Python Bootcamp for Data Analysis #7- EDA
- Development
- Apr 26, 2025

Python Bootcamp for Data Analysis #7: EDA, available at Free, has an average rating of 4.67, with 8 lectures, based on 3 reviews, and has 896 subscribers.
Free Enroll NowYou will learn about Conduct advanced functional exploratory data analysis Analyze categorical variables using various techniques Perform in-depth analysis of numerical variables Understand and apply correlation analysis to identify relationships between variables This course is ideal for individuals who are Beginner Python developers curious about advanced data analysis techniques or Data analysts and scientists looking to enhance their analytical skills or Students and researchers who need to perform comprehensive data analysis It is particularly useful for Beginner Python developers curious about advanced data analysis techniques or Data analysts and scientists looking to enhance their analytical skills or Students and researchers who need to perform comprehensive data analysis.
Enroll now: Python Bootcamp for Data Analysis #7: EDA
Summary
Title: Python Bootcamp for Data Analysis #7: EDA
Price: Free
Average Rating: 4.67
Number of Lectures: 8
Number of Published Lectures: 8
Number of Curriculum Items: 8
Number of Published Curriculum Objects: 8
Original Price: Free
Quality Status: approved
Status: Live
What You Will Learn
Who Should Attend
Target Audiences
Welcome to the seventh and final module of Miuul’s Python Bootcamp for Data Analysis!
This module is a crucial step in your journey as it introduces you to advanced data analysis techniques. We are excited to guide you through the foundational and advanced skills needed to perform comprehensive exploratory data analysis.
In this module, you’ll start with advanced functional exploratory data analysis, learning how to deeply explore your datasets. You’ll move on to analyzing categorical variables, with detailed lectures covering various techniques for understanding and interpreting these variables. We will also cover analyzing numerical variables, providing you with methods to extract meaningful insights from numerical data.
Additionally, you’ll learn how to capture variables effectively, analyze target variables to understand your data’s outcomes better, and perform correlation analysis to identify relationships between different variables.
This comprehensive exploration of advanced data analysis techniques will prepare you for real-world data challenges and enhance your ability to draw meaningful conclusions from complex datasets.
Join us at Miuul’s Python Bootcamp for Data Analysis, where learning to code becomes an adventure, empowering you to write, analyze, and innovate. Each analysis you perform brings you one step closer to mastering the art of data analysis with Python.
Course Curriculum
Chapter 1: EDA
Lecture 1: Course Materials
Lecture 2: Advanced Functional Exploratory Data Analysis
Lecture 3: Analyzing Categorical Variables I
Lecture 4: Analyzing Categorical Variables II
Lecture 5: Analyzing Numerical Variables
Lecture 6: Capturing Variables
Lecture 7: Analyzing Target Variable
Lecture 8: Correlation Analysis
Instructors

Miuul Data Science & Deep Learning
Data Science Team of Miuul.com
Rating Distribution
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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