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Data Science for Managers

Course Summary

Data Science skills are in big demand, every present-day organization seeks individuals who can leverage the potential of data, for making important decisions. The Data Science for Managers course mainly concentrates on the tools and techniques needed to analyze the data of a business and derive insights from them and use them to make further business decisions. 


Objectives

After learning the Data Science for Managers course, a candidate will be well equipped with the following:

  • Business Analytics Foundation
  • Statistics
  • Optimization models with excel
  • Predictive Analytics with Regression with excel
  • Decision modeling with excel

Course Outline

Data Science Introduction

  • Data Science Introduction 
  • Data Science Evolution 
  • Business Applications 
  • Benefits of Data Science 
  • Challenges of Data Science 

Data Science Context & Classification

  • Data Science Context : Data Mining / Business Intelligence / Data Science 
  • Perspective of Data Science 
  • Data Science Classification 
  • Various Types Of Data Science 

Data And Data Science Tools

  • Popular Tools for Data Science 
  • Data Sources 
  • Data Reliability and Validity

Data Science Workflow

  • Data Science Steps 
  • Recognize the Problem 
  • Define a Problem 
  • Structure the Problem 
  • Analyze the Problem 
  • Interpret the Results 
  • Implement Solution 
  • Crisp-Dm Reference Model

Data Science Introduction

  • Overview of Statistics 
  • Descriptive Statistics 
  • Inferential Statistics 
  • Basics Terminologies 
  • Cochran's Min Size Formula 
  • Types of Data 
  • Examples of Various Data 
  • Cochran’s Formula Example 
  • Examples of Variables 

Harnessing Data

  • Harnessing Data Introduction
  • Making Sense of the Data 
  • Sampling Methods 
  • Simple Random Sampling 
  • Stratified Sampling 
  • Systematic Sampling 
  • Biased Sampling Methods

Exploratory Data Analysis

  • Exploratory Data Analysis 
  • Measures of Central Tendencies 
  • Mean 
  • Median 
  • Mode 
  • Measures of Variability 
  • Range 
  • Calculating Standard Deviation

Histogram & Empirical Rule

  • Z- Score / Z-Value/ Standard Score 
  • Calculating Z-Score 
  • Histogram 
  • Empirical Rule 
  • Outliers 

Normal Distribution And Correlation

  • Normal Distributions, Mean, Variance 
  • Normality Testing
  • Skewness 
  • Kurtosis 
  • Correlation

Decision Modeling

  • Mathematical Modeling 
  • Decision Modeling 
  • Break Even Decision Model 
  • Prescriptive Model Pricing

Sales Promotion Model

  • Sales Promotion Decision 
  • Sales Prediction With Multiple Regression Analysis

Kerc Inc – Case Study: Predictive Analytics with Less Uncertainty

  • Kerc Inc – Car Manufacturer Case Study 
  • Kerc Inc Case Modeling 
  • Optimizing Kerc Production Model

Wonderzon Retailer : Case Study

  • Wonderzon Case Study: Problem Statement 
  • Wonderzon Case Modeling
  •  Predicting Optimum Logistics Cost

Predictive Analytics

  • Predictive Analytics Introduction 
  • Types of Predictive Analytics
  •  Application of Predictive Analytics

Regression

  • Mathematical Modeling Regression 
  • Simple Learning Regression 
  • Predicting Profit with Regression

Multiple Regression

  • Multiple Regression Modeling 
  • Predictive Analytics Summary

Smart It Inc Internet Usage - Plan Decision Predictive Analytics with High Uncertainty

  • Monte Carlo Simulation Introduction 
  • Smart It Inc. Internet Plan : Problem Statement 
  • Model Building 
  • Optimization and Plan Decision

Kickathlon Sport Retailer : Decision Tree

  • Kickathlon – Supplier Decision Making 
  • Decision Tree Convention 
  • Kickathlon – Supplier Decision Tree

Decision Tree – Decision Making Process

  • Decision Tree Convention 
  • Common Decision Strategies 
  • Maxi-Min Strategy 
  • Maxi-Max Strategy 
  • Maximize Expected Value Strategy 
  • Decision Trees with Monte Carlo Simulation Uncertain Output Range 
  • Decision Tree Summary

Tableau: Connecting to Data Source

  • Tableau Introduction 
  • Connecting to Various Data Sources 
  • Fixing Data Issues while Importing

Tableau: Basic Visualizations

  • Tableau Pane
  • Creating Basic Visualizations 
  • Insights for Data Through Visualizations 
  • Exploratory Data Analysis

Finding Insights

  • Stacked Bar Graph 
  • Deriving Insights Through Compound Plots

Time Series Forecasting

  • Forecasting Sales 
  • Adjusting Forecasting Parameters

Filters & Dashboards

  • Various Filters Options 
  • Interactive Filters 
  • Building Effective Dashboards

Publishing Insights

  • Various Publishing Options 
  • Tableau Packaged Workbook 
  • Summary

Who needs this course?

  • Senior professionals who wish to switch their career to Data Science
  • Chief executive officers, Directors and Decision-makers in the company
  • Professionals who have significant years of experience in the field

Prerequisite

  • Basic knowledge of working in the data science domain
  • Knowledge of Statistics and Mathematics and their relevance in Data Science
  • Should have an experience of working in a decision making role

Objectives

After learning the Data Science for Managers course, a candidate will be well equipped with the following:

  • Business Analytics Foundation
  • Statistics
  • Optimization models with excel
  • Predictive Analytics with Regression with excel
  • Decision modeling with excel

Course Outline

Data Science Introduction

  • Data Science Introduction 
  • Data Science Evolution 
  • Business Applications 
  • Benefits of Data Science 
  • Challenges of Data Science 

Data Science Context & Classification

  • Data Science Context : Data Mining / Business Intelligence / Data Science 
  • Perspective of Data Science 
  • Data Science Classification 
  • Various Types Of Data Science 

Data And Data Science Tools

  • Popular Tools for Data Science 
  • Data Sources 
  • Data Reliability and Validity

Data Science Workflow

  • Data Science Steps 
  • Recognize the Problem 
  • Define a Problem 
  • Structure the Problem 
  • Analyze the Problem 
  • Interpret the Results 
  • Implement Solution 
  • Crisp-Dm Reference Model

Data Science Introduction

  • Overview of Statistics 
  • Descriptive Statistics 
  • Inferential Statistics 
  • Basics Terminologies 
  • Cochran's Min Size Formula 
  • Types of Data 
  • Examples of Various Data 
  • Cochran’s Formula Example 
  • Examples of Variables 

Harnessing Data

  • Harnessing Data Introduction
  • Making Sense of the Data 
  • Sampling Methods 
  • Simple Random Sampling 
  • Stratified Sampling 
  • Systematic Sampling 
  • Biased Sampling Methods

Exploratory Data Analysis

  • Exploratory Data Analysis 
  • Measures of Central Tendencies 
  • Mean 
  • Median 
  • Mode 
  • Measures of Variability 
  • Range 
  • Calculating Standard Deviation

Histogram & Empirical Rule

  • Z- Score / Z-Value/ Standard Score 
  • Calculating Z-Score 
  • Histogram 
  • Empirical Rule 
  • Outliers 

Normal Distribution And Correlation

  • Normal Distributions, Mean, Variance 
  • Normality Testing
  • Skewness 
  • Kurtosis 
  • Correlation

Decision Modeling

  • Mathematical Modeling 
  • Decision Modeling 
  • Break Even Decision Model 
  • Prescriptive Model Pricing

Sales Promotion Model

  • Sales Promotion Decision 
  • Sales Prediction With Multiple Regression Analysis

Kerc Inc – Case Study: Predictive Analytics with Less Uncertainty

  • Kerc Inc – Car Manufacturer Case Study 
  • Kerc Inc Case Modeling 
  • Optimizing Kerc Production Model

Wonderzon Retailer : Case Study

  • Wonderzon Case Study: Problem Statement 
  • Wonderzon Case Modeling
  •  Predicting Optimum Logistics Cost

Predictive Analytics

  • Predictive Analytics Introduction 
  • Types of Predictive Analytics
  •  Application of Predictive Analytics

Regression

  • Mathematical Modeling Regression 
  • Simple Learning Regression 
  • Predicting Profit with Regression

Multiple Regression

  • Multiple Regression Modeling 
  • Predictive Analytics Summary

Smart It Inc Internet Usage - Plan Decision Predictive Analytics with High Uncertainty

  • Monte Carlo Simulation Introduction 
  • Smart It Inc. Internet Plan : Problem Statement 
  • Model Building 
  • Optimization and Plan Decision

Kickathlon Sport Retailer : Decision Tree

  • Kickathlon – Supplier Decision Making 
  • Decision Tree Convention 
  • Kickathlon – Supplier Decision Tree

Decision Tree – Decision Making Process

  • Decision Tree Convention 
  • Common Decision Strategies 
  • Maxi-Min Strategy 
  • Maxi-Max Strategy 
  • Maximize Expected Value Strategy 
  • Decision Trees with Monte Carlo Simulation Uncertain Output Range 
  • Decision Tree Summary

Tableau: Connecting to Data Source

  • Tableau Introduction 
  • Connecting to Various Data Sources 
  • Fixing Data Issues while Importing

Tableau: Basic Visualizations

  • Tableau Pane
  • Creating Basic Visualizations 
  • Insights for Data Through Visualizations 
  • Exploratory Data Analysis

Finding Insights

  • Stacked Bar Graph 
  • Deriving Insights Through Compound Plots

Time Series Forecasting

  • Forecasting Sales 
  • Adjusting Forecasting Parameters

Filters & Dashboards

  • Various Filters Options 
  • Interactive Filters 
  • Building Effective Dashboards

Publishing Insights

  • Various Publishing Options 
  • Tableau Packaged Workbook 
  • Summary

Who needs this course?

  • Senior professionals who wish to switch their career to Data Science
  • Chief executive officers, Directors and Decision-makers in the company
  • Professionals who have significant years of experience in the field

Prerequisite

  • Basic knowledge of working in the data science domain
  • Knowledge of Statistics and Mathematics and their relevance in Data Science
  • Should have an experience of working in a decision making role

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