Udemy – Python For Data Science In 2025 A-Z: EDA With Real Exercises 2025-1

Apr 18, 2025 - 18:43

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Python For Data Science In 2025 AZ: EDA With Real Exercises. This comprehensive course takes you from beginner to advanced level in data analysis with Python. Using the powerful Pandas library, you will learn how to clean, manipulate, and analyze large and complex data. This course is suitable for people who want to improve their data analysis skills or step into the world of data science. This course will enable you to become a professional data analyst.

What you will learn:

Strong foundation in data analysis with Python: Deep understanding of Pandas data structures (series, dataframes, and indexes)
Hundreds of methods and features: Learn a wide range of Pandas methods and features for data analysis
Big and complex data analysis: Ability to work with large and messy data files
Data preparation for machine learning: Preparing real data for use in machine learning algorithms
Fast and Efficient Data Manipulation: Mastering fast techniques for data manipulation
Essential Fundamentals for Data Analysts: Learn all the Pandas basics to become a professional data analyst.

Who is this course suitable for?

Beginner Python developers: interested in learning data science or data analytics
Data Analytics Beginners: Those who want to enter the world of data analytics
Students and professionals: People who want to improve their knowledge in data preprocessing for machine learning projects
Data analytics job seekers: Those who want to enhance their resume with Python data analysis tools

Course Details Python For Data Science In 2025 AZ: EDA With Real Exercises

Publisher: Udemy
Instructor: Pruthviraja L
Training level: Beginner to advanced
Training duration: 15 hours and 45 minutes
Number of lessons: 103

Course headings

Prerequisites for the Python For Data Science In 2025 AZ: EDA With Real Exercises course

Students must be willing to learn the Data Analysis with Python language
If you know the basics of Python that is fine and good
Basic or intermediate experience with Microsoft Excel or another spreadsheet software, but not necessary
Basic knowledge of data types (strings, integers, floating points, Booleans) etc, but not necessary
Basic programming knowledge or knowing any other programming languages will also help