Just a few decades ago, corporate training programs consisted mostly of onsite instructor led training (ILT) where instructors used computers and projectors to display slides for students in a traditional classroom setting.
The modern laboratory produces vast amounts of data from a wide variety of sources that are too often not integrated, creating data silos that impede digital transformation efforts. This drives the need for a successful LIMS implementation.
In this 2021 journal article published in Molecules, Pieracci et al. present the results of a two-year analysis and comparison of cannabis constituents in the essential oil of 11 hemp genotypes using gas chromatography—mass spectrometry (GC-MS). Noting prior researchers' difficulties in comparing "the chemical composition of the essential oils extracted from different Cannabis sativa L. genotypes," the researchers strived to conduct a thorough examination, demonstrating the ability of GC-MS methods to make the analyses necessary to determine most constituents, as well as "promote their employment as value-added by-products based on their peculiar characteristics." Through their efforts, the researchers were able to identify 116 compounds, representing 90.6–99.4% of the total composition of the essential oils (EO) gathered. After analyzing their results, the authors concluded "that both the EO chemical profile and extraction yield were significantly influenced by the genotype of the starting material, the year of cultivation, and the interaction between these two factors."
This is a Rochester Institute of Technology-created course that is released on the edX platform. The introductory eight-week course is designed to help learners "learn cybersecurity fundamentals, including how to detect threats, protect systems and networks, and anticipate potential cyber attacks." The course is free to take. A verified certificate of completion from RIT is available afterwards for $249 USD. Two sessions are currently available: January 5 to March 2, and March 30 to May 25.
This is an advanced University of Adelaide-created course that is released on the edX platform, and is part of a university MicroMasters Program. The scheduled 10-week course is designed to help learners to better "apply computational thinking in data science" using tools such as "mathematical representations, probabilistic and statistical models, dimension reduction and Bayesian models." The course is free; a certificate of completion costs $249. The course requires on average eight to 10 hours a week of effort. Access to the class is on-demand.