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 3 – Python for AI
Most hands-on artificial intelligence work is currently done using the Python programming language. As such, some understanding of Python and computer programming is needed to be successful in applying AI. That said, it is truly astounding how much complex AI research can be accomplished with a few lines of code!
The content in this workshop is aimed at beginning coders who may have never programmed before. As with the rest of the Practicum AI workshops, we use Jupyter Notebooks for the learning experience. A Jupyter Notebook is an easy-to-use, yet powerful tool that supports interactive coding as well as nicely formatted explanatory text. Much of exploratory AI research is conducted in Jupyter Notebooks, and it is easy to transfer code from Notebooks to scripts when it is time to scale up analyses.
Prerequisites – Computing for AI content: Understanding git and GitHub, navigating Jupyter notebooks on Atlas.
Objectives – Learners will be able to:
- Understand Python’s dominance in data science and its role in high-performance computing.
- Develop Python troubleshooting skills, including documentation referencing and error handling.
- Write Python code adhering to best practices for operators, variables, and functions.
- Utilize Python libraries through the import function and understand major AI libraries like TensorFlow and Keras.
- Manipulate and visualize data using Pandas and Matplotlib.