Course Duration	Course Level	Course Tuition Fees (Rs)	Mode of Study	Institute Type
3 Years	Undergraduate	1,20,000	Full-time	Private

Please adjust the table values according to the specific details of the BCA in Data Science program at SONA DEVI UNIVERSITY or the institution you're inquiring about.

As of my update in April 2023 I do not have specific details regarding the curriculum at SONA DEVI UNIVERSITY for a BCA program specializing in Data Science. Curricula can vary significantly among institutions. May undergo updates over time. Nonetheless I can offer an overview of essential subjects typically included in a Bachelor of Computer Applications (BCA) program with an emphasis on Data Science. These foundational topics are likely to form part of a Data Science curriculum at most universities; 1. **Introduction to Data Science**; Exploring the fundamentals, history and significance of data science in todays context including understanding the data science lifecycle. 2. **Programming Basics**; Mastery of programming languages like Python and R for data manipulation and analysis. 3. **Mathematics for Data Science**; Covering concepts such as linear algebra, calculus and statistics, for grasping and creating algorithms. 4. **Data. Algorithms**; Understanding various data structures (e.g., arrays lists, trees, graphs) and algorithms (sorting, searching) to facilitate efficient data handling and analysis. 5. **Database Management Systems (DBMS)* When studying databases you'll cover non relational databases SQL queries and database design. Data Cleaning and Preprocessing involves managing missing data, noise and inconsistencies in the data. Data Visualization uses tools like Matplotlib, Seaborn and Tableau to create visual representations of data. In Machine Learning you'll learn about supervised and unsupervised learning concepts and algorithms such as regression, classification, clustering and neural networks. Deep Learning introduces learning frameworks like TensorFlow and Keras as well as architectures such as CNNs, RNNs and autoencoders for more complex analyses. Big Data Technologies teaches you about tools like Hadoop and Spark for handling data effectively. Ethics and Privacy in Data Science covers considerations and privacy concerns when collecting, analyzing and sharing data. The Capstone Project allows students to apply their knowledge to real world data science problems. Stay updated on Emerging Trends, in Data Science including AI ethics, quantum computing, edge computing technologies to be of the curve.