Mastering Exploratory Data Analysis (EDA) with Python

Mastering Exploratory Data Analysis (EDA) with Python, available at $44.99, with 17 lectures, and has 2 subscribers.

You will learn about Comprehensive Overview of Exploratory Data Analysis Data Validation Techniques Data Summarization Techniques Handling Missing Data Categorical Data Analysis Numeric Data Analysis Temporal Data Analysis Understanding Correlation Exploring Factor Relationships and Distributions Hypothesis Generation This course is ideal for individuals who are Data Analysts or Data Scientists or Business Analysts or Researchers or Students and Aspiring Data Professionals It is particularly useful for Data Analysts or Data Scientists or Business Analysts or Researchers or Students and Aspiring Data Professionals.

Enroll now: Mastering Exploratory Data Analysis (EDA) with Python

Summary

Title: Mastering Exploratory Data Analysis (EDA) with Python

Price: $44.99

Number of Lectures: 17

Number of Published Lectures: 17

Number of Curriculum Items: 17

Number of Published Curriculum Objects: 17

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will Learn

Comprehensive Overview of Exploratory Data Analysis
Data Validation Techniques
Data Summarization Techniques
Handling Missing Data
Categorical Data Analysis
Numeric Data Analysis
Temporal Data Analysis
Understanding Correlation
Exploring Factor Relationships and Distributions
Hypothesis Generation

Who Should Attend

Data Analysts
Data Scientists
Business Analysts
Researchers
Students and Aspiring Data Professionals

Target Audiences

Data Analysts
Data Scientists
Business Analysts
Researchers
Students and Aspiring Data Professionals

Embark on a transformative journey into the heart of data exploration with our comprehensive course, “Mastering Exploratory Data Analysis with Python.” This course is meticulously designed to equip you with the essential skills and techniques needed to unlock insights and unleash the full potential of your data. With Python as our primary tool, you’ll delve into the intricate world of exploratory data analysis (EDA), where every dataset tells a unique story waiting to be uncovered.

Through 12 in-depth modules, you’ll gain a profound understanding of EDA from every angle. From mastering data validation and summarization techniques to navigating outliers and handling missing data with confidence, you’ll build a solid foundation for effective data analysis. You’ll explore the nuances of categorical and numeric data analysis, learning how to uncover patterns, relationships, and distributions that lie beneath the surface.

But we don’t stop there. You’ll also dive into the fascinating realm of time series analysis, where you’ll dissect divorce filings data to uncover temporal patterns and trends. Armed with this knowledge, you’ll harness the power of correlation analysis and delve into the intricacies of factor relationships, paving the way for deeper insights into your data.

Whether you’re a seasoned data professional seeking to sharpen your skills or an aspiring data scientist eager to embark on your journey, this course is for you. Join us, and let’s embark on a transformative exploration of data together

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Python Code & DataSets

Chapter 2: Environment Installations

Lecture 1: Mastering Anaconda_ A Step-by-Step Guide to Installation and Configuration

Lecture 2: Exploring the Power of Python_ A Comprehensive Overview and Practical Guide

Chapter 3: Mastering Exploratory Data Analysis with Python Programing

Lecture 1: Comprehensive Overview of Exploratory Data Analysis

Lecture 2: Mastering Data Validation Techniques with Python

Lecture 3: Mastering Data Summarization Techniques with Python

Lecture 4: Strategies for Handling Missing Data

Lecture 5: Exploring Categorical Data Analysis in Python

Lecture 6: Exploring Numeric Data in Python

Lecture 7: Navigating Outliers: Strategies for Effective Data Analysis

Lecture 8: Exploring Patterns Over Time: Analyzing Divorce Filings Data

Lecture 9: Exploring Relationships: Understanding Correlation in Data Analysis

Lecture 10: Exploring Factor Relationships and Distributions

Lecture 11: Exploring Categorical Data: From Frequencies to Representation

Lecture 12: Navigating Data Science: The Art of Hypothesis Generation

Chapter 4: Bonus

Lecture 1: Special Gift for You

Instructors

Educonnhub
Offering premium courses crafted by top experts
Cu Dinh Tien
Vice Director of IT, Banking/Finance, Software Architect
Quan Pham
IT expert – Data specialist for banking industry
Dien Pham
Chief Data Officer, Enterprise Architect, IT Experts

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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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