Feburary 01-05,2024
9:00 am - 5:00 pm
Instructors: Mesfin Diro, Dr. Natei Ermias
Helpers: TBA
This Training Workshop aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including data management, data cleaning , Data analysis and Scientific Report Writing. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.
For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".
Who: The training course is aimed researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop.
Where: Ethiopian Public Health Institutes. Get directions with OpenStreetMap or Google Maps.
When: Feburary 01-05,2024. Add to your Google Calendar.
Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below).
Contact: Please email mesfin.diro@aau.edu.et or natei.ermias@aau.edu.et for more information.
| 09:00 | Data Organization in Spreadsheets |
| 10:30 | Coffee |
| 11:00 | Spreadsheets(Continued) |
| 12:00 | Lunch break |
| 13:00 | Data Cleaning in OpenRefine |
| 14:30 | Coffee |
| 15:00 | OpenRefine(Continued) |
| 16:00 | Wrap-up |
| 09:00 | Introduction to machine learning |
| 10:30 | Coffee |
| 11:00 | ML: Linear Models |
| 12:00 | Lunch break |
| 13:00 | ML(continued): Kernelization |
| 14:30 | Coffee |
| 15:00 | ML(continued): Ensemble Learning |
| 16:00 | Wrap-up |
| 09:00 | Classification: Linear models |
| 10:30 | Coffee |
| 11:00 | Classification(continued): Kernelization |
| 12:00 | Lunch break |
| 13:00 | Classification(continued): Ensemble Learning |
| 14:30 | Coffee |
| 15:00 | Classification(continued): Ensemble Learning |
| 16:00 | Wrap-up |
| 09:00 | Introduction to Unsuppervised Learning |
| 10:30 | Coffee |
| 11:00 | Clustering with Scikit Learn |
| 12:00 | Lunch break |
| 13:00 | Dimensional Reduction |
| 14:30 | Coffee |
| 15:00 | Dimensional Reducton(continued) |
| 16:00 | Wrap-up |
| 09:00 | Neural Networks |
| 10:30 | Coffee |
| 11:00 | Neural Networks(continued) |
| 12:00 | Lunch break |
| 13:00 | Convolution Neural Networks(continued) |
| 14:30 | Coffee |
| 15:00 | Convolution Neural Networks(continued) |
| 16:00 | Wrap-up |
| 09:00 | Recurrent Neural Networks |
| 10:30 | Coffee |
| 11:00 | Recurrent Neural Networks(continued) |
| 12:00 | Lunch break |
| 13:00 | Deploy Machine Learning models |
| 14:30 | Coffee |
| 15:00 | Deploy Machine Learning models(continued) |
| 16:00 | Wrap-up |
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
Requirements: The training is hands-on, so participants are encouraged to bring in and use their own laptops to insure the proper setup of tools for an efficient workflow once you leave the workshop. (We will provide instructions on setting up the required software several days in advance) There are no pre-requisites, and we will assume no prior knowledge about the tools.
To participate in a training workshop, you will need working copies of the software described below. Please make sure to install everything and try opening it to make sure it works before the start of your workshop. If you run into any problems, please feel free to email the instructor or arrive early to your workshop on the first day. Participants should bring and use their own laptops to insure the proper setup of tools for an efficient workflow once you leave the workshop.
We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.
For this workshop you will need a spreadsheet program. Many people already have Microsoft Excel installed, and if you do, you're set! If you need a spreadsheet program, there are a few other options, like OpenOffice and LibreOffice. Install instructions for LibreOffice, which is free and open source, are here.
OpenRefine (previously Google Refine) is a tool for data cleaning that runs through a web browser, and any browser - Safari, Firefox, Chrome, Explorer - should work fine. You will need to download OpenRefine and install it, and when you open it, it will run through the browser, but you don't need an internet connection, and the data will all be stored on your computer.
Python is a popular language for research computing, and great for general-purpose programming as well. Installing all of its research packages individually can be a bit difficult, so we recommend Anaconda, an all-in-one installer.
Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., 3.4 is fine).
We will teach Python using the IPython notebook, a programming environment that runs in a web browser. For this to work you will need a reasonably up-to-date browser. The current versions of the Chrome, Safari and Firefox browsers are all supported (some older browsers, including Internet Explorer version 9 and below, are not).
bash Anaconda3-and then press tab. The name of the file you just downloaded should appear. If it does not, navigate to the folder where you downloaded the file, for example with:
cd DownloadsThen, try again.
yes and
press enter to approve the license. Press enter to approve the
default location for the files. Type yes and
press enter to prepend Anaconda to your PATH
(this makes the Anaconda distribution the default Python).