Deployment architectures

Module title:

Deployment architectures

Module overview:

The module guides students through a progressive learning path in mastering the fundamental skills for implementation of effective data science services. Starting with the demonstration of basic Linux skills, students advance to executing specialized Linux commands tailored for data science applications. In the realm of containerization, students implement both simple and multi-container data services, gaining insights into scalable and efficient deployment strategies. The focus on version control evolves from basic proficiency to advanced mastery, ensuring students are well-prepared for collaborative project management. The course culminates in exposing data services within deployment architectures, requiring students to showcase and secure data services with a commitment to data integrity and user privacy.

In this module students will:
Explore and practice elementary Linux operations tailored for data science applications.
Master containerization concepts and techniques for efficient deployment of data services.
Acquire proficiency in using version control systems, with a focus on GIT for effective collaboration.
Collaborate on real-world projects to apply learned concepts and develop a holistic understanding of deployment architectures.

Literature:

Required readings:
1. Nfonsang, N. (2021). Linux fundamentals: A Practical Guide for Data Scientists, Machine Learning Engineers, and IT Professionals

Supplementary readings:
1. Skoulikari, A. (2023). Learning git: A hands-on and visual guide to the basics of git. O’Reilly Media
2. Kane, S. P., and Matthias, K. (2023). Docker - up and running: Shipping reliable containers in production (3rd ed.). O’Reilly Media