How to Read This Course
Namaskar mitrano! Mi Ravindra Bagale. Ha Data Science course mhanje majha classroom – fakt browser madhe. Technical goshti English madhe aahet; Chala mitrano openers, tips aani closing lines madhe aapli Marathi (thodi Hindi) aahe. Job madhe aani interview madhe tumhi English tech terms vaparnar aahat – dataframe, plot, notebook – te English madhech theva.
How this course is organised
- Main body is ENGLISH only. Code, Jupyter steps, pandas methods, chart names and interview answers stay in clear English so you can paste them at work.
- Roman Marathi appears in the classroom opener (
Chala mitrano), in Ravindra Bagale's Tip boxes, in the recap, and in the closing Samajla ka? line. Optional मराठी / हिंदी tabs may be added later for tips; do not wait for them to study. - Each numbered chapter starts with objectives, then concept sections (
## N.M), each with why → tiny example → steps → what you should see, plus at least one tip and one practice task. - No machine learning in this course. We stop at clean data, EDA, matplotlib/seaborn and storytelling. A separate AI/ML course will come later — do not look for sklearn here.
- Sister courses: Excel and Power BI teach spreadsheets and BI dashboards. This course moves the same Blinkit thinking into Python + Jupyter. Brief cross-links are fine; we do not re-teach PivotTables, Power Query UI or DAX.
- Code lives in fenced Python blocks. Copy into a Jupyter cell and run. The site does not embed
.ipynbfiles and never links to PDFs.
Conventions
| You see | Meaning |
|---|---|
df.head() |
Type this in a Jupyter code cell |
| Steps in Jupyter | Numbered vertical list — follow in order |
| ₹1,25,000 | Indian comma style (lakh / crore) |
| 14-03-2026 | Dates as dd-mm-yyyy; times are IST |
| BLK-… / AMN-… | Fictional Blinkit / Amazon Now order IDs |
Fictional data
Blinkit and Amazon Now figures in this course are fictional sample data for learning only. They do not show real company numbers. People names (Ravindra Bagale, Shraddha Bagale, Ruhi Bagale, Shahrukh, Amir, Salman, Zoya, Ravina, Raja, Rani) are for practice; e-mails use example.com.
Cities in every dataset: Pune, Solapur, Nashik, Sambhaji Nagar, Kolhapur, Nagpur.
Chala tar mag, suru karuya! Ghabru naka — ek ek chapter, roj thoda Jupyter practice, aani data science nakki yeil.