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Data Analysis with Pandas

Data Analysis with Pandas

Original price was: USD $40.00.Current price is: USD $20.00.

This course introduces learners to Pandas and its role in data analysis, including how to work with DataFrames, Series, rows, columns, and external files such as CSV and Excel. It covers essential data cleaning, exploration, grouping, aggregation, and basic statistical analysis techniques, along with real-world applications in business, research, visualization, and machine learning.

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Category:
Attribute
Detail
Format
Online, self-paced course
Level
Basic / Beginner
Duration
2–3 Weeks
Certification
e-Certification
Fee
Free Course
Tools
Python, Pandas, Data Analysis Basics
About the Course
The Data Analysis with Pandas course is a free, beginner-friendly self-paced program designed to help learners understand how to analyze and work with structured data using the Pandas library in Python.
The course introduces key concepts such as data loading, data cleaning, filtering, grouping, and basic analysis. Learners will explore how Pandas is used to handle datasets efficiently and generate meaningful insights. This course is ideal for beginners who want to start working with real data using Python.
Program Highlights
• Free beginner-level Pandas and data analysis course
• Online self-paced learning format
• Simple explanation of data manipulation concepts
• Covers data cleaning, filtering, and analysis basics
• Real-world examples using structured datasets
• Suitable for students and non-programmers
• e-Certification upon successful completion
Course Curriculum
Module 1: Introduction to Pandas and Data Analysis
  • What is Pandas?
  • Why Pandas is Used in Data Science
  • Introduction to DataFrames and Series
  • Applications of Data Analysis
Module 2: Working with Data in Pandas
  • Loading Data from Files: CSV and Excel
  • Understanding Rows and Columns
  • Selecting and Filtering Data
  • Basic Data Exploration
Module 3: Data Cleaning and Preparation
  • Handling Missing Values
  • Removing Duplicates
  • Data Transformation Basics
  • Preparing Data for Analysis
Module 4: Data Analysis Techniques
  • Grouping and Aggregation
  • Sorting and Summarizing Data
  • Basic Statistical Analysis
  • Identifying Trends and Patterns
Module 5: Applications and Next Steps
  • Using Pandas in Real-World Projects
  • Data Analysis in Business and Research
  • Introduction to Visualization and ML
  • Mini Learning Activity / Concept-Based Practice
Tools, Techniques, or Platforms Covered
Python
Pandas
Data Analysis
Data Cleaning
DataFrames
Real-World Applications
  • Analyzing datasets for business insights
  • Cleaning and preparing data for analysis
  • Understanding trends and patterns in structured data
  • Supporting research and academic projects
  • Preparing for advanced data science and machine learning learning
Who Should Attend & Prerequisites
  • This course is suitable for students, beginners, freshers, and professionals who want to learn data analysis using Python and Pandas.
  • It is also useful for learners from engineering, computer science, business, statistics, research, and non-technical backgrounds interested in data.

Prerequisites: Basic Python knowledge is helpful but not mandatory. Basic computer knowledge and interest in data analysis are sufficient.

Frequently Asked Questions
1. Is this Data Analysis with Pandas course free?
Yes. This is a free online self-paced course designed for beginners.
2. Do I need Python knowledge before joining?
Basic Python knowledge is helpful but not required, as the course introduces key concepts in a beginner-friendly way.
3. What will I learn in this course?
You will learn how to load, clean, manipulate, filter, group, summarize, and analyze data using Pandas.
4. Who can join this course?
Students, beginners, and professionals from any background interested in data analysis can join.
5. Will I receive a certificate?
Yes. Learners receive an e-Certification after completing the course.
6. What is Pandas used for?
Pandas is a Python library used for working with structured data, including loading datasets, cleaning data, filtering records, grouping information, and performing basic analysis.
7. Is this course suitable for non-programmers?
Yes. The course is beginner-friendly and suitable for non-programmers who want to understand data analysis with Python and Pandas from the basics.
8. What is the duration of this course?
The Data Analysis with Pandas course is designed as a 2–3 week online self-paced course.
9. Is this course useful before learning data science?
Yes. Pandas is widely used in data science, analytics, and machine learning workflows, making this course a useful foundation for advanced learning.
10. What makes this Pandas course beginner-friendly?
The course explains data loading, cleaning, filtering, grouping, summarizing, and basic analysis in simple language using structured dataset examples.
The Data Analysis with Pandas course provides a simple and structured introduction to handling and analyzing data using Python. It is an ideal starting point for learners who want to build practical data analysis skills for data science, analytics, and real-world projects.

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