The Bachelor of Computer Applications (BCA) in Data Science is a specialized undergraduate program designed to equip students with the technical and analytical skills required to thrive in today’s data-driven world. The syllabus integrates core computer science subjects with modern data science components, including programming, statistics, machine learning, data visualization, and big data technologies.
Through a blend of theoretical knowledge and practical exposure, the program prepares students to collect, manage, analyze, and interpret large datasets to solve real-world problems across industries. It also introduces essential tools and technologies such as Python, R, SQL, Hadoop, and Tableau.
With a focus on both academic and industry-relevant skills, the BCA Data Science curriculum lays a strong foundation for careers in data analytics, AI, software development, and further studies in computer science or data science domains.
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BCA Data Science Syllabus: Course Structure
The BCA Data Science is a 4-year program divided into 8 semesters. The curriculum includes 4 types of courses, i.e, Major, Minor, Multidisciplinary, and Skill Enhancement Course.
BCA Data Science Syllabus: Semester-Wise
Here is the BCA Data Science syllabus offered by Jammu University. It is expected that the syllabus of other government universities for the BCA Data Science program will be similar to this.
BCA Data Science Syllabus: Exam Scheme
The exam scheme followed in each semester is almost similar, though in some of the semesters, the weightage of components may differ. The table below shows the components covered in each semester for all 4 types of courses and the full marks of these courses:
BCA Data Science Syllabus in Private Universities
Here is the BCA Data Science syllabus followed by UPES, Dehradun. It is expected that the other private universities may have a similar syllabus. The syllabus in private universities may slightly differ from the curriculum offered in the government colleges.
BCA Data Science Syllabus in Private Universities: Elective Courses
Here is the list of electives followed by UPES Dehradun. The other private institutes may also have similar electives:
BCA Data Science Syllabus FAQs
What subjects are covered in the BCA Data Science syllabus?
The BCA Data Science syllabus includes a combination of core computer science subjects and specialized data science topics. Key areas include Programming in Python and C, Data Structures, Database Management Systems, Statistics, Machine Learning, Data Mining, Big Data Analytics, Artificial Intelligence, and Data Visualization tools like Tableau and Power BI.
Is mathematics important in BCA Data Science?
Yes, mathematics plays a crucial role in BCA Data Science. Topics such as linear algebra, probability, and statistics are fundamental for understanding machine learning algorithms, data analysis, and predictive modeling. A solid foundation in mathematics enhances analytical thinking and problem-solving skills in data-driven applications.
Are there practical components in the BCA Data Science syllabus?
Absolutely. The syllabus includes multiple practical components such as programming labs, data analysis projects, and real-world case studies. Students gain hands-on experience with tools like Python, R, SQL, Hadoop, and data visualization software, which helps bridge the gap between theoretical learning and industry application.
What is the scope of BCA Data Science after graduation?
Graduates can pursue careers as Data Analysts, Junior Data Scientists, Business Intelligence Developers, or Software Developers. The course also prepares students for higher studies like MCA, M.Sc. in Data Science, or specialized certifications in AI, ML, and cloud computing. The demand for data professionals is high across industries like IT, finance, healthcare, and e-commerce.
How is BCA Data Science different from a regular BCA?
While a regular BCA focuses broadly on computer applications, BCA Data Science places a specialized emphasis on data analytics, machine learning, and data-driven technologies. It offers deeper insight into handling and interpreting large volumes of data, making it ideal for students aiming for careers in the data science and AI sectors.
