Data Science Competencies

This repository is designed to help you build the following core competencies:

Level 1: Foundation

• Programming: Python, R, SQL.
• Statistics: Descriptive statistics, probability basics.
• Tools: Jupyter Notebooks, Git/GitHub.

Level 2: Analysis & Visualization

• Data Manipulation: Pandas, NumPy, SQL joins.
• Visualization: Matplotlib, Seaborn, Tableau.
• Exploratory Data Analysis (EDA): Cleaning, profiling, and understanding data.

Level 3: Machine Learning

• Supervised Learning: Regression, Classification (Scikit-Learn).
• Unsupervised Learning: Clustering, Dimensionality Reduction.
• Model Evaluation: Cross-validation, metrics (RMSE, AUC-ROC).

Level 4: Advanced Specialization

• Deep Learning: PyTorch, TensorFlow, Keras.
• NLP: Text processing, Transformers, LLMs.
• Computer Vision: Image classification, Object detection.
• Deployment: MLOps, Docker, Cloud (AWS/Azure/GCP).