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Data_Science

==================LAB TASKS==================

Task 01: Exploration of Python Modules, Data Types and Function for Data Collection.

Task 02: Discriptive Stastics.

Task 03: Exploratory Data Analysis: Variance, Standard Derivation, Summarization, Distribution and Statistical Inference.

Task 04: Data Distributions using Box Plot and Scatter Plot, Outliers using Plot on Sample Dataset (IRIS DATASET).

Task 05: X,Y Graph, Bar-Chart, Histogram and Pie Chart.

Task 06: Correlation and Covariance Analysis (Heart_disease_pridiction.csv).

Task 07: Build and Evaluate the Model using Regression (Tips Dataset).

Task 08: Identify and Analyze Missing Values in a Dataset.

Task 09: Build and Evaluate the Decision Tree Model.

Task 10: Build and Evaluate the Decision Tree Model for Multi-Class Classification.

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Data Science Lab Tasks 1–10 completed in Google Colab with a fully Python-based workflow.

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