Udemy - Marketing Analytics Forecasting Models with Excel

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[GigaCourse.com] Udemy - Marketing Analytics Forecasting Models with Excel 1. Introduction
  • 1. Introduction.mp4 (14.4 MB)
  • 1. Introduction.srt (3.7 KB)
  • 1.1 00_INtro.pdf (455.0 KB)
10. Bonus Section
  • 1. Bonus Lecture.html (1.5 KB)
2. Basics of Forecasting
  • 1. Basics of Forecasting.mp4 (25.3 MB)
  • 1. Basics of Forecasting.srt (5.9 KB)
  • 1.1 01_reg_basics.pdf (195.2 KB)
  • 2. Course resources.html (0.1 KB)
  • 2.1 Files_forecasting.zip (2.9 MB)
  • 3. Creating Linear Model with Trendlines.mp4 (78.9 MB)
  • 3. Creating Linear Model with Trendlines.srt (7.9 KB)
3. Getting Data Ready for Regression Model
  • 1. Gathering Business Knowledge.mp4 (21.9 MB)
  • 1. Gathering Business Knowledge.srt (3.5 KB)
  • 1.1 03_01_PDE_Business_knowledge.pdf (153.9 KB)
  • 10. Variable Transformation in Excel.mp4 (54.1 MB)
  • 10. Variable Transformation in Excel.srt (3.8 KB)
  • 10.1 07_Dummy variable.xlsx (98.1 KB)
  • 11. Dummy variable creation Handling qualitative data.mp4 (40.6 MB)
  • 11. Dummy variable creation Handling qualitative data.srt (4.9 KB)
  • 11.1 04_11_Dummy_Var.pdf (163.0 KB)
  • 12. Dummy Variable Creation in Excel.mp4 (108.0 MB)
  • 12. Dummy Variable Creation in Excel.srt (6.8 KB)
  • 12.1 07_Dummy variable.xlsx (98.1 KB)
  • 13. Correlation Analysis.mp4 (80.1 MB)
  • 13. Correlation Analysis.srt (10.6 KB)
  • 13.1 04_10_Correlation.pdf (256.9 KB)
  • 14. Creating Correlation Matrix in Excel.mp4 (102.1 MB)
  • 14. Creating Correlation Matrix in Excel.srt (8.3 KB)
  • 14.1 08_corr.xlsx (96.9 KB)
  • 2. Data Exploration.mp4 (23.4 MB)
  • 2. Data Exploration.srt (3.6 KB)
  • 2.1 03_02_PDE_Data_exploration.pdf (322.9 KB)
  • 3. The Data and the Data Dictionary.mp4 (78.6 MB)
  • 3. The Data and the Data Dictionary.srt (7.8 KB)
  • 3.1 03_03_PDE_Raw_Data_Analysis_Uni.pdf (332.0 KB)
  • 4. Univariate analysis and EDD.mp4 (27.3 MB)
  • 4. Univariate analysis and EDD.srt (3.4 KB)
  • 4.1 04_House_Price.xlsx (104.8 KB)
  • 4.2 03_04_PDE_Univariate_Analysis_Uni.pdf (333.4 KB)
  • 5. Discriptive Data Analytics in Excel.mp4 (153.5 MB)
  • 5. Discriptive Data Analytics in Excel.srt (10.3 KB)
  • 5.1 05_Outlier.xlsx (104.9 KB)
  • 6. Outlier Treatment.mp4 (27.8 MB)
  • 6. Outlier Treatment.srt (4.5 KB)
  • 6.1 04_06_PDE_Outlier_Treatment.pdf (355.1 KB)
  • 7. Identifying and Treating Outliers in Excel.mp4 (64.4 MB)
  • 7. Identifying and Treating Outliers in Excel.srt (4.3 KB)
  • 7.1 05_Outlier.xlsx (104.9 KB)
  • 8. Missing Value Imputation.mp4 (27.6 MB)
  • 8. Missing Value Imputation.srt (4.1 KB)
  • 8.1 04_05_PDE_Missing_value.pdf (315.7 KB)
  • 9. Identifying and Treating missing values in Excel.mp4 (51.8 MB)
  • 9. Identifying and Treating missing values in Excel.srt (3.9 KB)
  • 9.1 05_Miss_val.xlsx (104.9 KB)
4. Forecasting using Regression Model
  • 1. The Problem Statement.mp4 (10.7 MB)
  • 1. The Problem Statement.srt (1.6 KB)
  • 1.1 05_01_Intro.pdf (239.3 KB)
  • 10. Assignment 1 Regression based Forecasting.html (0.2 KB)
  • 2. Basic Equations and Ordinary Least Squares (OLS) method.mp4 (50.2 MB)
  • 2. Basic Equations and Ordinary Least Squares (OLS) method.srt (9.9 KB)
  • 2.1 05_02_Simple_lin_reg.pdf (284.8 KB)
  • 3. Assessing accuracy of predicted coefficients.mp4 (104.4 MB)
  • 3. Assessing accuracy of predicted coefficients.srt (15.8 KB)
  • 3.1 05_03_Simple_lin_reg_Accuracy.pdf (332.7 KB)
  • 4. Assessing Model Accuracy RSE and R squared.mp4 (49.7 MB)
  • 4. Assessing Model Accuracy RSE and R squared.srt (8.0 KB)
  • 4.1 05_03_Simple_lin_reg_Accuracy.pdf (332.7 KB)
  • 5. Creating Simple Linear Regression model.mp4 (31.1 MB)
  • 5. Creating Simple Linear Regression model.srt (2.6 KB)
  • 6. Multiple Linear Regression.mp4 (38.9 MB)
  • 6. Multiple Linear Regression.srt (5.7 KB)
  • 6.1 05_04_Multiple_lin_reg.pdf (219.8 KB)
  • 7. The F - statistic.mp4 (64.1 MB)
  • 7. The F - statistic.srt (9.0 KB)
  • 7.1 05_05_F_stat.pdf (328.5 KB)
  • 8. Interpreting results of Categorical variables.mp4 (27.1 MB)
  • 8. Interpreting results of Categorical variables.srt (5.3 KB)
  • 8.1 05_06_Cat_var.pdf (155.5 KB)
  • 9. Creating Multiple Linear Regression model.mp4 (97.6 MB)
  • 9. Creating Multiple Linear Regression model.srt (8.0 KB)
  • 9.1 09_multiple.xlsx (100.5 KB)
5. Handling Special events like Holiday sales
  • 1. Forecasting in presence of special events.mp4 (9.0 MB)
  • 1. Forecasting in presence of special events.srt (3.2 KB)
  • 1.1 11_Special Events.pdf (204.1 KB)
  • 2. Excel Running Linear Regression using Solver.mp4 (111.7 MB)
  • 2. Excel Running Linear Regression using Solver.srt (8.4 KB)
  • 2.1 11_Solver_reg.xlsx (99.8 KB)
  • 3. Excel Including the impact of Special Events.mp4 (205.2 MB)
  • 3. Excel Including the impact of Special Events.srt (20.6 KB)
  • 3.1 12_SpecialEvents.xlsx (54.2 KB)
6. Identifying Seasonality & Trend for Forecasting
  • 1. Models to identify Trend & Seasonality.mp4 (39.1 MB)
  • 1. Models to identify Trend & Seasonality.srt (6.7 KB)
  • 1.1 12_Seasonality.pdf (204.1 KB)
  • 2. Excel Additive model to identify Trend & Seasonality.mp4 (89.6 MB)
  • 2. Excel Additive model to identify Trend & Seasonality.srt (9.4 KB)
  • 2.1 13_Seasonality.xlsx (20.3 KB)
  • 3. Excel Multiplicative model to identify Trend & Seasonality.mp4 (57.3 MB)
  • 3. Excel Multiplicative model to identify Trend & Seasonality.srt (6.1 KB)
  • 4. Moving Average Method.mp4 (9.6 MB)
  • 4. Moving Average Method.srt (1.6 KB)
  • 4.1 14_Moving_Avg.xlsx (12.7 KB)
  • 4.2 14_Moving_Average.pdf (119.3 KB)
  • 5. Quiz.html (0.2 KB)
  • 6. Excel Moving Average Method.mp4 (119.8 MB)
  • 6. Excel Moving Average Metho

Description

Udemy - Marketing Analytics Forecasting Models with Excel



Description

You're looking for a complete course on understanding Forecasting models to drive business decisions involving production schedules, inventory management, manpower planning, and many other parts of the business., right?

You've found the right Marketing Analytics: Forecasting Models with Excel! This course teaches you everything you need to know about different forecasting models and how to implement these models in Excel using advanced excel tool.

After completing this course you will be able to:

Implement forecasting models such as simple linear, simple multiple regression, Ratio to Moving Average, Winter's method for exponential smoothing with trend and seasonality, famous Bass diffusion model and many more.
Increase revenue/profit of your firm by implementing accurate forecasting using Excel solver Add-in
Confidently practice, discuss and understand different Forecasting models used by organizations

How this course will help you?

A Verifiable Certificate of Completion is presented to all students who undertake this Marketing Analytics: Forecasting Models with Excel course.

If you are a business manager or an executive, or a student who wants to learn and apply forecasting models in real world problems of business, this course will give you a solid base by teaching you the most popular forecasting models and how to implement it.

Why should you choose this course?

We believe in teaching by example. This course is no exception. Every Section’s primary focus is to teach you the concepts through how-to examples. Each section has the following components:

Theoretical concepts and use cases of different forecasting models
Step-by-step instructions on implement forecasting models in excel
Downloadable Excel file containing data and solutions used in each lecture
Class notes and assignments to revise and practice the concepts

The practical classes where we create the model for each of these strategies is something which differentiates this course from any other course available online.

What makes us qualified to teach you?

The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using Analytics and we have used our experience to include the practical aspects of Marketing and data analytics in this course

We are also the creators of some of the most popular online courses - with over 170,000 enrollments and thousands of 5-star reviews like these ones:

This is very good, i love the fact the all explanation given can be understood by a layman - Joshua

Thank you Author for this wonderful course. You are the best and this course is worth any price. - Daisy

Our Promise

Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.

Download Practice files, take Quizzes, and complete Assignments

With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning.

What is covered in this course?

Marketing Analytics: Forecasting Models with Excel Understanding how future sales will change is one of the key information needed by manager to take data driven decisions. In this course, we will explore how one can use forecasting models to

See patterns in time series data
Make forecasts based on models

Let me give you a brief overview of the course

Section 1 - IntroductionIn this section we will learn about the course structure
Section 2 - Basics of ForecastingIn this section, we will discuss about the basic of forecasting and we will also learn the easiest way to create simple linear regression model in Excel
Section 3 - Getting Data Ready for Regression ModelIn this section you will learn what actions you need to take a step by step to get the data and then prepare it for the analysis these steps are very important.We start with understanding the importance of business knowledge then we will see how to do data exploration. We learn how to do uni-variate analysis and bi-variate analysis then we cover topics like outlier treatment and missing value imputation.
Section 4 - Forecasting using Regression ModelThis section starts with simple linear regression and then covers multiple linear regression.We have covered the basic theory behind each concept without getting too mathematical about it so that you understand where the concept is coming from and how it is important. But even if you don't understand it,  it will be okay as long as you learn how to run and interpret the result as taught in the practical lectures.We also look at how to quantify models accuracy, what is the meaning of F statistic, how categorical variables in the independent variables dataset are interpreted in the results.
Section 5 - Handling Special events like Holiday salesIn this section we will learn how to incorporate effects of Day of Week Effect, Month Effect or any special event such Holidays, pay day etc.
Section 6 - Identifying Seasonality & Trend for ForecastingIn this section we will learn about trends and seasonality and how to use the Solver to develop an additive or multiplicative model to estimate trends and seasonality. We will also learn how to use moving averages to eliminate seasonality to easily see trends in sales.
Section 7 - Handling Changing Trend & Seasonality over timeIn this section we will learn about Winter’s Method that changes trend and seasonal index estimates during each period has a better chance of keeping up with changes than other methods.
Section 8 - Forecasting models for New ProductsIn this section we will learn techniques to forecast new product sales. It is difficult to forecast when we have little or no historical data. The S curve can be used when we have little data and the famous bass diffusion model can be used to predict product sales even before the product is launched in the market.

I am pretty confident that the course will give you the necessary knowledge and skills to immediately see practical benefits in your work place.


Created by Start-Tech Academy
Last updated 4/2020
English
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Udemy - Marketing Analytics Forecasting Models with Excel


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3.3 GB
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Udemy - Marketing Analytics Forecasting Models with Excel


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