Change-HI/EDU

Experiential Learning "Active" learning opportunities

This page collects together all of the “experiences” associated with individual modules.

In this site, experiences are used to represent the sequence of activities for participants in a workshop.

Module: Introduction to HI-DSI Data Fellows

HI-DSI Data Fellows Fall 2023 Onboarding

Forms and data to submit to get started.

Module: Python and Jupyter

Python Tutorial (Python.org)

Learn Python by following the official Python.org tutorial

Tutorial

Python Tutorial (Free Code Camp)

Learn Python through a video tutorial by FreeCodeCamp

Tutorial Video (4.5 hrs)

Jupyter Tutorial (DataCamp)

Learn Jupyter through a tutorial by DataCamp

Tutorial

Module: Design and Implementation of Workshops

1. Ice Breaker

Climate Change Model

2:00pm-2:10pm

2. Introduction to Workshop Development using Morea

What are workshops? How are they different from seminars?

2:10pm-2:30pm

3. Workshop Setup

Set up a local copy of the Workshop repo

2:30pm-2:45pm

4. Workshop Development, Part 1

Unlock the Best Ever Recipe workshop

2:45pm-3:00pm

5. Workshop Development, Part 2

Document your choice for the Best Ever Recipe

3:00pm-3:25pm

6. Workshop Development, Part 3

Commit your changes and make a pull request

3:25pm-3:30pm

7. Workshop Demos

Let’s see who has the best recipe

3:30pm-3:35pm

8. What's Next?

How to apply your workshop design and implementation skills in future

3:35pm-3:40pm

9. Pick your workshop

Provide your preferences for the workshop you will present this year.

3:40pm-3:50pm

Module: How to create a professional portfolio

1. Ice Breaker: What keeps you up at night?

Tell your group about a (professional) problem

2:00pm-2:10pm

2. Introduction to Professional Portfolios and TechFolios

What are professional portfolios? Why use TechFolios?

2:10pm-2:20pm

3. What is a high quality portfolio

Characteristics of a high quality portfolio

2:20pm-2:30pm

4. TechFolios Quick Start: Initialization

Create an initial version of your portfolio repo

2:30pm-3:00pm

5. TechFolios and GitPod

Learn how to speed up portfolio development using GitPod

3:00pm-3:30pm

6. Choose your own adventure

Work on whatever part of your portfolio you want

3:30pm-3:50pm

Module: Scientific Software Basics

1. Icebreaker: What are you excited for?

What is everyone excited for

2:00pm

2. Introducing the Shell

What is a command shell and why would I use one?

2:10pm

3. Navigating Files and Directories

Navigating Files and Directories

2:20pm

4. Working With Files and Directories

Creating, Copying and Deleting Files

2:40pm

5. Pipes and Filters

Combining Existing Functions to do New Things

2:55pm

6. Loops

Looping Functions

3:20pm

7. Shell Scripts

Saving and Reusing Commands

3:35pm

8. Finding Things

Locating Files

3:50pm

Module: High Performance Computing

1. Ice Breaker: How do you use computing?

Tell your group about a current computing project.

2:00pm-2:10pm

2. What is High Performance Computing (HPC)?

What is an HPC System? What are the components of an HPC system?

2:10pm-2:20pm

3. Connecting to a remote HPC System

Understand how to connect to an HPC system and the basics of Open OnDemand

2:20pm-2:40pm

4. Launch a Jupyter Lab in Open OnDemand

Requesting computing resources on Koa

2:40pm-2:50pm

5. Install Modules and Setup an Environment

Create an environment and setup a Python kernel

2:50pm-3:10pm

6. Deep learning CPU vs GPU

A basic Deep Learning tutorial on Koa

3:10pm-3:40pm

7. Staging and File System Choice

What is a file system? What is a distributed file system? How do you optimize the file system on Koa?

3:40pm-3:50pm

Module: Data Movement

1. Ice Breaker

Data Movement Ice Breaker

2:00pm

2. Introduction to Scientific Data Networks

Understand how networks connect everything and how UH is connected.

2:05pm

3. Networks

Understand what networks, and the equipment that connects everything, look like.

2:10pm

4. Data Transfer Evaluation of the Network

Understand what tools we use to test network throughput.

2:15pm

5. Processes and Queues

Understand how data actually moves between machines and explain queues and buffers.

2:20pm

6. Transmission Control Protocol (TCP)

Understand what transmission control protocol is.

2:25pm

7. Transfer Programs

Be able to identify common/best transfer applications.

2:30pm

8. Globus

Understand what Globus is.

2:35pm

9. Globus Installation

Understand how to setup and use Globus to move data.

2:45pm

10. Transferring Data using Globus

Understand how to setup and use Globus to move data.

2:55pm

11. Configuring and Using Rclone

Understand how to configure and use Rclone.

3:05pm

12. Transferring Files with Rclone

Understand how to transfer files using Rclone.

3:25pm

Module: Data Wrangling, Part 1

1. Data Wrangling Introduction

Understand why Jupyter Notebooks are useful for data wrangling

2:10pm

2. Google Colab Interface

Understand how the google colab interfrace is setup

2:20pm

3. Loading and Handling Pandas Data

Understand Pandas data structures basics

2:25pm

4. Accessing and Subsetting Data

Understading the basics of data accessing and subsetting

3:05pm

5. Common Methods on Series or DataFrames

Understanding the basics of the Pandas data structure - DataFrames

3:30pm

Module: Data Wrangling, Part 2

6. Applying Function to Data

Learning about functions that can be applied on Series and DataFrames

2:10pm

7. Applying GroupBy Operations

Understanding how to apply groupby operations

2:35pm

7. Real Example Cleanup

A real world example of data cleaning

3:05pm

9. Real Example Analysis

An example of data analysis

3:25pm

Module: Exploratory Time Series Analysis in R

1. Ice Breaker: Climate Fresk

Complete the Climate Fresk Challenge

2:00pm-2:10pm

Lab & Mini Lecture 1: What is Time Series Data?

Introduction to Time Series Data

2:10pm-2:40pm

Lab & Mini Lecture 2: Stationarity

Testing for Stationarity

2:40pm-3:10pm

Lab & Mini Lecture 3: Modeling & Cross-Correlating

Explore causality through decomposing time series and then cross-correlating data sets.

3:20pm-3:50pm

Module: Machine Learning Approaches in Climate Science

1. Ice Breaker

ML for Climate data Ice Breaker

2:00pm - 2:05pm

2. Scikit-Learn

A basic Scikit-learn tutorial using Gaussian Processes to model CO2 levels on Mauna Loa

2:05pm - 2.55pm

3. Pytorch

Pytorch tutorial for prediction of El Niño Southern Oscillation (ENSO) phase using sea surface temperature maps

3:00pm - 3:50pm

Module: Smart Data Collection for Sensor Networks

1. Introduction to smart data collection for sensor networks

What is Tapis? What is the Streams API? What is Abaco?

2:00 - 2:15pm

2. Connecting to Jupyter

How do we deploy and access a Jupyter notebook server using Koa?

2:15 - 2:30pm

3. Installing Jupyter Libraries

How do we access Tapis using a Jupyter notebook within MANA?

2:30 - 2:45pm

4. Tapis Streams

How can we use the Streams API to mimick a real-world sensor network?

2:45pm - 3:30pm

5. Tapis UI

How can we use Tapis UI to view sensor station data?

3:30pm - 3:45pm

Module: Creative Thinking

What Does Science Say About Creativity?

Where do we start?

2:05pm

Conditions for Creativity

Cultivating a Creative Environment

2:20pm

Collaboration and Creativity

Diversity of Thought

2:35pm

Mechanics of Creativity

Trusting the Process

3:00pm

Creative Thinking Exercise

Putting Pen to Paper

3:20pm

Key Points

Wrapping Things Up

3:45pm

Module: Data Visualization

1. Why use data visualizations?

Why use data visualizations?

2:00pm

2. Design Principles for Visualizations

Design Principles for Visualizations

2:30pm

3. Beyond Basic Charts

Beyond Basic Charts

2:40pm

4. Creating Visualizations with Code

Understand how to create visualizations with code

2:45pm

5.Creating Visualizations Using Tableau

Understand Tableau implementation basics

3:10pm