Free Certificate

Free Python Libraries Course Online with Certificate - 2025

Master core Python tools with this Python libraries free course. Learn how to manipulate data using NumPy, visualize insights with Matplotlib, and analyze datasets with Pandas.

15 hours of learning

NumPy

Vectors

Pandas

For enquiries call:
18002102020
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Key Highlights Of This Python Libraries Course

What You Will Learn

Matplotlib

After learning how to structure data using NumPy, this section equips you with the ability to visualize your data using Matplotlib, Python’s most widely used 2D plotting library.

Topics Covered

  • Creating and plotting graphs – Learn how to generate basic graphs such as line plots, bar charts, and scatter plots to represent trends and patterns in data.
  • Different chart types – Explore various chart formats—including histograms, pie charts, and stacked graphs—to communicate insights from diverse data structures.
  • Modification of charts – Gain control over chart aesthetics by adjusting titles, axes, legends, colors, and line styles to improve readability and presentation quality.

Pandas

Built on top of NumPy, Pandas is the go-to library for data manipulation and analysis in Python. This module introduces key techniques to clean, transform, and analyze structured data efficiently.

Topics Covered

  • Creating dataframes – Learn how to build dataframes—Pandas’ core data structure—from dictionaries, lists, or external data sources to structure your datasets effectively.
  • Import CSV files as Pandas dataframes – Import and manage data from CSV files, enabling you to handle real-world datasets in a structured and accessible format.
  • Reading and summarising dataframes – Use built-in methods to inspect, describe, and extract statistical insights from your datasets at a glance.
  • Sorting dataframes – Organize data based on one or more columns to uncover ordered relationships or prepare for deeper analysis.
  • Labelling, indexing and slicing data – Select specific data points or segments using intuitive labels or index positions to streamline data processing.
  • Merging dataframes using joins – Combine multiple datasets into one cohesive dataframe using inner, outer, left, or right joins—mirroring SQL operations.
  • Pivoting and grouping – Reshape datasets with pivot tables and perform aggregations using group-by functions to uncover trends and segment-level insights.

Python Libraries Course Certification

Earn and Share Your Certificate

Official & Verifiable

Receive a signed and verifiable e-certificate from upGrad upon successfully completing the course.

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Post your certificate on LinkedIn or add it your resume! You can even share it on Instagram or Twitter.

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Use your certificate to enhance your professional credibility and stand out among your peers!

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Why Choose This Free Python Libraries Course Online?

This Python Libraries course is more than just an introduction to NumPy, Pandas, and Matplotlib, it’s a gateway to building real-world data skills with zero financial commitment.

Here’s what makes this course worth your time:

  • Master the Most In-Demand Python Libraries from Scratch - Learn Python libraries like NumPy, Matplotlib, and Pandas, the powerful trio that drives modern data analysis.
  • Gain Job-Ready Skills for Real-World Roles - From building data pipelines with Pandas to drawing insights using Matplotlib, you’ll learn practical techniques that apply directly to roles like data analyst, marketing analyst, and business intelligence associate. These are the must-have skills employers look for in today’s data-driven world.
  • Boost Employability with Practical, Transferable Knowledge - Understand how to preprocess large datasets, generate insightful graphs, and manipulate arrays,all without prior experience. These data handling skills are not only valuable in tech, but also in finance, marketing, and operations roles where decisions are driven by data.
  • Get Certified with a Python Libraries Certification Online - After completing this free Python libraries course, you’ll receive a downloadable certificate that you can proudly share on your resume and LinkedIn profile.
  • Perfect for Freshers, Students & Career Switchers - This beginner-friendly course introduces everything step-by-step, making it the perfect entry point for those transitioning into data or tech from any field.

Key Features of This Free Python Libraries Course

This free Python libraries course is designed to help learners master the essential tools that power modern data analysis and machine learning. Whether you’re just starting with Python or looking to enhance your coding skills, this course makes learning simple, structured, and practical. 

Salient features of this free python libraries course  

100% Free with Verified Certificate - Enroll at no cost and earn a free Python certificate upon completion to validate your skills and strengthen your resume. 

Covers Major Python Libraries - Learn the most in-demand libraries, NumPy, Pandas, Matplotlib, and Scikit-learn, used by data analysts, engineers, and developers worldwide. 

Self-Paced, Beginner-Friendly Modules - The upGrad Python course is designed for beginners, allowing you to learn at your own pace with step-by-step coding tutorials and guided examples. 

Interactive Practice Sessions & Hands-On Projects - Work on real datasets, coding challenges, and exercises that help you apply concepts and gain practical experience using Python libraries. 

Accessible Anytime, Anywhere - Study flexibly on your laptop or mobile device. The Python libraries course free with certificate lets you learn whenever it suits you, at home, at work, or on the go.

Key Skills You Will Gain in This Python Libraries Course

Build hands-on coding and analytical skills with this free Python libraries course. From mastering data handling in NumPy and Pandas to creating impactful visualizations with Matplotlib, you’ll gain the practical knowledge needed to work confidently with data in Python. 

Skills you will learn  

  • NumPy Array Creation & Manipulation - Create and manage arrays for high-speed numerical and mathematical computations. 
  • Data Conversion in NumPy - Convert Python lists and tuples into NumPy arrays to handle large datasets efficiently. 
  • Array Inspection & Structure Understanding - Analyze shapes, data types, and dimensions to optimize performance. 
  • DataFrame Creation in Pandas - Build and manage DataFrames from multiple data sources for structured data analysis. 
  • Data Cleaning & Sorting - Clean, filter, and sort data to prepare it for deeper analysis. 
  • Indexing & Slicing in Pandas - Select specific data segments using labels or index positions for targeted analysis. 
  • Merging & Joining DataFrames - Combine datasets seamlessly using joins to create unified data views.
  • Pivoting & Grouping Data - Summarize and aggregate information to extract trends and insights. 
  • Creating Visualizations with Matplotlib - Generate line, bar, and scatter plots to visualize data effectively. 
  • Exploring Different Chart Types - Use histograms, pie charts, and stacked graphs to present diverse insights. 
  • Customizing Charts - Adjust chart titles, legends, axes, and colors for professional-quality visuals. 
  • Data Storytelling & Visualization - Present complex data clearly through meaningful, visually rich graphics.  

Who Should Enroll in This Course?

Whether you're new to Python or looking to upskill for data-driven roles, this Python libraries free course is designed to support a wide range of learners aiming to master practical tools like NumPy, Matplotlib, and Pandas.

This course is ideal for

  • Aspiring Data Scientists - Establish a strong foundation in core libraries that power data science workflows, from data wrangling to visualization.
  • Python Beginners - Move beyond the basics and apply your knowledge to real-world data handling and analytics tasks using industry-standard libraries.
  • Engineering & Computer Science Students - Enhance your academic and project work by integrating powerful data processing and visualization techniques into your Python toolkit.
  • Analytics Professionals - Upgrade your skill set by learning how to efficiently manipulate and visualize datasets for smarter, data-informed decision-making.
  • Career Changers in Tech - Break into data-centric roles with beginner-friendly, hands-on content, no prior Python experience required.
  • Researchers & Academics - Streamline your data processing and presentation workflows using scalable, open-source tools that support reproducible research.

What Makes This Course Different From Other Courses?

This Python libraries free course simplifies the learning curve by focusing on practical applications of NumPy, Matplotlib, and Pandas. The course skips the fluff and dives straight into data manipulation and visualization tasks that matter in practical scenarios.

How We Compare to Other Platforms:

Feature

This Course (upGrad)

Other Platforms

Course Fee

100% Free Python Libraries Course

Requires payment or limited free access

Lifetime Access

Unlimited lifetime access

Content often expires or is restricted

Certification

Free digital certificate upon completion

Certificates are usually paid

Hands-On Learning

Practical use of NumPy, Matplotlib & Pandas with real datasets

May stick to theoretical examples or outdated libraries

Beginner-Friendly Approach

No prior coding or data experience needed

Often assumes prior exposure to Python or analytics

Job-Relevant Skills

Teaches data wrangling, visualization, and analysis

May skip application-focused training

Learning Flexibility

100% self-paced with no deadlines

Fixed schedules and instructor timelines

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Frequently Asked Questions Free Python Libraries Course Online

A Python libraries course helps you master the most popular tools used for data science, analytics, and programming, like NumPy, Pandas, and Matplotlib. Learning these libraries makes data handling, visualization, and computation much easier. Whether you’re a beginner or a professional, this course gives you the practical coding skills needed for real-world projects. 

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