What you'll learn
You will learn to clean and format data, including removing duplicates, handling missing data, and managing outliers to ensure data integrity.
You will learn advanced techniques for sorting and filtering data to efficiently extract relevant insights from large datasets.
You will learn how to apply conditional formatting in Excel to visually highlight key trends, insights, and anomalies within your data.
You will learn essential Excel formulas and functions such as SUM, AVERAGE, COUNT, IF statements and MORE, enabling you to manipulate data effectively.
You will learn to utilize Excel's lookup functions (VLOOKUP, HLOOKUP, XLOOKUP) to efficiently search for and retrieve specific information within datasets.
You will learn various graph and chart types in Excel for data visualization, including bar charts, pie charts, scatter plots, and more to communicate insights.
You will learn advanced analysis using PivotTables and PivotCharts, enabling you to analyze, and visualize complex datasets with ease and interactivity.
You will learn to use Excel's built-in data analysis tools for statistical analysis, i.e., descriptive statistics, t-tests, ANOVA, correlation, and regression.
You will learn to design and create dynamic DASHBOARD in Excel, by a visually interactive format for effective decision-making and reporting.
You will learn best practices for enhancing your Excel dashboard, including layout optimization, graphical elements, etc., to maximize impact and usability.
Requirements
Microsoft Excel Installed
Desktop/Laptop (Mac or Windows)
Dedication to learn
Description
Unlock the power of data analysis with Excel in this comprehensive course designed to take you from novice to proficient data analyst. Whether you're new to Excel or looking to expand your skills, this course equips you with the essential tools and techniques to excel in data analysis.Throughout the course, you'll dive deep into data cleaning and formatting, learning how to remove duplicates, handle missing data, and manage outliers effectively. You'll discover advanced sorting and filtering methods to extract valuable insights from complex datasets, and you'll master conditional formatting to visually highlight trends and anomalies.With a focus on practicality, you'll gain proficiency in essential Excel formulas and functions for calculations, date manipulation, and conditional operations. You'll also harness the power of lookup functions to quickly retrieve specific information, streamlining your analysis workflow.Data visualization is a key component of effective analysis, and you'll learn to create a variety of graphs and charts in Excel to communicate insights with clarity. From bar charts to scatter plots, you'll explore different visualization techniques to enhance data interpretation and presentation.PivotTables and PivotCharts offer dynamic ways to summarize and analyze data, and you'll learn how to leverage these tools for advanced analysis and visualization. Additionally, you'll delve into Excel's statistical analysis tools, performing tasks such as descriptive statistics, t-tests, correlation, and regression analysis.As you progress, you'll bring your newfound skills together to create dynamic dashboards in Excel, consolidating information into visually appealing and interactive formats for effective decision-making and reporting. You'll refine your dashboard with layout optimization and graphical elements, ensuring maximum impact and usability.By the end of this course, you'll emerge as a proficient Excel user, equipped with the knowledge and skills to tackle data analysis challenges confidently and efficiently. Whether you're a professional seeking to enhance your career prospects or a student aiming to develop practical Excel expertise, this course empowers you to master data analysis from zero to hero.
Overview
Section 1: Don't Ignore It. Start From Here!
Lecture 1 Instructions you MUST follow
Lecture 2 Excel functions and shortcuts cheatsheet
Section 2: Necessary Foundation of Data Analysis
Lecture 3 What is data analysis?
Lecture 4 Key components of data analysis
Lecture 5 Methods of exploratory data analysis Part 1
Lecture 6 Methods of exploratory data analysis Part 2
Lecture 7 Methods of exploratory data analysis Part 3
Section 3: Necessary Foundation of Statistical Analysis
Lecture 8 What is statistical data analysis?
Lecture 9 Population v/s sample and its methods
Lecture 10 Types of statistical data analysis
Lecture 11 Inferential statistics Part 1 – T-tests and ANOVA
Lecture 12 Inferential statistics Part 2 – Relationships measures
Lecture 13 Inferential statistics Part 3 – Linear regression
Section 4: Necessary Foundation on Hypothesis Testing
Lecture 14 Hypothesis testing for inferential statistics
Lecture 15 Selecting statistical test and assumption testing
Lecture 16 Confidence level, significance level, p-value
Lecture 17 Making decision and conclusion on findings
Lecture 18 Complete statistical analysis and hypothesis testing
Section 5: Data Cleaning and Formatting in Excel
Lecture 19 Identify and remove duplicates
Lecture 20 Dealing with missing values
Lecture 21 Defining and removing outliers
Lecture 22 Dealing with inconsistent values
Lecture 23 Text-to-columns for data separation
Section 6: Sorting and Filtering Datasets
Lecture 24 Sorting and filtering for data precision
Lecture 25 Advanced filtering with criteria
Section 7: Conditional Formatting for Tabular Analysis
Lecture 26 Highlighting cells based on conditions
Lecture 27 Findings top and bottom insights
Lecture 28 Creating color scales and color bars
Section 8: Formulas and Functions for Analyzing data
Lecture 29 SUM, AVERAGE, MIN, and MAX functions
Lecture 30 SUMIF, and AVERAGEIF functions
Lecture 31 COUNT, COUNTA, and COUNTIF functions
Lecture 32 YEAR, MONTH and DAY for date manipulation
Lecture 33 IF STATEMENTs for conditional operation
Lecture 34 VLOOKUP for column-wise insight search
Lecture 35 HLOOKUP for row-wise insight search
Lecture 36 XLOOKUP for robust & complex insight search
Section 9: Graphs and Charts for Data Visualization
Lecture 37 Data analysis with Stacked and cluster bar charts
Lecture 38 Data analysis with Pie chart and line chart
Lecture 39 Data analysis with Area chart and TreeMap
Lecture 40 Data analysis with Boxplot and Histogram
Lecture 41 Data analysis with Scatterplot and Combo chart
Lecture 42 Adjusting and decorating graphs and charts
Section 10: Advanced Analysis in PivotTables and PivotCharts
Lecture 43 PivotTables for group data analysis PART 1
Lecture 44 PivotTables for crosstab data analysis PART 2
Lecture 45 PivotCharts and Slicers for interactivity
Section 11: Data Analysis Tools for Statistical Analysis
Lecture 46 Descriptive statistics and analysis
Lecture 47 Independent sample t-test
Lecture 48 Paired sample t-test
Lecture 49 Analysis of variance – One way
Lecture 50 Correlation test - relationship measure
Lecture 51 Regression analysis - influence measure
Section 12: Building Dashboard in Excel
Lecture 52 Integrating analysis and graphs for dashboard
Lecture 53 Building a canvas for implementing dashboard
Lecture 54 Creating dashboard with drag and drops
Lecture 55 Final adjustment of dashboard elements
Section 13: Final Project - Data Analysis A-Z in Excel
Lecture 56 Final remark for you
Individuals aiming to develop comprehensive knowledge in data cleaning, analysis, visualization, and dashboard creation in Excel.,Beginners interested in learning practical Excel techniques for efficient data manipulation, visualization, and interpretation.,Professionals seeking to enhance their data analysis skills within the familiar environment of Microsoft Excel.
Homepage

https://www.udemy.com/course/data-analysis-a-z-in-microsoft-excel-zero-to-hero/