- Jupyter
- Pandas (Python Package)
- Data Structures
- Object Oriented Programming (OOP)
- Web Scraping
- Data Analysis
- Data Manipulation
- File I/O
- Application Programming Interface (API)
- JSON
- Python Programming
- Computer Programming
Python for Data Science, AI & Development
Completed by DICK ABINATHANAEL TAKUNDA RUKANDA
August 17, 2022
25 hours (approximately)
DICK ABINATHANAEL TAKUNDA RUKANDA'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
