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End Term Available: Viva Questions

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INT234 Units

Practice

PREDICTIVE ANALYTICS

INT234 3 Credits L:2 T:0 P:2 Minor Data Science

This course enables students to understand data preprocessing and exploratory data analysis, apply regression and classification techniques, and analyze clustering algorithms and neural network models to enhance predictive accuracy.

Study Units

Unit 1

Introduction and Data Preparation

Notes MCQ
Unit 2

SUPERVISED LEARNING: REGRESSION

Notes MCQ
Unit 3

SUPERVISED LEARNING: CLASSIFICATION

Notes MCQ
Unit 4

UNSUPERVISED LEARNING: CLUSTERING AND PATTERN DETECTION

Notes MCQ
Unit 5

Dimensionality Reduction and Neural Networks

Notes MCQ
Unit 6

MODEL PERFORMANCE

Notes MCQ

Continuous Assessment

2 components

BYOD-Practical 50%

Scenario-based questions will be asked from the students to evaluate their understanding of the various concepts

Week 5 / 6
Skill Based Assignment 50%

To understand the knowledge gained by the students in the form of project

Week 5 / 12

Rubric
A) Problem Statement and Dataset (10 Marks); B) Implementation, Report, and Viva (60 Marks) including Data Cleaning, EDA, Model development, Report, Viva; C) LinkedIn Engagement (10 Marks); D) GitHub Contributions (20 Marks)

Exams & Practice

End Term Examination

Final semester comprehensive evaluation

50%

Type: Practical

Viva Questions

INT234 - FAQs

How many units are in INT234?

INT234 has 6 units. Each unit includes detailed notes and MCQ practice questions.

What exam resources are available for INT234?

Available resources include: Viva Questions.

How to prepare for INT234 exams?

Study each unit's notes thoroughly, practice MCQs to test understanding, and attempt mock tests before exams. Focus on important topics and previous year questions.