BCA in Data Analytics at IEM Kolkata - Course, Fees, Admission, Seats, Syllabus

As of my recent update in April 2023 the specific course outlines for the BCA in Data Analytics program at the Institute of Engineering and Management (IEM) may vary over time due to curriculum updates and changes in industry trends. However I can provide you with an overview of the important subjects usually covered in a BCA in Data Analytics program. These subjects are crucial for gaining an understanding of the field and are typically included in courses offered at institutions like IEM; **Introduction to Data Analytics**; This subject focuses on grasping the fundamentals of data analysis, including its significance in todays world, different types of data and the process involved in data analytics. **Programming Fundamentals**; In this subject students learn programming languages for data analytics such as Python or R. The focus is on acquiring skills related to manipulating, visualizing and analyzing data. **Statistics for Data Analytics**; This subject covers methods and probability theory that are essential for analyzing and interpreting data. It includes topics, like statistics, inferential statistics, hypothesis testing and regression analysis. **Database Management Systems (DBMS)**;Here are the key topics covered in the database systems course; 1. Understanding the principles of database systems, including SQL for data querying and the use of NoSQL databases for handling big data. 2. Exploring data mining techniques, algorithms and their practical applications in discovering patterns and making predictions from datasets. 3. Introduction to machine learning algorithms and their role in data analytics covering both unsupervised learning approaches, neural networks and deep learning. 4. Delving into data technologies like Hadoop, Spark and their associated frameworks used for managing large scale datasets efficiently. 5. Learning techniques and tools for visualizing data using software such as Tableau or Power BI as well as programming libraries like Matplotlib and Seaborn in Python. 6. Understanding how data analytics can be applied to drive business decisions across various areas such as marketing, finance and operations. 7. Discussing the considerations surrounding data analytics practices including privacy concerns, compliance with relevant laws and regulations protecting sensitive information. 8. Engaging in a capstone project that allows students to apply their knowledge in a world or simulated scenario demonstrating their proficiency in solving practical problems related to data analytics. Please note that for the accurate information, on this curriculum or any updates made by the Institute of Engineering and Management (IEM) it is advisable to consult official resources or contact the institution directly. This will give you information, about the courses and elective options.