BCA Semester 5 Subjects & Curriculum

Browse subject folders below to access unit-by-unit syllabus, textbooks, video lectures, and PDF study notes for Bachelor of Computer Applications.

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Semesters: Semester 1 3 Semester 2 Semester 3 4 Semester 4 Semester 5 Semester 6

Subject Folders

Subjects in Semester 5

Select any subject folder below to explore its complete syllabus, notes, textbooks, and resources.

8 Subjects Available

BCA 5001T / BCA 5001P

Neural Network

Course Type: DSEC-VII (Group-A Elective – III with Practical). Covers perceptrons, multi-layer feedforward networks, backpropagation, activation functions, regularization, optimization (Adam/SGD), and PyTorch/TensorFlow.

5.0 Credits Syllabus Ready

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BCA 5002T / BCA 5002P

Digital Image Processing

Course Type: DSEC-VIII (Group-A Elective – IV with Practical). Covers spatial and frequency domain image enhancement, filtering, restoration, morphological operations, edge detection, and OpenCV.

5.0 Credits Syllabus Ready

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BCA 5003T / BCA 5003P

Natural Language Processing

Course Type: DSEC-IX (Group-A Elective – V with Practical). Covers tokenization, stemming, lemmatization, POS tagging, NER, word embeddings (Word2Vec), transformer architecture, and NLTK/HuggingFace.

5.0 Credits Syllabus Ready

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BCA 5004T / BCA 5004P

Introduction to Data Science

Course Type: DSEC-X (Group-B Elective – III with Practical). Covers data lifecycle, statistical data exploration, ETL pipelines, predictive modeling, model validation, and data science tooling.

5.0 Credits Syllabus Ready

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BCA 5005T / BCA 5005P

Time Series Analysis

Course Type: DSEC-XI (Group-B Elective – IV with Practical). Covers trend & seasonality decomposition, stationarity tests, ARIMA/SARIMA models, exponential smoothing, and financial/business forecasting.

5.0 Credits Syllabus Ready

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BCA 5006T / BCA 5006P

Machine Learning

Course Type: DSEC-XII (Group-B Elective – V with Practical). Covers advanced ensemble techniques (Random Forests, Gradient Boosting, XGBoost), hyperparameter tuning, cross-validation, and ML pipeline deployment.

5.0 Credits Syllabus Ready

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BCA 5007T

Quantitative Techniques

Course Type: SEC-VI (Skill Enhancement Course). Covers linear programming, simplex method, transportation & assignment problems, queuing theory, and operational research methods.

2.0 Credits Syllabus Ready

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BCA 5008R

Summer Internship / Capstone Project-I

Course Type: SEC-VII (Internship/Project Report). Industry summer internship report evaluation, problem domain definition, requirements analysis, system architecture, and phase-I development.

4.0 Credits Syllabus Ready

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Semester 5 Overview

Fifth semester curriculum focusing on Neural Networks, DIP, NLP, Data Science, Time Series, Machine Learning, Quantitative Techniques, and Summer Internship / Capstone Project-I.