BCA in Data Science at City Group Of Colleges - Course, Fees, Admission, Seats, Syllabus

6. Data Mining and Predictive Analytics; This module focuses on techniques for finding patterns in datasets and using them to make predictions. It covers methods like machine learning algorithms, clustering, classification and association rule learning. 7. Big Data Technologies; In this section you will be introduced to the concepts of data along with popular technologies like the Hadoop ecosystem and Spark. These technologies are used for processing and analyzing amounts of data. 8. Machine Learning; Here we will cover the fundamentals of machine learning including supervised and unsupervised learning techniques, neural networks, decision trees and reinforcement learning. 9. Deep Learning; This module provides an introduction to learning techniques and their practical applications. It specifically focuses on networks, convolutional neural networks (CNNs) and recurrent neural networks (RNNs). 10. Ethics and Data Privacy; In this part of the course we delve into the considerations surrounding data science practices. We discuss topics such, as data protection laws, regulations, privacy concerns and responsible data handling. 11. Capstone Project; The final project allows you to apply your acquired knowledge and skills to solve real world problems in the field of data science. 12. **Soft Skills and Communication**; It is crucial to cultivate skills, like critical thinking, problem solving abilities and effective communication in order to thrive in ones professional journey.