A Bachelor of Science in Data Science is a four-years undergraduate degree program that focuses on the study of methods, processes, and systems to extract insights and knowledge from various forms of data. Profile of the program is as follows:
Core curriculum: The core curriculum of BSc Data Science program covers fundamental concepts in mathematics, statistics, computer science, and data analysis. Courses may include calculus, linear algebra, probability theory, programming languages (such as Python, R, and SQL), data structures, algorithms, and machine learning.
Data Analysis and Visualization: Students learn techniques of cleaning, transforming, and analysing data using statistical methods and software tools. Visualization techniques, such as creating plots, charts, and interactive dashboards, are emphasized to communicate effectively.
Machine Learning and Data Mining: Courses in machine learning and data mining explore algorithms and models for pattern recognition, classification, regression, clustering, and other tasks. Students learn how to apply machine learning techniques to real-world data set and evaluate model performance.
Big Data Technologies: As the volume and complexity of data increase, understanding big data technologies becomes essential. Students may learn about distributed computing frameworks like Hadoop and Spark, as well as techniques for handling large-scale data storage, processing, and analysis.
Database systems and data management: Understanding database systems and data management principles is crucial for organizing and accessing data efficiently. Students may study relational databases, NoSQL databases, data warehousing, and data integration techniques.
Domain Knowledge: BSc Data Science offers elective courses and specializations in specific domains such as healthcare, finance, marketing, or social sciences. These courses provide students with domain-specific knowledge and skills to address industry-specific challenges.
Capstone Project and Internship: Program includes capstone project and internship component where students work on real-world data science projects either within academic research groups or in industry settings. This hands-on experience allows students to apply their skills in a practical context and build their professional network.