Python for Data Analysis & Web Scraping
Master Python fundamentals and use it for essential Data Analysis and Web Scraping tasks.
Beyond development, Python is the language of data. This course focuses on practical skills: cleaning, analyzing, and visualizing data using key libraries (Pandas/Matplotlib) and collecting data from the web (Beautiful Soup/Scrapy).
Master Python syntax, functions, and data structures.
Use Pandas to manipulate, clean, and analyze datasets.
Create visualizations using Matplotlib and Seaborn.
Collect data from websites using Beautiful Soup and Requests.
Meet Your Mentors
Yamlak N.
Data Analyst & Python Instructor
Expert in modern web frameworks and best practices.
Detailed Course Curriculum
Python Setup & Basics
Install Python/IDE. Variables, operators, and basic I/O.
Data Structures
Mastering Lists, Dictionaries, Tuples, and Sets.
Control Flow & Functions
Conditionals, Loops, and writing reusable functions.
File Handling & Modules
Reading/writing CSVs and using standard library modules.
Intro to Pandas
Loading data into DataFrames, selection, and indexing.
Data Cleaning
Handling missing values, duplicates, and data transformation.
Data Aggregation
Using `groupby`, pivoting, and merging DataFrames.
Visualization with Matplotlib
Creating basic plots: bar charts, line graphs, and histograms.
Web Scraping: Requests & HTML
Understanding HTTP, web structure, and fetching pages.
Beautiful Soup
Parsing HTML and extracting specific data elements.
Advanced Scraping & Data Storage
Handling pagination and storing scraped data in a database/file.
Mini Project: Stock Data Analysis
Complete a project involving fetching and visualizing financial data.