Applied Data Science & Predictive Analytics with Python

Course Overview

This program focuses on practical data handling and statistical modeling techniques used in real-world business environments. You will work directly with relational databases, process messy datasets, and build predictive machine learning models using industry-standard open-source libraries.

What You Will Learn

• Extract and clean raw data using Pandas and SQL queries.
• Build regression and classification models to solve real business problems.
• Evaluate model performance using cross-validation and standard metrics.
• Create clear data visualizations to communicate insights to non-technical stakeholders.

Syllabus Breakdown

• Module 1: Data Preparation & Exploration: Cleaning structured data, handling missing values, and exploratory analysis in Jupyter.
• Module 2: Database Querying with SQL: Multi-table joins, subqueries, group aggregations, and performance tuning.
• Module 3: Applied Machine Learning: Implementing decision trees, random forests, and linear models with Scikit-Learn.
• Module 4: Project Delivery & Reporting: Building reproducible notebooks, visual dashboards, and final model reports.

Who This Is For

Designed for analysts, software engineers, and researchers who need hands-on technical skills to process and model data effectively.