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

Sure, I'll create a simple HTML table for the LNCT University BCA in Data Analytics course, semester-wise. Please note, for a more detailed or specific curriculum, you should refer to the official LNCT University website or contact them directly, as course structures can change. Here's a simplified version:

Semester	Subjects
Semester 1	Introduction to Data Analytics, Mathematics for Computer Science, Programming in Python, English Communication, Environmental Studies
Semester 2	Database Management Systems, Advanced Python Programming, Statistics for Data Science, Organizational Behavior, Financial Accounting
Semester 3	Data Structures and Algorithms, Operating Systems, Data Visualization, Business Analytics, Elective I
Semester 4	Machine Learning, Big Data Analytics, Web Technologies, Research Methodology, Elective II
Semester 5	Deep Learning, Cloud Computing for Data Analytics, Project Work I, Elective III, Elective IV
Semester 6	Internship/Project Work II, Elective V, Elective VI

This table is a simplified representation and includes generic subjects that might be part of a BCA in Data Analytics program. The actual subjects, their order, and the electives offered can vary. Electives are placeholders for subjects that may be chosen based on interest or specialization within the field of data analytics.

The BCA program in Data Analytics at LNCT University aims to provide students with the knowledge and practical skills to effectively analyze, manage and interpret large datasets. While I don't have the details of LNCT Universitys curriculum as of my last update in April 2023 I can give you an overview of the core subjects commonly included in BCA programs focused on Data Analytics. These topics are crucial for gaining an understanding of the field and preparing students for a successful career, in this rapidly evolving industry. Here is an overview of the courses offered in the field of data analytics; 1. We start with an introduction to Hadoop and Spark which're big data technologies commonly used for processing large datasets. 2. Next we delve into the world of data analytics and explore how it can provide valuable insights through advanced data processing techniques. 3. We also cover cloud computing for data analytics, which involves using servers to store and analyze data efficiently. 4. Moving on to business intelligence we lay the foundations by understanding its fundamentals and exploring tools and applications used in this field. 5. Decision making with data is another aspect we focus on as it helps businesses make informed choices based on statistical analysis. 6. In terms of ethics and privacy in data analytics we discuss topics such as ensuring data security handling information ethically and complying with privacy laws like GDPR. 7. To provide experience we offer capstone projects where students work on real world data analytics tasks. 8. Additionally internships in industry settings allow students to gain hands on experience in applying their skills to scenarios. 9. We also touch upon emerging trends in data analytics such as intelligences role in this field the impact of IoT (Internet of Things) on collecting and analyzing large volumes of information and predictive analytics. These courses aim to equip students with skills related to collecting, processing, analyzing and visualizing data while emphasizing ethical considerations and real world applications that are crucial for success, in a professional environment. For accurate course details tailored specifically to your needs or interests """