Program Overview
The Bachelor of Science in Data Science at Nipissing University equips students with the mathematical and computational skills to become data scientists. The program emphasizes experiential learning through research papers, practicums, and internships, and allows students to customize their studies based on their interests. Graduates are well-prepared for careers in data analysis, artificial intelligence, and other data-driven fields.
Program Outline
Degree Overview:
Overview:
The Bachelor of Science (BSc) in Data Science is an undergraduate program at Nipissing University that equips students with the necessary mathematical and computational background to become data scientists. It focuses on applying data science concepts to various areas of interest, like environmental studies, business analytics, or healthcare. The program integrates theoretical courses and practical experiences such as research papers, practicums, and internships.
Objectives:
- To train students to analyze and interpret data from various sources with a strong foundation in applied mathematics and computer science.
- To develop critical thinking and problem-solving skills for data collection, maintenance, processing, analysis, and communication.
- To equip students with hands-on skills through experiential learning programs.
- To provide students with the knowledge and skills to apply data science principles in their chosen field of study.
Program Description:
- The curriculum includes courses in machine learning, tools and technologies in data science, data analytics, computer science, statistics, artificial intelligence, and neural networks.
- Emphasis is placed on capturing, understanding, managing, visualizing, interpreting, and presenting data.
- Undergraduate research is highly encouraged through research papers, practicum courses (internships or applied projects within the University), and project-based learning in other courses.
Other:
- The program aims to cultivate data scientists for various career paths requiring data management and analysis skills.
Outline:
Curriculum Structure:
Data science courses are combined with courses from a variety of disciplines, allowing students to customize their studies based on their interests. Available disciplines include environment, health, biology, chemistry, physics, business, economics, social sciences, and humanities.
Program Resources:
The program boasts modern facilities, including:
- Computer labs
- Robotics labs
- Access to SHARCNET (high-performance computer network for research)
- The Sun Lab dedicated for computer science instruction
- Physics lab
- Harris Learning Library (awarded-winning design)
Assessment: The program likely uses various assessment methods depending on courses, such as:
- Assignments
- Quizzes
- Examinations
- Projects
- Presentations
- Participation
- Term papers
- Theses (M.Sc. and Ph.D.) Evaluation criteria may include factors like accuracy, critical thinking, problem-solving, creativity, communication skills, data analysis competency, and the implementation of theoretical knowledge.
Teaching:
Teaching Methods:
The program combines various teaching methods based on the course, including:
- Lectures
- Tutorials
- Seminars
- Discussions
- Hands-on labs
- Experiential learning
- Independent study
Faculty and Staff:
- The program consists of experienced faculty with expertise in various data science and related fields, ensuring students receive comprehensive knowledge and mentorship.
- Experienced and supportive staff provides guidance throughout the program.
Unique Approaches:
- Emphasis on experiential learning through research work, and internships/practicum placements.
- Focus on customization by allowing students to choose courses based on their interests.
Careers:
Career Potential:
Graduates are well-equipped for various data-driven careers, such as:
- Data analyst
- Financial advisor
- Statistician
- Business analyst
- Software developer
- Market research analyst
- Artificial intelligence developer
- Machine learning engineer
- Data scientist in various industry sectors
Further Education:
- Students can pursue their education with the Master of Science in Data Science, Doctor of Philosophy (Ph.D.) in Environmental Science/Studies, Master of Environmental Science/Studies program at Nipissing or other higher-level degrees.
Other: Nipissing University offers various support services to students:
- Academic support services (e.g., accessibility services, learning style assessments, tutoring, study skills seminars)
- Financial support services (scholarships, awards, loans, work-study programs)
- Personal counseling service
- Housing services through campus residence
Entry Requirements:
Data Science
Admission Requirements
- All applicants are required to have a minimum overall average of 70% in five (5) university or college courses.
- Applicants with a university degree will be required to have a minimum overall average of 70% in their last 20 full-course equivalents.
- All applicants must have completed a minimum of:
- Calculus I and II
- Linear Algebra
- Statistics I and II
- Programming I and II
- Applicants are encouraged to have completed courses in:
- Data Structures
- Discrete Mathematics
- Machine Learning
- Artificial Intelligence
Language Proficiency Requirements:
- Applicants whose first language is not English must demonstrate proficiency in English by achieving a minimum score on one of the following tests:
- TOEFL: 88 (internet-based)
- IELTS: 6.5 (overall)
- CAEL: 70 (overall)
Additional Requirements:
- Applicants are encouraged to submit a letter of intent outlining their interest in data science and their career goals.
- Applicants may also be required to complete an interview as part of the application process.
Note:
Applicants who do not meet the minimum admission requirements may be considered for admission on a case-by-case basis.
