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Computing for AI

Practicum AI

Practicum AI is a hands-on applied artificial intelligence (AI) curriculum intended for learners with limited coding and math background. To register for these courses, please fill out the registration form. You do not need to register for all courses and may instead register for only the courses that are most relevant to your work. You will need a SCINet account for this course. If you do not have a SCINet account, you may request one.

Course 2 – Computing for AI

This course is the second in the Practicum AI series. This course can also be taken on its own to familiarize yourself with some of the important tools used in data science and scientific computing.

In this course, you will learn about some of the tools recommended for building, testing, tweaking, and deploying AI models. You will learn about Jupyter Notebooks, Git, GitHub, and high-performance computing (HPC) environments. These are the key technologies that have become the industry standards for hands-on applied AI research and development.

Prerequisites – 1) A GitHub account and 2) a SCINet account.
Objectives – Learners will be able to:

  1. Describe essential technologies for hands-on AI applications, including Jupyter notebooks.
  2. Understand the role of Jupyter notebooks in AI data analysis and model development.
  3. Launch and use a Jupyter notebook session on SCINet’s Atlas cluster.
  4. Recognize the significance of version control for open and reproducible AI projects.
  5. Create and use a git repository.
  6. Grasp the computational demands of AI and the need for GPU-enhanced high-performance computing environments.