The Bachelor of Science in Data Science focuses on equipping students with the knowledge and skills to extract, analyze, and interpret meaningful information from large and complex datasets using statistical, computational, and machine learning tools.
Duration: 4 year (8 Semesters)
Foundational Knowledge
Establish a solid foundation in data science principles, statistics, programming, and data management techniques.
Technical Skills
Equip students with skills in data visualization, machine learning, statistical modeling, and big data processing tools.
Collaboration and Communication
Enhance teamwork and communication through collaborative data analysis projects, reports, and real-world case studies.
Elective Courses
Provide electives in NLP, financial analytics, healthcare data science, and data ethics to tailor the program to evolving industries.
Problem-Solving Abilities
Cultivate data-driven thinking to solve real-world problems through insightful analysis and predictive modeling.
Core courses
Covering fundamental topics in computer science, including programming languages, data structures, algorithms, computer networks, database systems, and software engineering
Elective courses
Elective courses allowing students to explore specialized areas of interest such as artificial intelligence, machine learning, cybersecurity, computer graphics, and game development.
Hands-on learning experiences
Hands-on learning experiences through programming labs, projects, internships, and industry collaborations to apply theoretical concepts to real-world problems and gain practical experience.
Capstone project or thesis work
Capstone project or thesis work requiring students to undertake a substantial independent research or software development project under the guidance of faculty mentors.
Graduates of the BS in Data Science program are well-equipped with the analytical, computational, and statistical skills needed to extract insights and inform decision-making. Some potential career paths include:
Data Scientist
Apply machine learning and statistical techniques to derive patterns and predictions from large datasets.
Data Analyst
Create dashboards, reports, and data visualizations to support operational and strategic initiatives.
Machine Learning Engineer
Develop predictive models and train algorithms for various data-driven applications.
Business Intelligence Analyst
Translate data into actionable insights for marketing, finance, and management decisions.
Data Engineer
Build and optimize data pipelines, warehouses, and ETL processes to support analytics.
