BCA in Data Science at Career Point University - Course, Fees, Admission, Seats, Syllabus

Creating a single-line HTML table for the Career Point University BCA in Data Science semester-wise syllabus involves condensing a lot of information into a compact format. Given the nature of such a syllabus, it's important to note that specific course details, including course names and their corresponding semesters, might vary or change over time. Below is a simplified example based on a generic structure for such a program. Please adjust the content according to the actual, most current syllabus from Career Point University.

Semester	Subjects
Semester 1	Introduction to Data Science, Mathematics for Data Science, Programming Fundamentals, English Communication, Environmental Studies
Semester 2	Statistics for Data Science, Python Programming, Database Management Systems, Organizational Behavior, Data Structures
Semester 3	Machine Learning Basics, Web Technologies, Operating Systems, Discrete Mathematics, Minor Project I
Semester 4	Advanced Machine Learning, Big Data Analytics, Computer Networks, Software Engineering, Minor Project II
Semester 5	Data Visualization, Cloud Computing for Data Science, Elective I, Elective II, Summer Internship
Semester 6	Deep Learning, Project Work, Elective III, Elective IV

This HTML snippet creates a table with two columns: one for the semester and one for the subjects taught in that semester. Each row after the header row represents a semester and lists subjects typically found in a BCA in Data Science program. Remember, the actual subjects and their distribution across semesters might differ, so it's crucial to refer to the latest syllabus provided by Career Point University for accurate information.

As of my last update in April 2023, specific syllabus details for the BCA in Data Science specialization at Career Point University or any other institution can vary and should be directly checked with the university for the most accurate and current information. However, I can provide you with a general overview of important topics that are typically covered in a BCA (Bachelor of Computer Applications) program with a specialization in Data Science. Please note, for the most accurate and detailed syllabus, refer to the official university resources.

Core Topics	Tools and Technologies	Applied Areas
Programming Fundamentals	Python, R	Data Analysis
Database Management Systems	SQL, NoSQL	Database Design
Statistics for Data Science	Excel, SPSS	Statistical Analysis
Data Structures and Algorithms	Java, C++	Algorithm Design
Machine Learning	TensorFlow, Scikit-learn	Predictive Modeling
Big Data Analytics	Hadoop, Spark	Data Processing at Scale
Data Visualization	Tableau, Power BI	Visual Analytics
Artificial Intelligence	PyTorch, Keras	AI Model Development
Cloud Computing for Data Science	AWS, Azure	Cloud-based Data Solutions

This table provides a simplified overview of the types of topics, tools, and applied areas you might expect in a BCA program focusing on Data Science. Keep in mind that the actual curriculum may include more specific or additional subjects, and the tools and technologies taught can evolve rapidly as new software and methodologies emerge in the field of Data Science.