BCA Data Science Syllabus and Subjects
BCA Data Science syllabus is an advanced course that deals with Data science and software applications. The course provides fundamental knowledge of today's IT industry requirements. Students will get to learn different topics Database Management System, Statistics and Probability, Machine Learning, Big Data Analytics and so on.
Semester Wise BCA Data Science Syllabus
BCA Data Science syllabus is divided into 6 semesters which will help students to understand the course effectively. The first two-semester of this course will primarily focus on the basics part while the other portions are the core topics that are more important to learn.
BCA Data Science course provides a strong understanding of Database Management Systems, Statistics and Probability, and Machine Learning. The course structure is very clear and easy to understand for the students.
BCA Data Science First Year Syllabus
Given below are the first and second-semester syllabus of BCA Data Science course:
|
Semester I |
Semester II |
|
Cultural Education 1 |
Cultural Education 2 |
|
Communicative English |
Language Paper 2 |
|
Language 1 |
Professional Communication |
|
Discrete Mathematics |
Statistics and Probability |
|
Environmental Science and Sustainability |
Database Management System |
|
Computer Essentials for Data Science |
Data Structure and Algorithm |
|
Computational Thinking and Programming in C |
Operating System |
|
Computational Thinking and Programming in C Lab |
Database Management System Lab |
|
Data Structures Lab |
BCA Data Science Second Year Syllabus
Given below are the third and fourth-semester syllabus of BCA Data Science course:
|
Semester III |
Semester IV |
|
Life Skills 1 |
Life Skills 2 |
|
Essential of Data Collection Ethics |
Introduction to Data Mining |
|
Descriptive Statistics |
Python Programming |
|
Computer Networks |
Open Elective A* |
|
Object Oriented Programming using C++ |
IIntroduction to Java and Web Programming |
|
Software Engineering |
Python Programming Lab |
|
Scripting Technologies Lab |
Elective A |
|
Practical Exposure to Data Collection Lab |
Java Programming Lab |
BCA Data Science Third Year Syllabus
Given below are the fifth and sixth-semester syllabi of BCA Data Science:
|
Semester V |
Semester VI |
|
Data Modeling and Visualization |
Big Data Analytics |
|
R Programming for Data Sciences |
Information and Data Security |
|
Machine Learning |
Natural Language Processing |
|
Elective B |
Elective C |
|
Introduction to Parallel Programming and Data Optimization |
Big Data Analytics Lab |
|
Open Elective B* |
Project |
|
Introduction to Parallel Programming Lab |
|
|
Fundamentals of Machine Learning Lab |
|
|
Minor Project |
BCA Data Science Subjects
BCA Data Science subject clarifies all the important methodologies Database Management Systems, Statistics and Probability, Machine Learning, Big Data Analytics and so on.
The overall course structure is totally based on the theoretical concept that students need to learn. The course consists of core topics and elective topics which are obviously optional for the students to choose.
BCA Data Science Core Subjects
Given below are the core subject of the BCA Data Science course:
- Introduction to Java
- Web Programming
- R Programming for Data Sciences
- Natural Language Processing
- Database Management System
- Object Oriented Programming using C++
BCA Data Science Elective Subjects
Given below are the elective subject of the BCA Data Science course:
- Non-relational Databases
- Soft Computing
- Text Mining and Analytics
- Distributed Computing
- Design Pattern
- Computational Linear Algebra
BCA Data Science Course Structure
BCA Data Science course structure is designed in a way to provide students with actual knowledge in this field.
The course duration is three years and it is compact with core and elective subjects accordingly. Students will conquer a bright future after completing this course attentively.
- VI Semesters
- Core Subjects
- Elective Subjects
- Undergraduate Course
- Research Project
- Field Project
BCA Data Science Teaching Methodology and Techniques
BCA Data Science teaching methodology is the most important aspect of a course curriculum to understand the subject more deeply.
The classroom-based teaching methodology is the ideal method of learning. The course is designed in a way that students get access to all the infrastructure and facilities available.
Listed below are the teaching methodology and techniques:
- Practical & Laboratory Sessions
- The Emphasis Of Practical Learning
- Experimentation
- Guest Lectures, Seminars, And Workshop
- Group Assignment And Discussion
- Learning Through Industrial Visit
- Research & Development
BCA Data Science Projects
BCA Data Science course projects are an important segment of the course curriculum. The projects are accessed by the professors to evaluate and judge the students' understanding of those subjects.
Students can choose their course project according to their specialization. Given below are some of the course projects.
- Recognition of Speech Emotion
- Gender and Age Detection with Data Science
- Driver Drowsiness Detection in Python
- Chatbots
- Handwritten Digit & Character Recognition Project
BCA Data Science Books
Books are termed to be the greatest investment that an aspiring individual can invest in. BCA Data Science books can help students to understand the core topics and they also can learn about various topics according to their interests.
Books will definitely have a great impact on the student’s life Given below are some of the important books:
|
Name of Book |
Author |
|
Fundamentals of Computers |
Rajaraman V |
|
Introduction to Computers |
Norton Peter |
|
The Internet complete reference |
Hahn |
|
The C Programming Language" |
Ritchie Kernighan |
|
Working with C |
Kanetkar Yashwant |
|
Computers & C Programming |
Bajpai, Kushwaha |
