Unit 1: Python Programming-II

NumPy, Pandas, data handling and Linear Regression.

Summary

This unit introduces students to Python libraries used in Data Science. Students learn how to manipulate datasets, perform analysis and build simple prediction models.

Key Topics

• NumPy arrays and numerical computation
• Pandas Series and DataFrames
• Importing and exporting CSV data
• Handling missing values
• Linear Regression
• Train–Test split

Unit 2: Data Science Methodology

Systematic framework for solving AI problems.

• Problem definition
• Data collection
• Data preparation
• Model building
• Evaluation
• Deployment

Unit 3: Making Machines See

Introduction to Computer Vision.

• Image recognition
• Computer vision pipeline
• Image preprocessing
• Applications in healthcare and security

Unit 4: AI with Orange Tool

• Visual programming for machine learning
• Widgets and workflow
• Classification models
• Natural Language Processing

Unit 5: Big Data

• Characteristics of Big Data (6Vs)
• Data streams
• Hadoop ecosystem
• Real-world applications

Unit 6: Neural Networks

• Artificial Neural Networks
• Deep learning
• Convolutional Neural Networks
• Recurrent Neural Networks

Unit 7: Generative AI

• GANs
• Large Language Models
• VAEs
• Ethics in AI

Unit 8: Data Storytelling

• Visual communication
• Data narratives
• Freytag's Pyramid
• Presentation techniques