This repo serves as a workbook and resource for Applied Data Science with a Specialization in Python.
Data science comprises three distinct and overlapping areas: the skills of a statistician who knows how to model and summarize datasets (which are growing ever larger); the skills of a computer scientist who can design and use algorithms to efficiently store, process, and visualize this data; and the domain expertise—what we might think of as "classical" training in a subject—necessary both to formulate the right questions and to put their answers in context"
(Jake VanderPlas, Preface).
- Web Development with Python
- Web Scraping with Python
- MongoDB with Python
- Django with Python
- PyQt
- Data Visualization
- Python Basics
- Flow Control
- Functions
- Lists
- Dictionaries and Structuring Data
- Manipulating Strings
- Pattern Matching with Regular Expressions
- Reading and Writing Files
- Organizing Files
- Debugging
- Web Scraping
- Working with Excel Spreadsheets
- Working with PDF and Word Documents
- Working with CSV Files and JSON Data
- Keeping Time, Scheduling Tasks and Launching Programs
- Sending Email and Text Messages
- Manipulating Images
- Controlling the Keyboard and Mouse with GUI Animation
- Financial Modeling in Python :: Fletcher and Gardner
- Basic Mathematical Tools
- Market: Curves and Surfaces
- Data Model
- Timeline: Events and Controller
- The Hull-White Model
- Price Using Numerical Methods
- Pricing Financial Structures in Hull-White
- Black-Scholes Modeling