- Web Scraping
- Automation
- Programming Principles
- Jupyter
- NumPy
- Data Import/Export
- Data Manipulation
- Application Programming Interface (API)
- Data Analysis
- JSON
- Restful API
- Object Oriented Programming (OOP)
Python for Data Science, AI & Development
Completed by Nicolas Suarez Piraquive
June 26, 2024
25 hours (approximately)
Nicolas Suarez Piraquive '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
