Python for Data Science, 10 weeks guidelines for the hands-on projects in each week:
Week 1: Introduction to Python and Data Manipulation Hands-on Project: Write a Python program that takes user input and performs basic operations like arithmetic calculations, conditional statements, and loops. Practice using Python lists to manipulate and analyze data. Week 2: Data Analysis with Pandas Hands-on Project: Choose a dataset of your choice (e.g., CSV file, Excel sheet) and load it into a Pandas DataFrame. Perform data cleaning tasks such as handling missing values, removing duplicates, and transforming data types. Perform basic exploratory data analysis (EDA) tasks like calculating summary statistics, visualizing data distributions, and identifying correlations. Week 3: Data Visualization with Matplotlib and Seaborn Hands-on Project: Select a dataset and create visualizations using Matplotlib and Seaborn. Choose appropriate plot types (e.g., line plot, bar chart, scatter plot) to showcase different aspects of the data. Customize the visualizations by adding labels, titles,