Git & GitHub for Data Scientists – Complete Workflow Guide 2026
Version control is not optional for professional data science. Without Git, every "working version" of your notebook is filename_v2_final_FINAL_v3.ipynb. Git tracks every change, lets you experiment safely on branches,...
Building Recommendation Systems in Python – Collaborative & Content-Based 2026
Recommendation systems drive billions of dollars in e-commerce, streaming, and social media revenue. Netflix's recommendations save $1 billion per year in prevented churn. Spotify's Discover Weekly keeps users engaged....
Data Visualisation with Matplotlib & Seaborn – Complete Guide 2026
A great visualisation can communicate a finding in seconds that a table of numbers cannot convey in minutes. Matplotlib is Python's foundational plotting library — powerful and precise, but...
Regular Expressions in Python – Complete re Module Guide 2026
Regular expressions (regex) are a mini-language for pattern matching in text. They are indispensable for data cleaning, log parsing, form validation, and text extraction. Python's built-in re module provides...
Time Series Analysis with Python – statsmodels, Prophet & LSTM 2026
Time series data is everywhere — stock prices, sales figures, website traffic, sensor readings, energy consumption. Unlike cross-sectional data, time series observations are ordered and dependent on past values....
