BCA in Data Analytics at Dev Bhoomi Group of Institutions - Course, Fees, Admission, Seats, Syllabus

As of my recent update in April 2023 Dev Bhoomi Group of Institutions (DBGI) provides a range of programs, including a Bachelor of Computer Applications (BCA) program with a specialization in Data Analytics. While I cannot provide the details of the curriculum specifically tailored to DBGI I can give you an overview of the important subjects typically covered in a BCA program that focuses on Data Analytics. These subjects are designed to equip students with the skills for analyzing, managing and interpreting large datasets, which is crucial in todays data driven world. Here is a summary of the topics; 1. **Introduction to Data Analytics**; This module covers the fundamentals of data analytics including its significance, different types and applications across industries. 2. **Foundations of Programming**; Students learn programming languages like Python, R or Java that're essential for data analysis and manipulation. 3. **Database Management Systems (DBMS)**; This subject provides knowledge about database systems. Teaches SQL (Structured Query Language) as well as NoSQL databases for efficient management and retrieval of data. 4. **Data Structures and Algorithms**; Students gain an understanding of how to store, manage and process data using various data structures such as arrays, lists, trees and graphs along, with algorithms. 5.In the field of data science it is crucial to have an understanding of statistical methods and probability to effectively analyze and interpret data. This includes topics such as statistics, inferential statistics, hypothesis testing and regression analysis. Another important skill is data visualization, which involves presenting data in an appealing manner using tools like Tableau, Power BI or Matplotlib in Python. Creating charts, graphs and dashboards allows for comprehension of complex information. Machine learning is also an aspect of data analytics. It involves learning about types of machine learning algorithms like supervised learning (where the model learns from labeled examples) unsupervised learning (where the model discovers patterns on its own) and reinforcement learning (where the model learns through trial and error). Understanding how these algorithms work and their applications is essential. To handle datasets effectively knowledge of big data technologies is necessary. This includes understanding concepts like Hadoop, Spark and Hive that are used for processing and analyzing amounts of data. Data mining techniques are also valuable for extracting insights from large datasets. These techniques involve tasks such as pattern recognition clustering (grouping items together) and association analysis (finding relationships between different variables). Ethical considerations and legal aspects play a role in working with data. It's important to understand topics such, as data protection laws and regulations to ensure handling of information. Lastly business intelligence focuses on using data analytics to make decisions that drive business success. This involves studying tools and techniques used in business analytics. The Capstone Project is an opportunity for students to put their knowledge into practice by tackling real world data analytics issues. This project often involves collaborating with industry partners to find solutions.