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CS 404/504 – Special Topics: Python Programming for Data Science

University of Idaho - Department of Computer Science

Instructor: Alex Vakanski

Semester: Fall 2022 (August 22 – December 16)

Course Syllabus

Lectures:

Theme 1: Python Programming

Theme 2: Data Engineering Pipelines

Theme 3: Model Engineering Pipelines

Theme 4: Model Deployment Pipelines

Course Description

With the increased use of data science projects for improving various functions and operations across organizations, the tools for managing such projects have matured as well. This course introduces students to Python tools and libraries that are commonly used by organizations for management of the different phases in the life cycle of data science projects. The content is divided into four main themes. The first theme reviews the basics of Python programming and extends it with advanced concepts. The second theme focuses on data engineering, and covers Python tools for data collection and exploration. The next theme overviews model engineering, and includes model design, training, testing, optimization, and packaging. The last theme introduces Data Science Operations (DSOps), and covers techniques for model serving, performance monitoring, diagnosis, and reproducibility of data science projects deployed in production.

Textbooks

  1. Joel Grus, “Data Science from Scratch: First Principles with Python,” 2nd Edition, O'Reilly Media, 2019, ISBN: 9781492041139.
  2. Chip Huyen, “Designing Machine Learning Systems,” O'Reilly Media, 2022, ISBN: 9781098107963.

Learning Outcomes

Upon the completion of the course, the students should demonstrate the ability to:

  1. Understand and describe commonly used Python frameworks for life cycle management of data science projects.
  2. Apply advanced Python tools for data collection, analysis, and visualization.
  3. Design, validate, and justify the selection of data science models using statistical approaches, data mining, and machine learning methods.
  4. Implement algorithms for image and natural language processing using Python-based frameworks.
  5. Understand the main characteristics of existing Python libraries for deployment, continuous integration, and monitoring of data science projects.
  6. Deploy data science models on cloud servers and edge devices.

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Course page for CS 404/504 Python Programming for Data Science taught in Fall 2022, University of Idaho.

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