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STAT 161 Introduction to Data Science Units: 3.00
This course introduces critical concepts, tools, techniques and skills in statistical inference/learning, machine learning, and computer programming, through hands-on analysis of real-world datasets from diverse fields in science and social science. It offers three perspectives (inferential thinking, computational thinking and real-world relevance) on the foundations of Data Science and develops a data-oriented mindset.
Learning Hours: 132 (36 Lecture, 12 Laboratory, 84 Private Study)
Requirements: Prerequisite None.
Recommended An Ontario 4U mathematics course or equivalent.
Exclusion Maximum of one course from: BIOL 243/3.0; CHEE 209/3.5; CISC 171/3.0; COMM 162/3.0; ECON 250/3.0; GPHY 247/3.0; HSCI 190/3.0; KNPE 251/3.0; NURS 323/3.0; POLS 285/3.0; POLS 385/3.0*; PSYC 202/3.0; SOCY 211/3.0; STAM 200/3.0; STAT 161/3.0; STAT 263/3.0.
Exclusion Maximum of one course from: PATH 111/3.0; STAT 161/3.0.
One-Way Exclusion May not be taken after STAT 269/3.0.
Offering Faculty: Faculty of Arts and Science
Course Learning Outcomes:
- Work with critical concepts, tools, techniques, and skills in computer programming, statistical inference/learning and machine learning.
- Use visualization to understand data.
- Work with the computational tools and practices for summary, analysis, and visualization of data.
- Analyze real data sets and communicate their results.
- Have a basic understanding of the implications and tools of data collection.