What's included

• Data Cleaning and Preprocessing

  Transforming raw data into a usable format by handling missing values, outliers, and inconsistencies.

• Exploratory Data Analysis (EDA)

  Analyzing data to identify patterns, trends, and relationships using various statistical methods and visualizations.

• Descriptive Statistics

  Summarizing key characteristics of the data with measures like mean, median, mode, standard deviation, etc.

• Hypothesis Testing

  Formulating and testing hypotheses about the data to draw conclusions and make informed decisions.

• Regression Analysis

  Modeling relationships between independent and dependent variables to understand how changes in one variable affect the other.

• Classification and Clustering:

  Segmenting data into groups based on similarities or differences.

• Data Visualization

  Creating charts, graphs, and other visual representations to communicate insights from the data effectively.