Skip to content
Course Content
Introduction to Data Analytics
0/5
What is Data Analytics?
Data Types and Sources
The Role of a Data Analyst
Introduction to Data Analytics Quiz
Overview of the Data Analysis Process
Understanding Data: Types and Sources
0/5
Introduction to Data Types
Categorical Data: Nominal and Ordinal
Numerical Data: Discrete and Continuous
Data Sources: Primary vs. Secondary
Quiz on Data Types and Sources
Data Collection and Cleaning Techniques
0/4
Introduction to Data Collection Methods
Understanding Data Sources
Techniques for Data Cleaning
Data Cleaning Challenges
Exploratory Data Analysis and Visualization
0/5
Introduction to Exploratory Data Analysis
Visualizing Data with Matplotlib and Seaborn
Descriptive Statistics for EDA
EDA and Visualization Techniques Quiz
Handling Missing Data in EDA
Concluding Insights and Future Trends in Data Analytics
0/5
Summarizing Key Concepts in Data Analytics
Emerging Trends in Data Analytics
The Role of Data Analytics in Industry 4.0
Final Assessment: Concluding Insights and Future Trends
Preparing for a Career in Data Analytics
Data Analytics Essentials: Master the Basics

Learn how to identify and handle missing data during the EDA process. This lesson covers various methods such as imputation and removal, emphasizing their impact on data analysis and visualization.

Previous
Next