Languages: Python

Tools: Jupyter, Pandas, Numpy

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Session 1: Introduction to Data Analysis and Jupyter Notebooks

• Overview of data analysis and its importance
• Introduction to Jupyter Notebooks: installation, creating notebooks, basic operations
• Basics of Python for data analysis: variables, data types, basic operations

Session 2: Introduction to Pandas and Data Structures

• Installing and importing Pandas
• Introduction to Series and DataFrames: creation, basic methods
• Loading data into DataFrames from various sources (CSV, Excel)

Session 3: Data Cleaning and Preparation

• Handling missing data: detecting, dropping, filling in missing values
• Data type conversions
• Renaming, adding, and removing columns

Session 4: Data Exploration and Analysis

• Descriptive statistics: mean, median, mode, standard deviation
• Sorting, filtering, and grouping data
• Basic data visualization with Pandas and Matplotlib