Faculty of Computing & Data Sciences

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  • Undergraduate Tutoring Center

    • CDS DS100 - Data Speak Louder than Words

      30 minutes

      Covers the three perspectives that are fundamental to their ability to reason with data: critical thinking, inferential thinking, and computational thinking. Through data modeling and visualization, students will construct and communica ...

    • CDS DS110 - Introduction to Data Science with Python

      30 minutes

      Students will use Python to explore fundamental CS concepts and processes used in data science with a focus on descriptive data analysis, including data structures, development of functions and more advanced recursion, object- oriented ...

    • CDS DS120 - Foundations of Data Science I

      30 minutes

      Introduction to key concepts from Calculus (differentiation and integration), Probability (discrete and continuous random variables) and Linear Algebra (vector spaces, matrices, and linear systems). The course links mathematics and comp ...

    • CDS DS121 - Foundations of Data Science II

      30 minutes

      Covers an introduction to key concepts from Linear Algebra (vector space, independence, orthogonality and matrix factorizations). The DS theme running through the course is exploratory data analysis, enabling a better understanding of t ...

    • CDS DS122 - Foundations of Data Science III

      30 minutes

      Covers topics in probability (including common probability distributions, conditional probability, independence, Bayes Theorem, prior and posterior distributions, sampling, and the central limit theorem), statistics (including maximum l ...

    • CDS DS210 - Programming for Data Science

      30 minutes

      First half continues the programming experience begun in DS110, with enhanced focus on machine learning applications. Later, the course introduces students to compiled programming languages, such as Rust, Go and Java, suitable for build ...

    • CDS DS310 - Data Mechanics

      30 minutes

      Focused on developing capacity to design and implement data flows and the computational workflows meant to inform online/offline decision- making within large systems. Data science lifecycle, including question formulation, data collect ...

    • CDS DS320 - Algorithms for Data Science

      30 minutes

      Fundamental principles underlying the design and analysis of algorithms. Including classical design methods, such as greedy algorithms, design and conquer, and dynamic programming, focusing on applications in data science. Algorithmic m ...

    • CDS DS340 - Introduction to Machine Learning & Artificial Intelligence

      30 minutes

      This course instructs students in key algorithms for classic artificial intelligence (AI) and modern machine learning (ML). Along the way, we seek to explore what kinds of problems these techniques are good and bad at, and build intuiti ...