How To Be A Data Analyst: Essence Of Data Analysis

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Definition and role of Data analysis in the society

Lecture 3: Why Organisations and individuals need data analysis

Lecture 4: Definition of Data Analysis

Lecture 5: What is Data Analysis?

Lecture 6: Importance of data analysis for businesses

Lecture 7: How to use data analysis in your business

Lecture 8: Another reason Data Analysis is important

Lecture 9: How accurate data improves data analysis

Lecture 10: Data Analysis Steps

Lecture 11: Data Requirement Gathering

Lecture 12: Data Collection

Lecture 13: Data cleaning

Lecture 14: Data Analysis tools

Lecture 15: Data Interpretation

Lecture 16: Data Visualisation

Lecture 17: Types Of Data Analysis

Lecture 18: Diagnostic Analysis

Lecture 19: Predictive Analysis

Lecture 20: Prescriptive Analysis

Lecture 21: Statistical Analysis

Lecture 22: Text Analysis

Lecture 23: Data Analysis Methods

Lecture 24: Qualitative Data Analysis

Lecture 25: Quantitative Analysis

Lecture 26: Artificial Intelligence and Machine Learning

Lecture 27: Maths and Stats

Lecture 28: Graphs and Visualisation

Chapter 2: Data Analysis: Tools and Techniques

Lecture 1: Purpose of Data Analysis

Lecture 2: Example of Data Analysis

Lecture 3: Data Analysis Tools

Lecture 4: Types Of Data Analysis

Lecture 5: Text Analysis

Lecture 6: Statistical Analysis

Lecture 7: Descriptive Analysis

Lecture 8: Inferential Analysis

Lecture 9: Diagnostic Analysis

Lecture 10: Predictive Analysis

Lecture 11: Prescriptive Analysis

Lecture 12: Data Analysis Process

Lecture 13: Data Requirement Gathering

Lecture 14: Data Collection

Lecture 15: Data Cleaning

Lecture 16: Data Analysis

Lecture 17: Data Interpretation

Lecture 18: Data Visualisation

Lecture 19: Summary

Chapter 3: Common Statistical Analysis Methods

Lecture 1: The Four Common Methods Used For Statistical Analysis

Lecture 2: Mean

Lecture 3: How To Calculate Mean

Lecture 4: Standard Deviation

Lecture 5: How To Calculate Standard Deviation

Lecture 6: Variance

Lecture 7: Regression

Lecture 8: How To Calculate Regression

Lecture 9: Hypothesis Testing

Chapter 4: Essential Chart Types for Data Visualisation

Lecture 1: Introduction

Lecture 2: How To Choose A Chart Type

Lecture 3: The Foundational Four

Lecture 4: Bar Chart

Lecture 5: Line Charts

Lecture 6: Example Of A Line Chart

Lecture 7: Scatterplot

Lecture 8: Data Analysis Steps

Lecture 9: Example Of A Scatterplot

Lecture 10: Common Variations

Lecture 11: Histogram

Lecture 12: Example Of A Histogram

Lecture 13: Stacked Bar Chart

Lecture 14: Example Of A Stacked Bar Chart

Lecture 15: Bubble Plots

Lecture 16: Example Of A Bubble Plot

Lecture 17: Heatmaps

Lecture 18: Example Of A Heatmap

Lecture 19: More On Heatmaps

Lecture 20: Pie Charts

Lecture 21: More On Pie Charts

Lecture 22: Funnel Charts

Lecture 23: Adwords Conversion Funnel

Lecture 24: Map-Based Plots

Lecture 25: Choropleth

Chapter 5: Data Analysis Myths That Can Hamper Your Business

Lecture 1: Data Analysis Myths That Can Hamper Businesses

Lecture 2: Data Analysis Leads To New Discoveries

Lecture 3: Data Analysis Is To Expensive

Lecture 4: Data Analysis Is Too Time-Intensive

Lecture 5: You Need To Be An Analyst To Get Value From Data

Lecture 6: All Businesses Are Driven By Data

Lecture 7: There's No Reason To Track Bounce Rate

Lecture 8: Machine-made Decisions Eliminates Bias

Lecture 9: Data Analytics Leads To Job Loss

Lecture 10: The More Data You Gather, The Better

Lecture 11: Analysis Can Drive Your Business

Chapter 6: Companies That Use Big Data Analytics

Lecture 1: Top Data Analytics Companies Should Follow

Lecture 2: Reonomy