Marketing Analytics Certification Training Course(CMAP) + Lean Six Sigma Green Belt Certification Training Course(CSSE-GB)

Henry Harvin

Online

64 Hours

₹ 22050 24500

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study, Virtual Classroom	Mode of Delivery Video and Text Based

Course and certificate fees

Fees information

₹ 22,050 ₹24,500

certificate availability

Yes

certificate providing authority

Henry Harvin

The syllabus

Phase 1

Marketing Analytics Using Python and R Programming

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

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