The Complete Data Analytics Course in Excel

The Complete Data Analytics Course in Excel, available at $74.99, has an average rating of 4.37, with 71 lectures, based on 954 reviews, and has 6274 subscribers.

You will learn about Data Analytics Data Visualization Hypothesis Testing Statistics Forecasting Excel Regression Monte Carlo Simulation Linear Programming Pivot Tables Business Intelligence Excel Analytics This course is ideal for individuals who are Operations managers or Quality professionals or Industrial Engineers or Data Analysts or casual Excel users curious about data science It is particularly useful for Operations managers or Quality professionals or Industrial Engineers or Data Analysts or casual Excel users curious about data science.

Enroll now: The Complete Data Analytics Course in Excel

Summary

Title: The Complete Data Analytics Course in Excel

Price: $74.99

Average Rating: 4.37

Number of Lectures: 71

Number of Published Lectures: 71

Number of Curriculum Items: 71

Number of Published Curriculum Objects: 71

Original Price: $74.99

Quality Status: approved

Status: Live

What You Will Learn

Data Analytics
Data Visualization
Hypothesis Testing
Statistics
Forecasting
Excel
Regression
Monte Carlo Simulation
Linear Programming
Pivot Tables
Business Intelligence
Excel Analytics

Who Should Attend

Operations managers
Quality professionals
Industrial Engineers
Data Analysts
casual Excel users curious about data science

Target Audiences

Operations managers
Quality professionals
Industrial Engineers
Data Analysts
casual Excel users curious about data science

Do you think you need to learn new software to perform data analysis, statistics, simulations? You don’t! Everything you need to get started in the world of data analytics is already on your computer in the wonderful application called Excel.

This course will first acquaint you with the Excel environment including how to use simple and complex functions, hot-key shortcuts and navigation tips to make sure you work efficiently and effectively. From there, I lead you in lectures and practice exercises on the fundamental topics of data analytics.

Data Visualizations – Visualizing data is an important part in analyzing data as well as presenting and explaining what it means. Lectures in this course Included how to craft and use bar charts, line charts, radial charts, histograms, box and whisker charts, pie charts, conditional formatting and Sparklines.

Pivot Tables – Pivot Tables are very powerful, simple to use tools built into excel. The lectures will include how to structure data to get the most out of pivot tables, and then a few use cases including root cause analysis, comparative analysis, along with other visualization tools specific to pivot tables.

Statistics – The Statistics module is by far the most densely packed module in this course. As a statistician by training, I present a deep dive into the data behind the statistics and how to use different statistical tests based on different circumstances. The module is filled with different lectures and exercises involving ANOVA tests, T Tests, Chi-Squared Tests, Tests for Normality, Regression Analysis and more.

Forecasting – Organizations have to be able to anticipate the future. The forecasting tools presented in this course help us accomplish this feat. Forecasting is presented in two different ways – Factor forecasting and Time Series forecasting. For each approach to forecasting, many tools and techniques are introduced and reviewed including Regression analysis, Monte Carlo Simulation, Simple Moving Averages, and Auto-Regressive techniques.

Excel Tools – Excel has a lot of useful tools that don’t quite fit neatly into any of the other modules. The last module of this course explores the use cases of using these tools. In particular, several archetypal problems are introduced and solved using the miscellaneous data analysis tools found in excel, including Excel Solver.

Course Curriculum

Chapter 1: Excel Environment and Excel Basics

Lecture 1: Navigation Part 1

Lecture 2: Navigation Part 2

Lecture 3: Basic Excel Formulas

Lecture 4: Structuring Data in Excel

Lecture 5: Intermediate Excel Functions

Lecture 6: Descriptive Statistics Part 1

Lecture 7: Descriptive Statistics Part 2

Lecture 8: Module #1 Practice & Solutions

Chapter 2: Visualizations

Lecture 1: Introduction to Visualizations and Pie Charts

Lecture 2: Histograms

Lecture 3: Bar Charts

Lecture 4: Line Charts

Lecture 5: Box and Whisker

Lecture 6: Radial Charts

Lecture 7: Combo Charts

Lecture 8: Scatter Plots

Lecture 9: Conditional Formatting Part 1

Lecture 10: Conditional Formatting Part 2

Lecture 11: Conditional Formatting Part 3

Lecture 12: Sparklines

Lecture 13: Appendix: Control Charts

Lecture 14: Module #2 – Practice & Solutions

Chapter 3: Pivot Tables, Charts and Slicers

Lecture 1: Introduction to Pivot Tables

Lecture 2: Root Cause Analysis

Lecture 3: Comparative Analysis

Lecture 4: Pivot Charts and Slicers

Lecture 5: Module #3 – Practice & Solutions

Chapter 4: Statistics: Hypothesis Testing and Regression

Lecture 1: Types of Data

Lecture 2: Fundamentals of Sampling

Lecture 3: Distributions Part 1

Lecture 4: Distributions Part 2

Lecture 5: Introduction to Hypothesis Testing

Lecture 6: T-tests Part 1

Lecture 7: T-tests Part 2

Lecture 8: T-tests Part 3

Lecture 9: Chi-Squared Test Part 1

Lecture 10: Chi-Squared Test Part 2

Lecture 11: Test for Normality Part 1

Lecture 12: Test for Normality Part 2

Lecture 13: ANOVA Part 1

Lecture 14: ANOVA Part 2

Lecture 15: Simple Regression Part 1

Lecture 16: Simple Regression Part 2

Lecture 17: Multi-Variate Regression Part 1

Lecture 18: Multi-Variate Regression Part 2

Lecture 19: Multi-Variate Regression Part 3

Lecture 20: Module 4 – Practice & Solutions

Chapter 5: Forecasting

Lecture 1: Introduction to Forecasting

Lecture 2: Factor Forecasting – Regression Part 1

Lecture 3: Factor Forecasting – Regression Part 2

Lecture 4: Factor Forecasting – Monte Carlo Simulation – Part 1

Lecture 5: Factor Forecasting – Monte Carlo Simulation – Part 2

Lecture 6: Factor Forecasting – Monte Carlo Simulation – Part 3

Lecture 7: Time Series Forecasting – The Simple Moving Average Part 1

Lecture 8: Time Series Forecasting – The Simple Moving Average Part 2

Lecture 9: Time Series Forecasting – Parameter Tuning Part 1

Lecture 10: Time Series Forecasting – Parameter Tuning Part 2

Lecture 11: Time Series Forecasting – Parameter Tuning Part 3

Lecture 12: Time Series Forecasting – Auto Regression

Lecture 13: Time Series Forecasting – Time Series ARMA

Lecture 14: Time Series Forecasting – Time Series ARIMA

Lecture 15: Module 5 – Practice Set #1 & Solutions

Lecture 16: Module 5 – Practice Set #2 & Solutions

Chapter 6: Miscellaneous Analytical Tools

Lecture 1: Intro and Goal Seek

Lecture 2: Scenario Analysis

Lecture 3: Data Tables

Lecture 4: Introduction to Excel Solver Tool

Lecture 5: Excel Solver Tool – The Backpack Problem

Lecture 6: Excel Solver Tool – The Mixing Problem

Lecture 7: Excel Solver Tool – The Traveling Salesman Problem

Lecture 8: Module 6 – Practice & Solutions

Instructors

Michael Parent
Principal – Michael Parent Consulting

Rating Distribution

1 stars: 11 votes
2 stars: 21 votes
3 stars: 97 votes
4 stars: 349 votes
5 stars: 476 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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