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INT344 Units

Practice

NATURAL LANGUAGE PROCESSING

INT344 3 Credits L:2 T:0 P:1 Minor Machine Learning

This course covers the fundamentals of Natural Language Processing, including linguistic components, text preprocessing, and vector space models. Students explore probabilistic models, deep learning architectures such as RNNs and Transformers, and develop end-to-end systems for applications like chatbots and machine translation.

Study Units

Unit 1

Introduction to NLP and Text Processing

Notes MCQ
Unit 2

Vector Space Models

Notes MCQ
Unit 3

Natural Language Processing with Probabilistic Models

Notes MCQ
Unit 4

Natural Language Processing with Classification Models

Notes MCQ
Unit 5

Natural Language Processing with Sequence and Attention Models

Notes MCQ
Unit 6

Building Models/ Case Studies

Notes MCQ

Continuous Assessment

2 components

Project 50%

Group project creating an NLP tool and writing a quality paper. Submission is online.

Week 3 / 12

Rubric
Project report(10 marks), Viva(10 marks), Presentation(10 marks)

Test 50%

Offline test covering Unit 1 and Unit 2.

Week 5 / 6

Exams & Practice

Mid Term Examination

Mid-semester comprehensive evaluation

20%

All MCQ

Coming Soon

End Term Examination

Final semester comprehensive evaluation

50%

Type: Examination

All MCQ

Coming Soon

INT344 - FAQs

How many units are in INT344?

INT344 has 6 units. Each unit includes detailed notes and MCQ practice questions.

What exam resources are available for INT344?

Unit-wise notes and MCQ practice are available. Exam resources coming soon.

How to prepare for INT344 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.