📊 Master Data Science

Course Overview

This comprehensive Data Science course covers the entire workflow: data collection, cleaning, visualization, statistical analysis, and building machine learning models using Python. You will work on real-world datasets and build impressive portfolio projects.

Tech Stack You'll Master

What You'll Learn

• Python for Data Analysis — Master pandas, numpy, and data manipulation techniques
• Data Visualization — Create compelling visuals with matplotlib, seaborn, and plotly
• Statistics & EDA — Exploratory Data Analysis and statistical thinking
• Machine Learning Fundamentals — Classification, regression, and clustering with scikit-learn
• Model Evaluation & Tuning — Cross-validation, hyperparameter optimization, and performance metrics
• Real-World Projects — Build 5+ portfolio-ready data science projects
• Model Deployment — Deploy ML models to production using Flask/FastAPI

Syllabus (Modules)

1. Python Fundamentals & Data Libraries — Variables, functions, pandas, numpy basics
2. Exploratory Data Analysis (EDA) — Data cleaning, preprocessing, and visualization techniques
3. Statistical Analysis — Hypothesis testing, probability, and descriptive statistics
4. Supervised Learning Models — Linear regression, logistic regression, decision trees, random forests
5. Unsupervised Learning & Clustering — K-means, hierarchical clustering, PCA, dimensionality reduction
6. Model Evaluation & Optimization — Cross-validation, grid search, feature engineering
7. Real-World Capstone Project — End-to-end data science project with deployment