Bachelor of
SCIENCE IN
data
SCIENCE
SCIENCE IN
data
SCIENCE
Program Overview
Award : Bachelor of Science in Data Science
The Bachelor of Science in Data Science is designed to equip students with the essential skills and knowledge required to analyze complex data sets, derive meaningful insights, and make data-driven decisions. Our comprehensive curriculum combines theoretical knowledge with practical applications, preparing graduates for a variety of roles in the data-driven economy.
Total Credit Hours: 180 ECTS
Program Duration: 3 years (6 semesters)
Mode of learning: On campus/Online/Blended
Semester 1: Foundations of Data Science
- Introduction to Data Science
- Programming for Data Science (Python/R)
- Mathematics for Data Science
- Data Visualization Techniques
- Communication Skills for Data Professionals
Semester 2: Data Management and Analysis
- Database Systems and SQL
- Data Wrangling and Preprocessing
- Statistical Methods for Data Analysis
- Introduction to Machine Learning
- Ethics in Data Science
Semester 3: Advanced Data Techniques
- Advanced Machine Learning
- Big Data Technologies and Tools (Hadoop, Spark)
- Data Mining Techniques
- Data Engineering and Architecture
- Research Methods in Data Science
Semester 4: Specialization and Application
- Specialization Electives (Choose 1)
- Natural Language Processing
- Computer Vision
- Time Series Analysis
- Data Science Project I (Group Project)
- Business Intelligence and Analytics
- Cloud Computing for Data Science
Semester 5: Capstone and Real-World Experience
- Data Science Project II (Individual Project)
- Industry Internship / Co-op Experience
- Advanced Topics in Data Science (Guest Lectures)
- Data Ethics and Policy
Semester 6: Career Preparation and Deployment
- Data Science Practicum
- Professional Development and Career Readiness
- Final Capstone Project
- Data Science Portfolio Development
- Industry Networking and Job Search Strategies
Assessment Methods
Assessment in the Bachelor of Science in Data Science program will be conducted through a variety of methods to ensure a comprehensive evaluation of student understanding and skills:
- Exams and Quizzes: Regular assessments to test theoretical knowledge.
- Assignments and Projects: Hands-on assignments and group projects to apply learned concepts.
- Practical Labs: Practical sessions to reinforce technical skills in data manipulation and analysis.
- Capstone Projects: A significant project at the end of the program that demonstrates the ability to apply data science techniques to real-world problems.
- Internship Evaluation: Performance assessment based on internship experience.
- Portfolio Review: Evaluation of a compiled portfolio showcasing skills and projects completed during the program.
Career Opportunities
Graduates of the Bachelor of Science in Data Science can pursue various career paths, including but not limited to:
- Data Scientist
- Data Analyst
- Machine Learning Engineer
- Business Intelligence Analyst
- Data Engineer
- Statistician