Sort by
Refine Your Search
-
University of Toronto Faculty of Information Sessional Lecturer Winter Term 2026 (January - April) INF2179H – Machine Learning with Applications in Python Course Description: Machine learning has
-
operations management, proficient in Python, and the ability to manage grades and course admin tasks on Quercus. Class Schedule: Courses may be online or in person depending on circumstances, so candidates
-
using Python. Python and IBM Watson Analytics are modeling and visualization software used in this course. Practical aspects of computational models and case studies in Interactive Python are emphasized
-
work independently and autonomously Proficiency in programming languages such as SQL, Python or R and datavisualization tools Assets (Nonessential): Experience working with startups, technology companies
-
gained through experience or advanced training. Working knowledge of analytics tools and technologies such as SAS, R, Python, MS SQL Server, as well as visualization technologies such as, PowerB and/or
-
Python, Ruby, Javascript, and Unix/Linux shell Demonstrated experience and ability in building application software using web frameworks, and troubleshooting web applications Ability to communicate
-
, Python, or C/C++, with the ability to develop custom scripts and algorithms for data analysis and modeling. Familiarity with rheological characterization techniques, such as rheometry or viscometry
-
data science tools and techniques (e.g., Python, R), database design and management, algorithmic auditing, human-centered design, and interdisciplinary research methods bridging technical, social, and
-
-level Unix-based server applications. Strong scripting skills required including Shell, bash, Python, and/or other interpreted languages. Experience configuring databases and database-backed applications
-
maintain ETL pipelines for data warehouses. Exceptional analytical skills, showing fluency in SQL, Python, Java, or Scala. Knowledge of cloud platforms such as AWS, Azure, GCP. Ability to effectively