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Data Science is at the intersection of three domains: computer science, mathematics and statistics, and application (e.g. business, social science, health).
The insights of data and analytics influence our everyday lives, from streaming service algorithms to the life altering decisions made by science, industry and government. Data Science combines the practical application of mathematics, statistics, computer science and analytics to extract value from data to infer knowledge from patterns. Data scientists form questions, design the collection and storage of data, write reliable and fast code for wrangling datasets, utilize inferential statistics, machine learning and AI to analyze the data, and present the translated results in a responsible, reproducible and actionable way.
In our data-driven world, there is a clear need for individuals from this field who can think analytically, creatively and leverage AI and big data to aid in decision-making. Learn to synthesize and apply statistical and computer science skillsets to ethically extract knowledge and insights from data. The Data Science program has a basis in data wrangling, inferential statistics, analytics, AI, big data and data ethics.
Work Experience
A Co-op option is available. Co-op is the opportunity to get a head start on a career. Co-op work terms allow for the development of key employability skills, exploration of career options and graduation with tangible, workplace experience.
Strong Professional Network
Carleton is heavily involved in Ottawa’s tech sector. Our annual Data Day showcases the work of Carleton researchers and data science experts, and discusses the cutting-edge research and current developments in data science. The Institute for Data Science has an industrial advisory committee with members from IFS, Kx Systems, Shopify, IBM, TACTIX, MindBridge AI, Interset, the Ottawa Police Service, the City of Ottawa, and Statistics Canada, as well as corporate members of the Institute such as Cisco Systems, Invest Ottawa, and CANARIE.
Concentrations
Artificial Intelligence (AI): The concentration in AI allows you to learn more about computer science theory and AI.
Statistics: For students looking to increase their knowledge of inferential statistics and the theory behind it.
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
BDS
Study Level
Undergraduate
Study Mode
On Campus
Data Science is at the intersection of three domains: computer science, mathematics and statistics, and application (e.g. business, social science, health).
The insights of data and analytics influence our everyday lives, from streaming service algorithms to the life altering decisions made by science, industry and government. Data Science combines the practical application of mathematics, statistics, computer science and analytics to extract value from data to infer knowledge from patterns. Data scientists form questions, design the collection and storage of data, write reliable and fast code for wrangling datasets, utilize inferential statistics, machine learning and AI to analyze the data, and present the translated results in a responsible, reproducible and actionable way.
In our data-driven world, there is a clear need for individuals from this field who can think analytically, creatively and leverage AI and big data to aid in decision-making. Learn to synthesize and apply statistical and computer science skillsets to ethically extract knowledge and insights from data. The Data Science program has a basis in data wrangling, inferential statistics, analytics, AI, big data and data ethics.
Work Experience
A Co-op option is available. Co-op is the opportunity to get a head start on a career. Co-op work terms allow for the development of key employability skills, exploration of career options and graduation with tangible, workplace experience.
Strong Professional Network
Carleton is heavily involved in Ottawa’s tech sector. Our annual Data Day showcases the work of Carleton researchers and data science experts, and discusses the cutting-edge research and current developments in data science. The Institute for Data Science has an industrial advisory committee with members from IFS, Kx Systems, Shopify, IBM, TACTIX, MindBridge AI, Interset, the Ottawa Police Service, the City of Ottawa, and Statistics Canada, as well as corporate members of the Institute such as Cisco Systems, Invest Ottawa, and CANARIE.
Concentrations
Artificial Intelligence (AI): The concentration in AI allows you to learn more about computer science theory and AI.
Statistics: For students looking to increase their knowledge of inferential statistics and the theory behind it.
Admission Requirements
6.5+
60+
86+
120+
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
Bachelor of Data Science
Main Campus, Ottawa, Canada
Data Science and Artificial IntelligenceMain Subject Area
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
BDS
Study Level
Undergraduate
Study Mode
On Campus
Data Science is at the intersection of three domains: computer science, mathematics and statistics, and application (e.g. business, social science, health).
The insights of data and analytics influence our everyday lives, from streaming service algorithms to the life altering decisions made by science, industry and government. Data Science combines the practical application of mathematics, statistics, computer science and analytics to extract value from data to infer knowledge from patterns. Data scientists form questions, design the collection and storage of data, write reliable and fast code for wrangling datasets, utilize inferential statistics, machine learning and AI to analyze the data, and present the translated results in a responsible, reproducible and actionable way.
In our data-driven world, there is a clear need for individuals from this field who can think analytically, creatively and leverage AI and big data to aid in decision-making. Learn to synthesize and apply statistical and computer science skillsets to ethically extract knowledge and insights from data. The Data Science program has a basis in data wrangling, inferential statistics, analytics, AI, big data and data ethics.
Work Experience
A Co-op option is available. Co-op is the opportunity to get a head start on a career. Co-op work terms allow for the development of key employability skills, exploration of career options and graduation with tangible, workplace experience.
Strong Professional Network
Carleton is heavily involved in Ottawa’s tech sector. Our annual Data Day showcases the work of Carleton researchers and data science experts, and discusses the cutting-edge research and current developments in data science. The Institute for Data Science has an industrial advisory committee with members from IFS, Kx Systems, Shopify, IBM, TACTIX, MindBridge AI, Interset, the Ottawa Police Service, the City of Ottawa, and Statistics Canada, as well as corporate members of the Institute such as Cisco Systems, Invest Ottawa, and CANARIE.
Concentrations
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
BDS
Study Level
Undergraduate
Study Mode
On Campus
Data Science is at the intersection of three domains: computer science, mathematics and statistics, and application (e.g. business, social science, health).
The insights of data and analytics influence our everyday lives, from streaming service algorithms to the life altering decisions made by science, industry and government. Data Science combines the practical application of mathematics, statistics, computer science and analytics to extract value from data to infer knowledge from patterns. Data scientists form questions, design the collection and storage of data, write reliable and fast code for wrangling datasets, utilize inferential statistics, machine learning and AI to analyze the data, and present the translated results in a responsible, reproducible and actionable way.
In our data-driven world, there is a clear need for individuals from this field who can think analytically, creatively and leverage AI and big data to aid in decision-making. Learn to synthesize and apply statistical and computer science skillsets to ethically extract knowledge and insights from data. The Data Science program has a basis in data wrangling, inferential statistics, analytics, AI, big data and data ethics.
Work Experience
A Co-op option is available. Co-op is the opportunity to get a head start on a career. Co-op work terms allow for the development of key employability skills, exploration of career options and graduation with tangible, workplace experience.
Strong Professional Network
Carleton is heavily involved in Ottawa’s tech sector. Our annual Data Day showcases the work of Carleton researchers and data science experts, and discusses the cutting-edge research and current developments in data science. The Institute for Data Science has an industrial advisory committee with members from IFS, Kx Systems, Shopify, IBM, TACTIX, MindBridge AI, Interset, the Ottawa Police Service, the City of Ottawa, and Statistics Canada, as well as corporate members of the Institute such as Cisco Systems, Invest Ottawa, and CANARIE.
Concentrations
Admission Requirements
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
How to get a full scholarship
Looking for a fully-funded scholarship to see you into university? Find out how to boost your chances of getting one.
Scholarships to study abroad
Find scholarships to study abroad with our lists of international scholarships – categorized by country, by subject, and by type of student.
Scholarship Applications: Frequently Asked Questions
Get answers to all your questions about scholarship applications, including tips on how to find scholarships and chances of success.
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