ASU New College B2C2 Data and Methods Student Workshop (Virtual)

Come to join us and learn must-have skill (data analytics, Python coding, artificial intelligence, machine learning, and data-driven research) for today’s students and researchers in a one-day workshop.

Date: Saturday, November 21, 2020
Time: 9:00AM - 4:00PM
Registration: https://asu.zoom.us/meeting/register/tZwudOugqzMoGNBDzCAuP75zKN8M1tx4C-f5
Download flyerPDF icon b2c2_workshop.pdf

Free to ASU Students. Limited virtual seats. Early RSVP is highly recommended. After registering, you will receive a confirmation email containing information about joining the meeting.

Data and Methods Student Workshop Agenda

1. Introduction to Artificial Intelligence (9AM – 9:50AM)

This module will teach students with little or no knowledge of computer science to learn the basic concepts, terms, and applications of artificial intelligence (AI).

Prerequisites: None

2. Introduction to Python Programming (10AM – 10:50AM)

This module will teach students with little or no programming background to learn Python programming with hands-on Jupyter notebooks on Google Colab.

Prerequisites: None

3. Introduction to Machine Learning (11AM – 11:50AM)

This module will introduce the basic concepts and algorithms of machine learning and its power in solving real world problems.

Prerequisites: None

4. Supervised Learning (1PM – 1:50PM)

This module will do a deep dive on one of the main types of machine learning: supervised learning. Students will learn decision trees, k-nearest neighbors, and neural networks for exploring data sets with targets or labeled variables for different real-world applications.

Prerequisites: Introduction to Artificial Intelligence, Introduction to Machine Learning

5. Unsupervised Learning (2PM – 2:50PM)

This module will introduce students to the second main type of machine learning: unsupervised learning. Students will learn different clustering techniques for discovering insights from data sets that do not have a target or labeled variable.

Prerequisites: Introduction to Artificial Intelligence, Introduction to Machine Learning

6. Data Analytics in Python (3PM – 3:50PM)

This module will introduce simple data analytics capabilities in Python language. In this module, the students will get hands-on experience on Python packages (e.g., NumPy, scikit learn) to plug and play using Jupyter notebooks on Google Colab.

Prerequisites: Introduction to Python Programming

COVID-19 information

Fall 2021 Update page  |  FAQ page   | Novel coronavirus updates