BCA in Data Analytics at Sai Nath University - Course, Fees, Admission, Seats, Syllabus

Semester	Subjects
Semester 1	Introduction to Data Analytics, Mathematics for Computer Science, Programming in Python, English Communication, Computer Fundamentals and Office Automation
Semester 2	Database Management Systems, Data Structures, Operating System Concepts, Statistical Methods for Data Analysis, Environmental Studies
Semester 3	Object-Oriented Programming with Java, Web Technologies, Advanced Database Management Systems, Data Visualization, Minor Project
Semester 4	Machine Learning, Big Data Analytics, Cloud Computing, Ethics in Data Science, Business Intelligence
Semester 5	Deep Learning, Data Mining, Research Methodology, Elective I, Elective II
Semester 6	Internship/Project Work, Elective III, Elective IV

Please note, the subjects listed are hypothetical and meant to serve as an example. Actual course offerings and structure may vary. Always refer to the university's official curriculum for the most accurate and current information.

As of my last update in April 2023, I don't have access to the specific syllabus details of Sai Nath University's BCA in Data Analytics specialization. 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 curricula. For the most accurate and up-to-date information, please refer directly to Sai Nath University's official resources or contact them directly. Below is a hypothetical overview in a single line HTML format:

Course	Key Topics
Introduction to Data Analytics	Basics of Data Analysis, Data Life Cycle, Introduction to Big Data
Programming for Data Analytics	Python/R Programming, Data Structures, Algorithms
Database Management Systems	SQL, NoSQL, Data Warehousing, Data Mining
Statistical Methods for Data Analysis	Descriptive Statistics, Inferential Statistics, Probability
Data Visualization	Tableau, Power BI, Data Presentation Techniques
Machine Learning	Supervised Learning, Unsupervised Learning, Neural Networks
Big Data Technologies	Hadoop, Spark, Big Data Analytics Tools
Business Intelligence	BI Concepts, Tools, Decision Making Processes
Project	Real-world Data Analytics Project

This table is a simplified representation and does not cover all courses or topics. The actual curriculum may include additional subjects such as ethics in data analytics, cloud computing for data analytics, advanced machine learning techniques, and domain-specific analytics (like financial, healthcare, or social media analytics). Always refer to the university's official curriculum for the most accurate and comprehensive information.