IBM : Python for Data Science, AI & Development
-
Acquired foundational Python programming skills: syntax, expressions, variables, data types, control flow, loops, functions, object-oriented programming.
-
Learned to manipulate, clean, and analyze data using Pandas and NumPy libraries in Jupyter Notebooks.
-
Gained experience accessing and processing external data sources: working with files (CSV, JSON), REST APIs, and web scraping using BeautifulSoup and requests libraries.
-
Developed skills for automating tasks and preparing data pipelines to support further data science or AI project work.
​​
Tools & Techniques:
-
Python basics: data structures, functions, classes, error handling.
-
Data manipulation & analysis: NumPy, Pandas.
-
Web data extraction: APIs (requests) & Web Scraping (BeautifulSoup).
-
Development environment: Jupyter Notebooks.