Course guide · Sharad Khare
Mastering Data Analysis & Visualization with Python
5+ real projects for data analysis and visualization with NumPy, Pandas, Matplotlib, Plotly, and Seaborn.
Videos stream on Udemy. This page is the full on-site guide — overview, audience, prerequisites, and learning outcomes — written by Sharad Khare.
Overview
Data analysis only creates value when others can see the story. This English course pairs five industry-style projects with NumPy, Pandas, Matplotlib, Plotly, and Seaborn so you learn to clean messy data, choose the right chart, and present findings that stakeholders actually use.
What you will learn
- Exploratory analysis workflows from raw CSV to insight
- Matplotlib customization: axes, legends, annotations, and themes
- Interactive charts with Plotly for dashboards and presentations
- Seaborn for statistical plots and distribution comparisons
- Choosing chart types that match the question — not the trend
- Five end-to-end projects you can showcase in interviews
Who this course is for
Analysts, researchers, and Python learners who know basics but need portfolio-ready visualization skills.
Prerequisites
Introductory Python. Familiarity with Pandas is helpful but taught where needed.
How enrollment works
Sharad Khare hosts structured video lessons on Udemy for convenient playback, progress tracking, and certificates. Use the button above to open the official course page. Pricing and promotions are set by Udemy. Many learners pair video lessons with the free note packs on this site’s Notes page for offline review.
Explore more courses
Fourteen structured programs in English and Hindi — Python, data science, machine learning, AI, and more.