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The Ultimate Beginners Guide to Data Analysis with Pandas

Perfect introduction to data science & ai for beginners starting their learning journey.

Online Course
Self-paced learning
Flexible Schedule
Learn at your pace
Expert Instructor
Industry professional
Certificate
Upon completion
What You'll Learn
Get started with data science & ai from absolute basics
Understand core concepts and terminology
Master the fundamentals of data science & ai
Apply best practices and industry standards

Skills you'll gain:

Professional SkillsBest PracticesIndustry Standards
Prerequisites & Target Audience

Skill Level

BeginnerPerfect for those new to the subject

Requirements

No prior experience required
Basic computer literacy
Willingness to learn and practice
Access to a computer with internet connection

Who This Course Is For

Anyone interested in learning data science & ai
Career changers looking to enter the field
Students wanting to expand their skill set
Professionals seeking to understand the basics
Course Information

About This Course

Welcome to the "Ultimate Beginners Guide to Pandas for Data Analysis" course, a comprehensive journey designed for beginners interested in exploring the Pandas library in the context of data analysis. This course has been carefully structured to provide a solid understanding of Pandas fundamentals and advanced techniques, empowering students to manipulate data with confidence and efficiency. Check out the modules and main topics below:Section 1: SeriesWe start with Pandas installation and the creation of Series, the essential one-dimensional structure for storing data.

Throughout the module, we explore fundamental concepts such as slicing, copying, accessing with iloc and loc, sorting, filtering, mathematical operations, and string manipulations. We also cover advanced topics, including numerical and categorical grouping, handling missing values, functions, and practical challenges. Section 2: DataframeContinuing on, we delve into the creation and exploration of Dataframes, vital structures for analyzing more complex datasets.

This module covers topics such as accessing with iloc and loc, manipulation of rows and columns, handling duplicate data and missing values, sorting, advanced filtering, creating and manipulating columns, aggregation, pivot tables, concatenation, joining, and import/export techniques. We include practical challenges to reinforce learning. Section 3: Data VisualizationIn the final module, we explore data visualization with Pandas.

We cover the creation of line, bar, pie, scatter, and histogram plots, as well as formatting techniques and subplots. The module includes a practical challenge to apply the newly acquired skills in visualizing data. Upon completing this course, participants will be equipped with the practical skills necessary to effectively use Pandas in data analysis.

Provider
Udemy
Estimated Duration
8-15 hours
Language
English
Category
Technology & Programming

Topics Covered

Data Science & AIUiBeginner Friendly

Course Details

Format
Online, Self-Paced
Access
Lifetime
Certificate
Upon Completion
Support
Q&A Forum
Course Details
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This course includes:

Lifetime access to course content
Access on mobile and desktop
Certificate of completion
Downloadable resources

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