This Specialization equips learners with essential skills in Python-based data analysis using NumPy and Pandas. Starting with foundational numerical operations, learners progress to advanced data manipulation, cleaning, and transformation techniques. Through real-world datasets and case studies, participants will gain hands-on experience in building efficient workflows, handling missing values, managing time series, and applying advanced analytical techniques. By the end of the program, learners will be prepared to apply industry-relevant skills in data science, business intelligence, and analytics roles.



Data Analysis with NumPy and Pandas Specialization
Master Data Analysis with Python Libraries. Gain practical skills in NumPy and Pandas to clean, analyze, and transform real-world datasets.

Instructor: EDUCBA
Included with 
Recommended experience
Recommended experience
What you'll learn
Apply NumPy and Pandas to clean, analyze, and transform structured and unstructured datasets.
Build efficient data workflows, including aggregation, filtering, joins, pivots, and time series analysis.
Implement real-world projects to convert raw datasets into actionable business and data science insights.
Overview
Skills you'll gain
Tools you'll learn
What’s included

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October 2025
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from EDUCBA

Specialization - 3 course series
What you'll learn
Filter, group, aggregate, and reshape datasets using Pandas.
Handle missing values, manage indexes, and analyze time series.
Create pivot tables, crosstabs, and export data to CSV/Excel.
Skills you'll gain
What you'll learn
Perform numerical operations and memory optimization with NumPy.
Create, join, pivot, and clean Pandas DataFrames effectively.
Apply aggregation, filtering, and workflows on real datasets.
Skills you'll gain
What you'll learn
Manipulate arrays, linear algebra, and gradient descent in NumPy.
Clean, transform, and analyze retail datasets with Pandas.
Build pivot tables, groupby reports, and export business insights.
Skills you'll gain
Earn a career certificate
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Frequently asked questions
The Specialization can typically be completed in 10 to 11 weeks, with a recommended commitment of 3–4 hours per week. This flexible schedule is designed to accommodate both students and working professionals, allowing learners to progress at a steady pace while balancing other responsibilities. By the end of the program, participants will have gained a solid foundation in NumPy and Pandas, along with practical, hands-on experience applying these tools to real-world data analysis projects.
Learners should have a basic understanding of Python programming, including familiarity with variables, loops, and functions. No prior experience with NumPy or Pandas is required, as the courses are structured to build skills from the ground up.
Yes. The courses are designed to be taken in sequence, starting with foundational concepts in NumPy and Pandas before moving into advanced techniques and case study–based projects. This progression ensures that each new skill builds on the previous one, creating a smooth and structured learning path.
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Financial aid available,

