Data Analytics With Excel and Power BI

Data Analytics With Excel and Power BI, available at $19.99, has an average rating of 3.5, with 88 lectures, 9 quizzes, based on 45 reviews, and has 224 subscribers.

You will learn about You will gain an advanced level of awareness on the types of data, the role of a data scientist and the types of. You will learn how to use advanced Excel Statistical functions You will learn how to gather, transform, model and visualize data with Power BI You will gain an advanced level of awareness on the types of machine learning and how it works You will feel confident in implementing Excel and Power BI data solutions to your orginisations This course is ideal for individuals who are Those exploring the idea of moving into data analytics for their career or Those looking for bridging course to add to your current reporting skills or Business Owners or Accountants or Data enthusiastic or Those looking for a deep awareness of the field It is particularly useful for Those exploring the idea of moving into data analytics for their career or Those looking for bridging course to add to your current reporting skills or Business Owners or Accountants or Data enthusiastic or Those looking for a deep awareness of the field.

Enroll now: Data Analytics With Excel and Power BI

Summary

Title: Data Analytics With Excel and Power BI

Price: $19.99

Average Rating: 3.5

Number of Lectures: 88

Number of Quizzes: 9

Number of Published Lectures: 88

Number of Published Quizzes: 9

Number of Curriculum Items: 105

Number of Published Curriculum Objects: 105

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

You will gain an advanced level of awareness on the types of data, the role of a data scientist and the types of.
You will learn how to use advanced Excel Statistical functions
You will learn how to gather, transform, model and visualize data with Power BI
You will gain an advanced level of awareness on the types of machine learning and how it works
You will feel confident in implementing Excel and Power BI data solutions to your orginisations

Who Should Attend

Those exploring the idea of moving into data analytics for their career
Those looking for bridging course to add to your current reporting skills
Business Owners
Accountants
Data enthusiastic
Those looking for a deep awareness of the field

Target Audiences

Those exploring the idea of moving into data analytics for their career
Those looking for bridging course to add to your current reporting skills
Business Owners
Accountants
Data enthusiastic
Those looking for a deep awareness of the field

This course is an introduction level course to business and data analytics. The aim is to address several competencies, Data awareness, statistical applications in excel, business intelligence software and machine learning awareness.

The first competency is data trend awareness. What are the different fields? What are the different analysis types and tool? and what are the general buzz terms? By the end of this section you should have an advanced level of awareness on the types of data, the role of a data scientist and the types of.�

After this we ill look at Statistical application in Excel. By the end of this you should have the ability to carry out an interpenetrate the results from Descriptive Statistics, calculate probability and select samples and variables, Understand the power of hypothesis testing to solve business problems all within Excel

We will then move into power bi, and self-service tool for business intelligence. You will learn how do to simple transformations on data, how to model data using DAX and how to visualize data

When discussing data and business analytics you can not overlook machine learning. By the end of this course you will have an advanced level of awareness on how this works and where it can be applied.

By the end of this course you should feel comfortable Implementing business intelligence solutions to your organisation using tools such as Excel or Power BI that improve the current reporting system and add greater depth to the information to aid in the business decision making process.

Although this course only has 5 hours or so of video material, the reality is you should expect to take about 20 hours to really complete the course and gain full understanding. There are many activities to complete and it might be necessary to revisit tutorials to ensure you gained the knowledge that you want.

Course Curriculum

Chapter 1: Getting Started

Lecture 1: Introduction

Lecture 2: Competencies

Lecture 3: Tools Files and Data Sources

Lecture 4: What is big data?

Lecture 5: What is data science?

Lecture 6: How does analytics join big data with data science?

Chapter 2: Types of Data, Analytics and Tools

Lecture 1: What is categorical and numerical data

Lecture 2: What is exploratory analysis

Lecture 3: What is descriptive analysis

Lecture 4: What is Inferential analysis

Lecture 5: What is Predictive Analysis

Lecture 6: Casual and Mechanistic Analysis

Chapter 3: Descriptive Stats In Excel

Lecture 1: Descriptive Statistics In Excel

Lecture 2: Introduction to Histrograms

Lecture 3: How to create and Read a Histogram in Excel

Lecture 4: Understanding Box Plots

Lecture 5: How to create a boxplot in Excel

Lecture 6: Categorical and Numerical Data in Excel

Lecture 7: How to summarize Categorical Data with Pivot Tables

Lecture 8: Useful Excel Statistics Functions – descriptive statistics

Lecture 9: Useful Excel Statistics Functions – RANK, LARGE and SMALL

Lecture 10: Percentile Functions and Percentrank Functions

Lecture 11: Geometric Mean on Investment Returns

Chapter 4: Basics of Probability In Excel

Lecture 1: What is Probability

Lecture 2: COUNTIF to calculate probability

Lecture 3: What is the Law of Complements

Lecture 4: What are Mutually Exclusive and Independent Events

Lecture 5: Calculating Probability on Independent and mutually exclusive events

Lecture 6: What is conditional Probability

Lecture 7: How to Calculated Join Probability using HYPGEOM.DIST

Lecture 8: What is the law of Total Probability

Lecture 9: joint probability pivot table and probability examples

Chapter 5: Random Variables

Lecture 1: What are random Variables

Lecture 2: What are Binomia and Poissonl Random Variables

Lecture 3: solve problems using both BINOM.DIST and BINOM.DIST.RANGE

Lecture 4: how do you calculate Poisson probability in Excel?

Lecture 5: What is Normal Distribution

Lecture 6: Use NORM.DIST and NORM.INV to solve probability questions

Lecture 7: What is the Central Limit Theorem and how do you use Excel to solve probability

Lecture 8: What are Z scores and how are these calculated or used in Excel?

Chapter 6: Sampling In Excel

Lecture 1: What are Populations and Samples

Lecture 2: How to select a random sample using Excel

Lecture 3: What are Confidence Levels ?

Lecture 4: when you use CONFIDENCE.NORM and CONFIDENCE.T.

Lecture 5: How to estimate a sample size when using an estimated population mean

Lecture 6: example of calculating the population size when using an estimated population me

Chapter 7: Hypothesis Testing in Excel

Lecture 1: What is a hypothesis test?

Lecture 2: What is a Z-Test

Lecture 3: Z-test in Excel

Lecture 4: T.Test

Lecture 5: Correlation in Excel

Lecture 6: Using Excels Data Analysis ToolPak for Hypotheses testing

Chapter 8: Introduction to Power BI

Lecture 1: What is Power BI and how do I install it

Lecture 2: Tour around desktop

Lecture 3: Connecting to data

Lecture 4: sample connections and transformations

Lecture 5: relationships

Lecture 6: first visulisation

Lecture 7: What about calculations

Chapter 9: Introduction to Power Query

Lecture 1: Power Query tour

Lecture 2: Connect to excel and transform the data

Lecture 3: Duplicate querys and change query source

Lecture 4: Connecting to a folder

Lecture 5: other Common Transformations

Chapter 10: DAX and Introduction

Lecture 1: What is DAX

Lecture 2: Calculated Columns

Lecture 3: Measures

Lecture 4: X expressions

Lecture 5: Working with related tables

Chapter 11: Power BI – Visualization Canvas

Lecture 1: Visualization Canvas

Lecture 2: Tooltips and hierarchy

Lecture 3: Slicers

Lecture 4: Gauges

Instructors

Paula Guilfoyle CPA
CPA Accountant, & Life Long Learner

Rating Distribution

1 stars: 2 votes
2 stars: 3 votes
3 stars: 15 votes
4 stars: 14 votes
5 stars: 11 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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