BCA in Data Analytics at BIMS bangalore - Course, Fees, Admission, Seats, Syllabus

Year	Semester	Subjects
1	1	Introduction to Programming, Mathematics for Data Science, Principles of Management, Database Management Systems, English for Communication
1	2	Python Programming, Statistics for Data Science, Organizational Behavior, Data Structures and Algorithms, Environmental Studies
2	1	Machine Learning, Big Data Analytics, Operating Systems, Financial Accounting, Elective I
2	2	Deep Learning, Data Visualization, Web Technologies, Business Data Management, Elective II
3	1	Cloud Computing for Data Analytics, Advanced Database Management Systems, Project Management, Elective III, Project Work I
3	2	Internet of Things for Data Science, Business Intelligence, Elective IV, Elective V, Project Work II

This table is a simplified representation and includes generic subjects that might be part of a BCA in Data Analytics program. The actual syllabus could include more specific subjects, practical labs, workshops, and project work tailored to the institute's curriculum design. Always refer to the official source for the most accurate information.

As of my last update in April 2023, specific syllabus details for the BCA in Data Analytics specialization at the Bangalore Institute of Management & Science (BIMS) might not be readily available due to the dynamic nature of course offerings and updates in curriculum. However, I can provide you with a general overview of important topics that are typically covered in a BCA Data Analytics specialization based on standard academic structures. Please note, for the most accurate and up-to-date syllabus, you should consult the official BIMS website or contact the institution directly. Here's a simplified single-line HTML format representation of what the syllabus might include, focusing on core areas of study:

Core Topics	Software & Tools	Applied Areas
Data Structures and Algorithms	Python, R	Business Intelligence
Database Management Systems	SQL, NoSQL Databases	Market Analysis
Statistics and Probability	Excel, Tableau	Financial Analytics
Machine Learning	TensorFlow, Scikit-learn	Healthcare Analytics
Big Data Analytics	Hadoop, Spark	E-commerce Analytics
Data Visualization	Power BI, D3.js	Social Media Analytics

This table includes a broad overview of core topics like Data Structures, Database Management, and Machine Learning; software and tools such as Python, SQL, and Hadoop; and applied areas including Business Intelligence, Financial Analytics, and Healthcare Analytics. Keep in mind that the actual syllabus may include more specific subjects, additional tools, and other applied areas relevant to the evolving field of data analytics.