Name: Python Data Analysis - Matplotlib, Seaborn, Pandas & NumPy
Availability: InStock
Rating: 4.0 (1 reviews)

Python Data Analysis – Matplotlib, Seaborn, Pandas & NumPy by Muhammad Riaz Uddin is a hands‑on Udemy course that teaches you how to turn raw data into actionable insights. If you’re searching for a free Python data analysis course, an Udemy course on data visualization, or want to learn data analysis online in 2026, this updated (July 2026) program covers everything from core Python syntax to advanced plotting and basic machine‑learning concepts. The curriculum focuses on real‑world datasets, practical coding exercises, and a certification you can showcase on LinkedIn.

What You'll Learn

Build end‑to‑end data analysis pipelines using Pandas, NumPy, Matplotlib, and Seaborn.
Master data cleaning techniques, including handling missing values and type conversions.
Learn how to create static, interactive, and multi‑panel visualizations with Matplotlib and Seaborn.
Understand array operations, broadcasting, and linear‑algebra functions in NumPy for fast numerical computing.
Create descriptive statistics and exploratory data analysis reports that reveal hidden patterns.
Implement basic supervised‑learning algorithms and evaluate model performance with common metrics.
Apply API requests and web‑scraping methods to gather external data for analysis projects.
Analyze real‑world case studies, turning CSV files and API responses into polished visual dashboards.

Course Details

Instructor: Muhammad Riaz Uddin
Rating: 4.0 stars (reviews)
Language: English (en‑US)
Certificate: Yes, upon completion
Includes: Lifetime access, mobile‑friendly videos, downloadable resources

What This Course Covers

Python Fundamentals

Variables, data types, and operators in Python
Control flow structures: if/else, for and while loops
Function definitions, modules, and best coding practices

Data Manipulation with Pandas

Importing CSV, Excel, and JSON files into DataFrames
Cleaning data: handling nulls, duplicates, and type casting
Filtering, grouping, and pivoting for targeted analysis

Visualization with Matplotlib & Seaborn

Building basic line, bar, and scatter plots in Matplotlib
Customizing axes, legends, and figure aesthetics
Creating statistical visualizations (box, violin, heatmaps) with Seaborn

Numerical Computing with NumPy

Constructing one‑dimensional and multi‑dimensional arrays
Performing vectorized operations and broadcasting rules
Solving linear‑algebra problems: dot products, matrix inversion, eigenvalues

Machine‑Learning Basics & Model Evaluation

Overview of supervised learning concepts and terminology
Implementing regression and classification algorithms with scikit‑learn
Measuring accuracy, precision, recall, and using cross‑validation

APIs, Web Scraping & Real‑World Projects

Sending HTTP requests and parsing JSON responses
Extracting data from web pages using BeautifulSoup
Integrating scraped data into Pandas workflows for final reporting

Who Should Take This Course

Beginners who want to start a career in data analysis or data science.
Students and professionals seeking to add Python analytics to their skill set.
Business analysts, researchers, and engineers who regularly work with datasets.
Anyone aiming to create professional visual reports for stakeholders.
Developers transitioning to data‑focused roles and needing a solid Python foundation.

Prerequisites

No prior programming experience required — the course is beginner‑friendly.
Basic computer literacy (ability to install software and navigate file systems).
Recommended: a willingness to practice coding daily and explore sample datasets.

Why Enroll in This Course

This Udemy offering delivers a complete data‑analysis workflow without the need for multiple fragmented tutorials. A free coupon provides 100 % off for a limited time, making the certification truly cost‑free while the content remains up‑to‑date as of July 2026. Compared with other courses, it balances theory and hands‑on projects, ensuring you can apply every concept to real‑world problems immediately.

Course Highlights

Lifetime access to all video lectures and downloadable assets.
Self‑paced learning that fits any schedule, with mobile‑friendly playback.
Certificate of completion to showcase on professional profiles.
Real‑world datasets and step‑by‑step coding exercises for practical mastery.
30‑day money‑back guarantee for risk‑free enrollment.
Community Q&A where you can interact with the instructor and peers.

Frequently Asked Questions

Q: Is this course really free?
A: Yes. By applying the available Udemy free coupon, you can enroll at 100 % off. The coupon is valid for a limited period, so claim it soon to start learning without any payment.

Q: What will I learn in this Python data analysis course?
A: You will master Python basics, data cleaning with Pandas, numerical operations with NumPy, visual storytelling using Matplotlib and Seaborn, and introductory machine‑learning concepts. Each module includes hands‑on projects that reinforce the skills.

Q: Do I get a certificate after completing this course?
A: Absolutely. Udemy issues a digital certificate of completion once you finish all lectures and assignments, which you can add to your résumé or LinkedIn profile.

Q: Is this course suitable for beginners?
A: The curriculum starts with fundamental Python programming before moving to data‑analysis libraries, making it ideal for beginners with little or no prior coding experience.

Q: How long do I have to enroll for free?
A: The free coupon is available for a limited time; typically, Udemy coupons expire after a few weeks. Enroll as soon as possible to secure the 100 % discount and begin learning immediately.

Final Thoughts

Python Data Analysis – Matplotlib, Seaborn, Pandas & NumPy equips beginners and aspiring analysts with the tools to clean, explore, and visualize data confidently. Enroll today, claim the free coupon, and start turning raw numbers into clear insights—your data‑driven career begins now.