- Exam(s) / assessment(s) is included in price
- Tutor is available to students
Price, Retail Marketing & Excel Analytics With Machine Learning
Knowledge Door
5 Courses Bundle Certified By CPD | Learn From Experts | **Tutor Support & MCQ Assessment Included** | 100% Pass Rate
Summary
Overview
CPD
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Description
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The Price, Retail Marketing & Excel Analytics With Machine Learning is one of our most popular training courses and is perfect for those individuals who want to start a new career path as a data scientist, machine learning engineer, marketing analyst & retail manager, as well as established professionals who want to test their existing abilities and learn the latest techniques.
Course Curriculum
This comprehensive Price, Retail Marketing & Excel Analytics With Machine Learning course has been divided into 5 interactive lessons. This makes for a more stimulating and comprehensive study of all the essential areas of Linear regression, marketing & retail analytics and management, which also means that learners will be able to absorb the knowledge in manageable and intuitive segments and retain the vital information without even realising it.
This fully inclusive Price, Retail Marketing & Excel Analytics With Machine Learning course includes the following modules:
Learn how to increase your expertise in Linear regression, marketing & retail analytics and management by taking the following modules of this popular Price, Retail Marketing & Excel Analytics With Machine Learning course.
**Pricing Strategy and Analytics**
Introduction
- Welcome to the course
Step 1: Pricing Policy and Pricing Objective
- 6 Steps of Setting a Pricing Policy
- Different Pricing Objectives
Step 2: Estimating Demand
- Estimating Demand
- Forms of Demand Curve
- Excel: Estimating Linear Demand Curve
- Excel: Estimating Power Demand curve with Elasticity
Step 3: Estimating Costs
- Estimating the cost function
- Excel: Modeling Cost Function and Maximizing Profit
- Including effect of complementary goods
- Excel: Effect of complementary goods
Step 4: Analyzing competitors
- Analyzing Competitors
Step 5a : Price Bundling Strategy
- Price Bundling
- Types of Bundling
- The Bundling Problem
- Excel: Solving Bundling problem Part 1
- Excel: Solving Bundling problem Part 2
- Excel: Solving Bundling problem (Price Reversal)
**Pricing Strategies and Price Analytics**
Introduction
- Introduction
Lifetime Customer value
- Lifetime Customer Value – Key Concepts
- Lifetime Customer Value – Excel model
Variations and Sensitivity Analysis
- Sensitivity Analysis in Excel
- Variations in finding customer value
Monte Carlo Simulation
- Monte Carlo Simulation – Introduction
- Monte Carlo Simulation – Example
- Problem Statement
- Monte Carlo Simulation in Excel: Part 1
- Monte Carlo Simulation in Excel: Part 2
- Monte Carlo Simulation in Excel: Part 3
The following module of the Price, Retail Marketing & Excel Analytics With Machine Learning course will give the exact set of skills and information base that you’ll need to succeed in your chosen career path of Linear regression, marketing & retail analytics and management.
**Retail Business Management and Retail analytics**
Course Introduction
- Introduction
Part 1: Forecasting
- Basics of Forecasting
- Creating Linear Model with
1.1 Getting Data ready for Regression Model
- Gathering Business Knowledge
- Data Exploration
- The Data and the Data Dictionary
- Univariate analysis and EDD
- Discriptive Data Analytics in Excel
- Outlier Treatment
- Identifying and Treating Outliers in Excel
- Missing Value Imputation
- Identifying and Treating missing values in Excel
- Variable Transformation in Excel
- Dummy variable creation: Handling qualitative data
- Dummy Variable Creation in Excel
- Correlation Analysis
- Creating Correlation Matrix in Excel
1.2 Forecasting using Regression Model
- The Problem Statement
- Basic Equations and Ordinary Least Squares (OLS) method
- Assessing accuracy of predicted coefficients
- Assessing Model Accuracy: RSE and R squared
- Creating Simple Linear Regression model
- Multiple Linear Regression
- The F – statistic
- Interpreting results of Categorical variables
- Creating Multiple Linear Regression model
1.3 Handling Special events like Holiday sales
- Forecasting in presence of special events
- Excel: Running Linear Regression using Solver
- Excel: Including the impact of Special Events
1.4 Identifying Seasonality & Trend for Forecasting
- Models to identify Trend & Seasonality
- Excel: Additive model to identify Trend & Seasonality
- Excel: Multiplicative model to identify Trend & Seasonality
Market Basket Analysis
- Market Basket and Lift – Introduction
- Named Ranges – Excel
- Indirect Function – Excel
- 2-way lift calculation in Excel
- 2-way lift calculation – Dynamic
- 2-way lift data table creation
- 3-way lift calculation
- Store Layout optimization using Lift values
**Machine Learning**
Welcome to the course
- Introduction
Setting up R Studio and R crash course
- Installing R and R studio
- Basics of R and R studio
- Packages in R
- Inputting data part 1: Inbuilt datasets of R
- Inputting data part 2: Manual data entry
- Inputting data part 3: Importing from CSV or Text files
- Creating Barplots in R
- Creating Histograms in R
Basics of Statistics
- Types of Data
- Types of Statistics
- Describing the data graphically
- Measures of Centers
- Measures of Dispersion
Data Preprocessing for Regression Analysis
- Gathering Business Knowledge
- Data Exploration
- The Data and the Data Dictionary
- Importing the dataset into R
- Univariate Analysis and EDD
- EDD in R
- Outlier Treatment
- Outlier Treatment in R
- Missing Value imputation
- Missing Value imputation in R
Linear Regression Model
- The problem statement
- Basic equations and Ordinary Least Squared (OLS) method
- Assessing Accuracy of predicted coefficients
- Assessing Model Accuracy – RSE and R squared
- Simple Linear Regression in R
**Excel Analytics - Linear Regression Analysis**
Getting Data Ready for Regression Model
- Transportation Problem in Excel using Goal Seek
- Gathering Business Knowledge
- Data Exploration
- The Data and the Data Dictionary
- Univariate analysis and EDD
- Discriptive Data Analytics in Excel
- Outlier Treatment
- Identifying and Treating Outliers in Excel
- Missing Value Imputation
Creating Regression Model
- The Problem Statement
- Basic Equations and Ordinary Least Squares (OLS) method
- Assessing accuracy of predicted coefficients
- Assessing Model Accuracy: RSE and R squared
- Creating Simple Linear Regression model
- Multiple Linear Regression
- The F – statistic
- Interpreting results of Categorical variables
Certificate of Achievement from Knowledge Door
On completion of the Price, Retail Marketing & Excel Analytics With Machine Learning course, you will be eligible to obtain the certificate of achievement from Knowledge Door to evidence your new skill and accomplishment, as well as your knowledge and skill set. The certification is available in PDF format, at the cost of £12, or a hard copy can be sent via post at the cost of £35.
Who is this course for?
This comprehensive Price, Retail Marketing & Excel Analytics With Machine Learning course is ideal for anyone who is looking to improve their skills and move on to more challenging roles in this sector. Completion of the Price, Retail Marketing & Excel Analytics With Machine Learning course will prove your learning potential and provide the impetus to boost their career into whatever direction they choose but gaining an up-to-date perspective of everything involving Linear regression, marketing & retail analytics and management.
The Price, Retail Marketing & Excel Analytics With Machine Learning course will provide both established professionals and relative newcomers to Linear regression, marketing & retail analytics and management with some real advantages, earning extensive knowledge acquiring new skills which will make any candidate’s CV stand out in a crowded marketplace.
Requirements
There is no previous experience or specific entry requirements needed to enrol into this Price, Retail Marketing & Excel Analytics With Machine Learning course, any student from any background, and of any age, can enrol into this course and learn at their own pace.
As long as you are seventeen years old, have a basic knowledge of the Linear regression, marketing & retail analytics and management and are relatively comfortable with rudimentary IT skills, you will be eligible to enrol into this Price & Excel Analytics With Machine Learning course.
Career path
This Price & Retail Marketing With Machine Learning course will bring you new opportunities and new possibilities in an ever-changing job market. Gain the latest techniques, theories, knowledge and confidence that you’ll need to procure the dream job you’ve been looking for. To achieve all this and to gather more valuable credits on your CV, this course could be a critical part of your future.
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