Data Science

This program provides a complete pathway to becoming a skilled Data Scientist, covering both fundamental concepts and advanced techniques. Across structured modules, you’ll progress from data handling and visualization to advanced machine learning, deep learning, and real-world production deployment. In the Basic Data Science track, you will learn: - Python for data handling (NumPy, Pandas, Matplotlib) - Data collection, cleaning, and transformation - Exploratory Data Analysis (EDA) with visualization tools - Introduction to machine learning (regression & classification) - Beginner projects like student score analysis, Titanic dataset EDA, and sales data analysis - In the Advanced Data Science track, you will dive into: - Working with large datasets, SQL queries, and data pipelines - Advanced statistics & probability (hypothesis testing, Bayesian methods) - Machine learning with ensemble methods, regularization, dimensionality reduction, and hyperparameter tuning - Deep learning with TensorFlow/Keras, including CNNs for image data and NLP for text analysis - Model deployment with Flask, FastAPI, and Streamlit, plus CI/CD practices for ML models Hands-on projects include fraud detection, recommendation systems, and house price prediction, culminating in a Capstone Project: AI-Powered Predictive Maintenance in IoT Systems – where you’ll use sensor data to predict machine failures with ML and LSTM models, deploying the solution in a production-ready environment. By completing this program, you will gain the skills to work confidently in Data Science, Machine Learning, and AI-driven analytics, preparing you for careers as a Data Scientist, ML Engineer, or AI Specialist.