representation of Data

Module 13: Modeling Techniques & Linear Regression

Module 14: Logistic Regression

Module 15: Classification

Module 16: Cluster Analysis

Module 17: Association Rule Analysis

Module 18: Text Mining

Admission Closes On 20 Jan 2025

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Starts in 5 day. 20 Jan 2025

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Get Ahead with Henry Harvin® Lean Six Sigma Combo (Six Sigma Green Belt + Python Business Analyst) in Agra Certification

What you'll Learn in this course

Process Improvement Methodologies

Performing Complex Data Analysis

Organizational Improvements

Project Management and Leadership Skills

Market Trend Analysis

Manufacturing Process Optimization

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