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- Marketing Analytics Using Python and R Programming
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- Henry Harvin
- Courses
- Marketing Analytics Certification Training Course Plus Lean Six Sigma Green Belt Certification Training
Marketing Analytics Certification Training Course(CMAP) + Lean Six Sigma Green Belt Certification Training Course(CSSE-GB)
Quick Facts
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Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
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Mode of Delivery
Video and Text Based
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Course and certificate fees
Fees information
₹ 22,050 ₹24,500
certificate availability
Yes
certificate providing authority
Henry Harvin
The syllabus
Phase 1
Module 1
Introductory Topics to Analytics
- Understanding the need for Analytics in Specific Domain; CRISP Modeling
Introduction to Data Management
- Properties & Types of Data, Measurement Scale, Basic Statistics on Data
Basics of Python Programming
- Need for R
- Features of R
- Download, Setup, Installation
- Python & Python Studio
- Configuration. eg. Learning to set up Python and share Code
Data Structures in R
- Creating and Understanding Basic Data Structures in Python - Vector, List, Matrix, Array, Data Frame & Factors which help in creating data in Python programming.
Data Manipulation & Summarisation in R
- Understanding how data can be summarised in different ways to do Descriptive Analysis which describes features of data.
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
Analytical Modeling
- Understand what is Modeling and how it can be used in Various Domain
Statistical Tests
- P-Value
- Z Value
- Hypothesis
- Null Hypothesis
- Alternative Hypothesis
- F Test
- ANOVA Introduction
Linear Regression (Using Python)
- Start of Machine Learning,
- Develop a Prediction Model for predicting financial values based on one or more than 1 Independent Variable
- Understand the assumptions and measures of goodness of Model
- Understand its prediction ability
Visualization using Graphs
- Creating Graph in Python and understanding which graph to be used when.
Missing Value and Outlier Analysis
- Understanding how missing values & outliers are handled in data summarisation & modelling
Logistic Regression
- Predicting Binary Outcome (Buy or not, Churn or not, Loan Default or not) based on Independent Variables eg. Predicting Cases for Fraud, Default on Payment, etc.
Define
- Project Charter
- Project Charter Contents
- Process Mapping
- SIPOC
- Identifying Customers & VOC
- Establishing VOC to CTQ
- KANO Model
- RACI Model
- Quiz
Module 3
Clustering
- Grouping customers based on characteristics so that they can be a target for sale increase
Decision Trees
- When to use CART & CHAID to create a decision tree based on categorical variables.
Ensembles (Bagging & Boosting)
- Random Forest, XGBoost: Problems of Decision Tree covered in Random Forest
- How group thinking impacts the decisions (from a business point of view).
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
Twitter Analysis
- Configure Twitter Account & Application
- Setup for downloading tweets and analyse them for positive and negative sentiments related to Financial News/ Articles.
- Analyse
- 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
Post Learning
- Final Assessment
- Certificate Dispatch
- Monthly Brush Up Sessions- Live Online (12months)
Phase 2
- Six Sigma Green Belt
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
- Statistical Process Control
- SPC Selection Process
- Control Plan
Complimentary Module 1: Soft Skills Development
- Soft Skills Training
Complimentary Module 2: Resume Writing
- Resume Writing
Projects Covered
Analytics
- HR: Analyze the Attrition rate of Employees
- Sales: Predicting Department wise Sales
- Multi-Domain: Business Analytics Optimization
- Marketing: Website Trend Analysis
- Financial Analysis: Stock Market Prediction
- Finance: Analyze ETF Trends
Six Sigma
- Quality of Work Life in an Organization of Employees
- Improve Total time & Rolled Throughput Yield
- Optimization of Average call times in a BPO-Voice Process
- Defect Reduction in Die Casting
- Improving Internal SQR in XXM Activities
Articles
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