Data Science Roadmap
Phase 1: Learn the Fundamentals
- Mathematics & Statistics – Probability, linear algebra, calculus.
- Python & R – Core programming languages for data science.
- Data Structures & Algorithms – Sorting, searching, trees, graphs.
Phase 2: Data Manipulation & Processing
- NumPy & Pandas – Handling large datasets.
- Data Visualization – Matplotlib, Seaborn, Plotly.
Phase 3: Databases & Big Data
- SQL – Querying relational databases.
- Big Data Technologies – Apache Spark, Hadoop.
Phase 4: Machine Learning
- Supervised Learning – Linear regression, decision trees, SVM.
- Unsupervised Learning – Clustering, dimensionality reduction.
- Deep Learning – TensorFlow, PyTorch, CNNs, RNNs.
Phase 5: Model Deployment
- Flask & FastAPI – Deploying ML models as web services.
- MLOps – Automating ML pipelines using Kubernetes, Docker.
