BCA in Data Science at AISECT University Hazaribagh - Course, Fees, Admission, Seats, Syllabus

Semester	Subjects
Semester 1	Introduction to Data Science, Mathematics for Computer Science, Programming in Python, Computer Fundamentals and Office Automation, English Communication, Environmental Studies
Semester 2	Advanced Python Programming, Database Management Systems, Data Structures, Discrete Mathematics, Organizational Behavior, Principles of Management
Semester 3	Operating Systems, Web Technologies, Introduction to Algorithms, Statistical Methods for Data Science, Soft Skills, Minor Project I
Semester 4	Machine Learning, Big Data Analytics, Java Programming, Computer Networks, Professional Ethics, Minor Project II
Semester 5	Deep Learning, Cloud Computing for Data Science, Elective I, Elective II, Summer Internship, Major Project I
Semester 6	Data Visualization, Internet of Things (IoT) for Data Science, Elective III, Elective IV, Major Project II

Please note, the subjects listed are indicative and based on a typical BCA in Data Science curriculum. The actual syllabus may vary. Electives can include advanced topics or specialized subjects in the field of data science and are usually chosen based on the student's interest or the institution's offerings. Always refer to the official AISECT University Hazaribagh curriculum for the most accurate and updated information.

As of my update in April 2023 the specific course details for the BCA in Data Science at AISECT University, Hazaribagh may vary over time due to curriculum updates and the evolving nature of the data science field. However I can give you an overview of the important subjects typically covered in a Bachelor of Computer Applications (BCA) program with a specialization in Data Science. These subjects serve as foundations. Are usually included in such a program; **Introduction to Data Science**; This module provides an understanding of the fundamentals of data science, its significance and its application across industries. **Programming Fundamentals**; In this module students learn programming languages for data science like Python and R. The focus is on learning syntax, data structures and basic algorithms. **Mathematics for Data Science**; This module covers mathematical concepts such as linear algebra, calculus and statistics which are essential, for comprehending data science algorithms. **Database Management Systems (DBMS)**;In this course we will cover the principles of managing databases, including both SQL and NoSQL databases. You will learn how to manipulate and retrieve data from these databases. We will also delve into the world of data analysis and visualization. You will gain the skills to analyze datasets in order to extract insights from them. Furthermore you'll discover how to visualize data using tools like Tableau, Power BI or programming libraries such as Matplotlib and Seaborn in Python. Another important topic we'll explore is machine learning. Throughout the course you'll be introduced to machine learning algorithms, including supervised and unsupervised learning techniques. We'll cover decision trees, methods regression analysis approaches and even delve into neural networks. Additionally we'll discuss data technologies extensively. This includes exploring frameworks like Hadoop and Spark along with their ecosystems that are specifically designed for processing and analyzing large volumes of data. Lastly. Not leastly we'll dive into the realm of data mining. You'll gain an understanding of how to uncover patterns and extract knowledge from vast amounts of data. Join us on this journey where you will acquire valuable skills in database management, data analysis and visualization techniques machine learning algorithms, big data technologies utilization as well, as mastering the art of data mining. The emphasis lies on concepts such as association rule learning, cluster analysis and anomaly detection. **Ethics and Data Privacy**; Delving into the considerations and concerns about privacy in the field of data science including regulations for data protection and responsible use of data. **Capstone Project**; A project that typically requires students to apply their knowledge and skills to solve real world problems or carry out significant research in the realm of data science. **Internship/Industrial Training**; Practical experience gained through internships or industry projects is often incorporated into the curriculum to provide students with hands on learning opportunities. Please note that for the accurate and up to date information regarding the BCA in Data Science curriculum, at AISECT University, Hazaribagh it is recommended to consult the official website of the university or get in touch with them directly.