High-Growth AI Career
Data Science & ML power modern AI-driven products and decisions.
End-to-End Skills
From raw data to trained models and deployment.
Industry Projects
Work on real datasets from finance, healthcare, marketing & tech.
⭐ Core Roadmap
Complete journey from Python basics to machine learning & deployment.
1. Python for Data Science
Python fundamentals, NumPy, Pandas, data cleaning and preprocessing.
2. Statistics & Probability
Descriptive stats, probability, distributions, hypothesis testing.
3. Data Visualization & EDA
Matplotlib, Seaborn, exploratory data analysis and insights.
4. Machine Learning Foundations
Supervised vs unsupervised learning, model evaluation, bias-variance.
5. Supervised Learning
Linear & logistic regression, KNN, decision trees, random forest.
6. Unsupervised Learning
K-Means, hierarchical clustering, PCA & dimensionality reduction.
7. Advanced ML
Gradient boosting, XGBoost, model tuning and pipelines.
8. Model Deployment
Flask/FastAPI, REST APIs, basic cloud & ML project lifecycle.