BCA in Data Science at LPU - Course, Fees, Admission, Seats, Syllabus

Based on my recent update in April 2023 the specific details of the curriculum for the BCA in Data Science program at Lovely Professional University (LPU) may have undergone some changes. However I can provide you with an overview of the key subjects typically covered in a BCA program with a specialization in Data Science. These subjects aim to provide students with a foundation, in both computer applications and the specialized field of data science; First it's important to have an understanding of databases including both SQL and NoSQL databases. Operating systems play a crucial role in computer science. It's essential to grasp concepts like processes, threads and memory management. Familiarize yourself with the basics of computer networks, such as networking principles, network protocols and internet technologies. Software engineering principles are fundamental for software development. This includes understanding the software lifecycle and project management. A good foundation in mathematics and statistics is necessary for data analysis; Discrete mathematics covers topics like logic set theory, combinatorics, graph theory and algorithms. Probability and statistics are essential for analyzing data. This includes statistics, inferential statistics, probability distributions and hypothesis testing. Linear algebra is key for data science algorithms. Concepts like vectors, matrices,eigenvalues and eigenvectors are crucial to understand. In addition to these concepts; Data structures and algorithms focus on organizing data efficiently while ensuring optimal algorithm performance. Data analysis and visualization techniques help us gain insights from datasets by using tools like Python libraries such as Pandas, Matplotlib and Seaborn. Machine learning introduces algorithms used for tasks like classification, regression and clustering. These include supervised learning, unsupervised learning decision trees and neural networks. Moreover; Big data technologies provide an overview of managing large scale datasets using frameworks, like Hadoop ecosystemand Spark. Lastly; Data mining involves techniques used to discover patterns and extract knowledge from amounts of data. These topics collectively contribute towards an understanding of artificial intelligence (AI).*; In this course we will cover the fundamentals of AI, which include search algorithms, knowledge representation and applications of AI.