BCA in Data Analytics at Lingaya's Vidyapeeth - Course, Fees, Admission, Seats, Syllabus

As of my update in April 2023 I'm afraid I don't have access to the current syllabus for the BCA in Data Analytics program at Lingayas Vidyapeeth. Universities and colleges tend to update their curricula frequently to stay up to date with the latest advancements in the field and cater to the evolving needs of students and employers. Therefore it's crucial that you refer to the Lingayas Vidyapeeth website or directly contact the institution for accurate and up to date information. However I can certainly give you an overview of what a BCA, in Data Analytics program usually covers based on typical course content found in similar programs. This should provide you with an understanding of the subjects and skills typically encountered in such a program. *Programming Introduction*; This course covers the fundamentals of programming languages like Python or Java. *Mathematics for Computer Science*; In this course you will learn about mathematics, probability and statistics as they relate to computer science. *Introduction to Data Analytics*; Gain an overview of data analytics, its significance and practical applications. *Database Management Systems*; Get a grasp, on the basics of DBMS, SQL and data storage. *Computer Fundamentals and Office Automation*; Understand the foundations of computers including hardware and software components. Additionally learn how to utilize office productivity tools. *Communication Skills*; This course focuses on improving both written communication skills. After gaining programming knowledge in the first year we can further delve into more complex concepts and explore an additional programming language. In the year we will cover various subjects including; **Operating Systems**; Understanding the core principles of operating systems and their role in data analytics. **Web Technologies**; Learning about web development technologies that're relevant to data analytics. **Principles of Data Analytics**; A deep dive into the principles, techniques and tools used in data analytics. **Statistical Methods for Data Analysis**; An exploration of statistical methods that are applicable to analyzing and interpreting data. Moving on to the year we will focus on; **Machine Learning**; Introduction to machine learning algorithms and their applications in data analytics. **Big Data Analytics**; Understanding concepts, tools and technologies related to big data analysis. **Data Visualization**; Exploring techniques and tools for visualizing data to make informed decisions. **Cloud Computing for Data Analytics**; An examination of cloud platforms and their utilization in storing and analyzing data. **Project Work**; Undertaking a project where students can apply their acquired knowledge to solve real world problems in data analytics. **Electives**; Depending on the programs offerings students may choose from a range of courses. By following this curriculum structure students will gain an understanding of programming, operating systems, web technologies, statistical analysis methods, machine learning algorithms, big data analytics concepts, data visualization techniques, cloud computing applications, and practical experience, through project work.