Description
Module 1: Introduction to Data Analysis
– Data analysis process.
– Data types and formats.
– Data analysis tools and libraries.
Module 2: Data Wrangling and Cleaning
– Data cleaning and preprocessing.
– Handling missing data.
– Data transformation and normalization.
Module 3: Exploratory Data Analysis (EDA)
– Descriptive statistics.
– Data visualization with Python (e.g., Matplotlib, Seaborn).
– Exploring data patterns and relationships.
Module 4: Data Analysis with Pandas
– Pandas library for data manipulation.
– Data aggregation and summarization.
– Advanced data analysis techniques.
Module 5: Data Visualization and Reporting
– Creating interactive visualizations (e.g., Plotly).
– Building dashboards.
– Communicating data insights effectively.

