- Automation
- Python Programming
- Object Oriented Programming (OOP)
- Pandas (Python Package)
- Computer Programming
- Scripting
- Data Import/Export
- Data Analysis
- Jupyter
- Restful API
- Data Structures
- NumPy
Python for Data Science, AI & Development
Completed by Rachel Elam
December 1, 2023
25 hours (approximately)
Rachel Elam'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
