In this course, 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.

Upon completion, you'll be able to: • Import data into Python from CSV files, Excel spreadsheets, and APIs. • Create, manage, and manipulate DataFrames. • Filter, sort, merge, and group data to prepare it for analysis. • Manage and transform categorical and date/time data using Pandas. • Create and manipulate NumPy arrays, perform mathematical operations, and use vectorized functions. • Apply data import and manipulation skills to build a multi‑source data integration pipeline in a graded challenge.

In this course, 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.

Upon completion, you'll be able to: • Perform hypothesis testing and correlation studies. • Design, conduct, and analyze A/B tests to compare different versions of an approach • Automate repetitive tasks, generate professional reports, and document workflows effectively using automated tools. • Tackle a challenge that integrates statistical analysis, A/B testing, and workflow automation to simulate real-world data problems.

This course equips you with professional version control strategies essential for collaborative data science projects. Beginning with fundamental GitHub integration for Jupyter notebooks, you'll establish a solid foundation in tracking, sharing, and managing analytical code.

As you progress, you'll discover how to leverage generative AI to streamline documentation processes and implement specialized branching strategies that support data science experimentation. Through hands-on labs using the EngageMetrics project, video instruction, and interactive sessions, you'll build a comprehensive version control workflow that enhances both individual productivity and team collaboration. Upon completion, you'll be able to: • Integrate Jupyter notebooks with GitHub for systematic version tracking and collaboration • Generate comprehensive documentation efficiently using AI-assisted techniques • Implement specialized branching strategies that support parallel data science experimentation • Create a professional-grade version control workflow that maintains project integrity while enabling innovation

This project-based course challenges you to demonstrate your data science mastery through a comprehensive real-world project using TrendWave Media's dataset. Beginning with industry expert insights into professional workflows, you'll establish a structured analytical approach to media engagement data before applying your skills independently in a guided project.

The course combines authentic business context with technical application, allowing you to integrate and showcase the full spectrum of your Python data science capabilities. Through hands-on analysis and focused assessment, you'll experience the complete lifecycle of a data science project—from initial exploration to delivering actionable recommendations—creating tangible evidence of your ability to derive value from complex datasets in professional contexts. Upon completion, you'll be able to: • Apply Python data science techniques to extract meaningful insights from real-world media engagement data • Implement professional data science workflows that follow industry best practices • Develop a portfolio-ready project that demonstrates your ability to solve business problems through data analysis • Demonstrate mastery of key data science concepts and techniques through comprehensive assessment