Overview

Master Python programming for data analysis in this comprehensive course designed for aspiring data scientists. Through hands-on projects using real-world datasets, you'll learn essential data manipulation, visualization, and statistical analysis techniques while integrating modern AI tools and version control practices. This course is perfect for analysts and professionals who want to advance beyond spreadsheets to powerful programming solutions. Starting with Python fundamentals and progressing through advanced analysis techniques, you'll develop practical skills that directly apply to real-world data challenges. Upon completion, you'll be able to: • Import, clean, and manipulate data using Python's powerful libraries (Pandas, NumPy) • Create compelling visualizations with Matplotlib, Seaborn, and Plotly • Perform statistical analysis and A/B testing for data-driven decisions • Automate data workflows and generate professional reports • Implement version control best practices using GitHub

Syllabus

Introduction to Python and Environment Setup

In this module, you'll set up a powerful development environment, master essential Python syntax, and learn to leverage GitHub for seamless collaboration. By the module's end, you'll be equipped with the same foundational skills used by industry pros, including cutting-edge GenAI applications. Get ready to transform from a coding novice to a confident data explorer.

Data Loading and Manipulation

In this module, you'll develop essential skills for transforming raw data into analysis-ready formats - a critical foundation for any data science workflow. You'll master techniques for importing data from diverse sources, manipulating complex datasets, and optimizing data structures for analysis. Working with real-world datasets from our EngageMetrics and MediTrack case studies, you'll build practical experience in data preparation that directly translates to professional scenarios.

Data Exploration and Visualization

In this module, you'll learn to uncover and communicate insights through powerful data visualization techniques. You'll master both static and interactive visualization tools, from Matplotlib and Seaborn to Plotly, while conducting thorough exploratory data analysis. Using the EngageMetrics and MediTrack datasets, you'll develop the skills to transform complex data into compelling visual stories that drive decision-making.

Advanced Data Analysis Techniques

In this module, you'll elevate your analytical capabilities with advanced statistical methods and testing procedures. You'll learn to conduct hypothesis tests, design and analyze A/B tests, and automate analytical workflows. Working with real employee and medical data, you'll gain hands-on experience in applying sophisticated analytical techniques to solve complex business problems.

GitHub Integration

In this module, you'll learn to implement professional data science workflows using GitHub, AI-assisted documentation, and strategic version control. Working with the EngageMetrics employee dataset, you'll develop essential skills for collaborative data science projects. You'll learn version control best practices for Jupyter notebooks and discover how to leverage AI tools for efficient documentation. Throughout the module, you'll practice effective branching strategies that help manage complex analyses. Through hands-on labs and real-world scenarios, you'll gain practical experience that directly translates to professional data science work. By the end of this module, you'll be prepared to manage collaborative projects using industry-standard version control practices.

Data Science Workflow Capstone

This final module combines hands-on practice and focused assessment to validate your data science capabilities. You'll first work through a comprehensive TrendWave Media analysis project, then demonstrate your mastery through a targeted assessment covering key data science concepts and skills.