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Carnegie Mellon Cloud Lab training will allow the user to understand where to begin with the Carnegie Mellon Cloud Lab and receive certification and support for grants.
The learning process
Stage 1:
Introduction to the Carnegie Mellon Cloud Lab Facility and Software:
Welcome to the first step of your scientific journey in the Carnegie Mellon Cloud Lab Training Program. In these initial modules, we will introduce you to the fascinating world of the cloud lab and the essential software tools that form its backbone.
Cloud Lab Exploration:
We’ll begin with an exploration of the cloud lab concept, where you’ll discover the immense potential it offers for scientific research. Through an engaging virtual tour, you’ll gain insights into the advantages of conducting experiments in a cloud-based environment.
Software Familiarization:
Next, we’ll dive into the software essentials. You’ll be guided through a hands-on tour of the software applications you’ll be using throughout your scientific endeavors. Expect to learn the different tools and functions, from setting up your notebook to navigating the interface effectively.
Stage 2:
The Cloud Lab Training Program has been designed to provide a structured and comprehensive approach to training, ensuring that users can progressively build their skills and knowledge at their own pace while aligning with their individual goals and experience levels.
Created by Experts:
During your training journey, you’ll be guided through simple modules showcasing specific knowledge and tools for the Carnegie Mellon Cloud Lab as well as complex scientific workflows demonstrating how to perform scientific research inside the cloud lab. These modules and workflows have been designed and curated by experienced instructors who are passionate about helping you succeed. They will be there to answer your questions and provide valuable insights to make your learning experience rewarding and enjoyable.
Practical Exercises:
To solidify your understanding, we’ll provide practical exercises that will allow you to get your hands dirty (virtually, of course). You’ll perform basic tasks, such as configuring experiments and run analysis, all within the cloud lab software environment.
Interactive Learning:
Our training modules are designed with interactivity in mind. You’ll find quizzes, simulations, and opportunities to discuss your progress with fellow learners through our forum. As you progress through this training program, you’ll gain the foundational knowledge and skills needed to embark on your scientific experiments within the Carnegie Mellon Cloud Lab. We can’t wait to see how you leverage this innovative platform for your research. Let’s get started!
Basic Training Program:
The Basic Training Program is the entry point for users new to the cloud lab. It provides foundational knowledge and skills necessary to navigate our platform successfully. Participants will be introduced to the concept of the cloud lab, familiarize themselves with the software and tools used, and learn how to efficiently prepare, run, and analyze their experiments. This level is designed to establish a strong fundamental understanding of the platform.
Advanced Training Program:
The Advanced Training Program is ideal for users who have completed the Basic level or already possess a basic understanding of the cloud lab. In this program, participants will delve deeper into their training, covering essential topics such as laboratory safety, open science principles, advanced research techniques within a cloud lab environment and the creation of scientific workflows. This level aims to equip users with the skills and knowledge needed to conduct scientific research effectively and collaboratively in a cloud-based setting.
Expert Training Program:
The Expert Training Program is tailored for experienced users who have a solid foundation in the scientific cloud lab and want to take their expertise to the next level. Participants at this level have the opportunity to specialize in various roles, including becoming an instructor, lab developer or scientific developer. This program offers advanced, specialized training to empower users with the skills and knowledge required to not only excel as researchers but also to contribute to the development and growth of the scientific cloud lab ecosystem.
Stage 3:
Upon successful completion of the Basic and Advanced Training Programs, users will undergo an assessment process to evaluate their competency and knowledge. This evaluation will include quizzes and hands-on exercises designed to ensure they have acquired the necessary skills. Once they pass these assessments, they will be awarded a Cloud Lab Scientific Certification.
Certification Process:
This certification not only recognizes their expertise but also grants them the authorization to independently run experiments within the cloud lab. What’s more, this certification is designed to be compatible with other existing Cloud Labs (ECL) and future cloud labs, allowing users to showcase their proficiency across a broader spectrum of platforms. Additionally, users have the option to include this prestigious certification in their curriculum, bolstering their academic and professional profiles.
Completion Requirements:
To earn a Cloud Lab Scientific Certification, participants would need to successfully complete all the required training modules from the Basic Training, and all designated training modules, assessments and any practical exercises from the Advanced Training.
Assessment:
The certification assessment involves a combination of multiple-choice quizzes and hands-on assignments that showcases the application of the participants’ knowledge. This includes demonstrating proficiency in using the software, tools and techniques introduced in the training program. The participants should also demonstrate a comprehensive understanding of laboratory safety, open science principles and the ability to conduct research within a cloud lab.
Stage 4:
Maximizing the Cloud Lab’s Efficiency
The Carnegie Mellon Cloud Lab subscription model is designed to optimize resource allocation and ensure efficient usage of the facility. To be able to start running experiments and after obtaining their Cloud Lab Scientist Certification, users can subscribe to the Carnegie Mellon Cloud Lab based on the number of threads they require for their experiments.
Thread-Based Subscription: Subscribers can choose from various thread options, which determine the maximum number of experiments they can run concurrently. Each thread corresponds to one active experiment in the lab at any given time.
For instance, a subscription with three threads allows users to run up to three protocols simultaneously. If all allocated threads are in use, any additional protocols or instructions are intelligently placed in a backlog queue. As currently executing protocols are completed and threads become available, the queued protocols will automatically enter execution in the order they were received.
This thread-based subscription model ensures efficient use of the Cloud Lab’s resources, guaranteeing that every experiment gets its fair share of processing power while minimizing downtime and wait times for users.
This model efficiently manages the use of resources and ensures a smooth and organized workflow for users in the Carnegie Mellon Cloud Lab, helping to maximize the facility’s capabilities.