- Web Scraping
- Application Programming Interface (API)
- Data Manipulation
- NumPy
- Jupyter
- Data Analysis
- Pandas (Python Package)
- Scripting
- Data Processing
- Automation
- Data Import/Export
- Object Oriented Programming (OOP)
Python for Data Science, AI & Development
Completed by Daniel Yoonseo Kim
July 13, 2019
25 hours (approximately)
Daniel Yoonseo Kim's account is verified. Coursera certifies their successful completion of Python for Data Science, AI & Development
What you will learn
Develop a foundational understanding of Python programming by learning basic syntax, data types, expressions, variables, and string operations.
Apply Python programming logic using data structures, conditions and branching, loops, functions, exception handling, objects, and classes.
Demonstrate proficiency in using Python libraries such as Pandas and Numpy and developing code using Jupyter Notebooks.
Access and extract web-based data by working with REST APIs using requests and performing web scraping with BeautifulSoup.
Skills you will gain
