APPLY: Practice Makes Perfect
Something magic happens when you apply your new skills in a live environment. Hands-on Labs are on-demand experiences using data-intensive cyberinfrastructure within the Praxis platform.
Hands-On Labs – Apply what you have learned using AI workflows and on-demand labs.
Discover the future of hands-on learning with AI-powered virtual labs running in a Linux environment in the cloud so you don’t have to install software on your own computer. Our platform revolutionizes the traditional hybrid classroom experience by providing students with immersive, interactive, and engaging virtual labs that teach computational problem-solving skills desperately sought by public and private employers.
The Praxis LXP leverages the latest in AI technology to create a realistic and dynamic learning environment that allows students to explore, experiment, and apply what they have learned in a safe and controlled virtual setting.
Benefits to the student include:
- Hands-on experience with cutting-edge technology
- Improved engagement and retention of knowledge
- Access to data-intensive computing scenarios not possible on your laptop
- Persistent digital “locker” where you can store all your files and discoveries
- Online portfolio of your deliverables via integrated GitLab environment
- The ability to repeat experiments and activities to reinforce learning
- Flexible and convenient learning that can be accessed from anywhere
- Gaining experience in workforce ready technical skills
For learning institutions, our platform offers a valuable solution for delivering hands-on learning experiences that challenge and inspire students. By integrating AI-powered virtual labs, institutions can:
- Enhance the learning experience for students
- Offer innovative and cutting-edge learning experiences
- Foster student engagement and knowledge retention
- Save resources and time previously spent on physical lab setup and maintenance
- Increase the institution’s reputation as a leader in technology-enhanced education.
Here is a list of cutting-edge virtual lab topics included in our programs, along with the virtual lab infrastructure and technologies required to deliver each topic:
Genomics and Bioinformatics
- Virtual lab infrastructure: Linux Environment, Jupyter Lab, High-Performance Computing (HPC) Clusters, Cloud Infrastructure and Services, Virtualized Server Infrastructure
- Technologies: Bioinformatics Tools and Platforms (e.g. Bioconductor, Nextflow, SRA Toolkit), Sequence Analysis Software (e.g. FASTQC, SAMtools, BWA, Hisat2, BLAST, GEMMAKER, DESeq2, genome assemblers), Software Development and Programming Languages (e.g. Python, R, bash scripting)
- Data mining: Search, download, and mine from powerful open-source databases (e.g. NCBI, ENSEMBL, UCSC genome Browser, GTEx, NCI Genome Data Commons)
- Real world lab activities tailored for specific disciplines: Medical bioinformatics, Veterinary genomics, Plant genomics, Conservation genomics
Foundations of AI
- Virtual lab infrastructure: Jupyter Lab, Cloud Infrastructure and Services, Virtualized Server Infrastructure
- Core Python libraries: numpy, pandas, matplotlib, scipy, seaborn, sklearn, keras, tensorflow
- Applied lab topics: Statistical hypothesis testing, Linear algebra for machine learning, Exploratory data analysis (EDA), Data visualization in Python, Linear regression, Feature engineering and dataset curation, K-nearest neighbor classification, Decision tree classification, Model evaluation and hypertuning, Multi-layer perceptrons and deep neural networks, Natural language processing (NLP), Convolutional neural nets for image classification, Generative AI and the transformer model, Using APIs to access open-source AI models, Engagement with generative AI, Creating vector embeddings of data with OpenAI.
Foundations in Data Science
- Virtual lab infrastructure: R Studio, R Shiny, Cloud Infrastructure and Services, Virtualized Server Infrastructure, Remote Access and Virtual Desktop Infrastructure (VDI)
- Applied lab topics: Data visualization, Plotting with GGPlot, Curating data for missing values, Advanced plots with Plotly, Detecting statistical outliers, Creating Heatmaps, Exploratory data analysis, Sentiment Analysis, Accessing social media APIs, Developing interactive data apps
- Virtual lab infrastructure: Fedora Linux Desktop, Cloud Infrastructure and Services, Remote Access and Virtual Desktop Infrastructure (VDI), Processing programming environment
- Applied lab topics: Technologies: Game Design Fundamentals, Evaluating Formal Elements of Games , Evaluating Dramatic Elements of Games, Evaluating System Dynamic of Games, Conceptualization, Prototyping, Digital Prototyping, Playtesting, Testing for Functionality, Accessibility ,Working in Teams, Agile Development and Project Planning , Communicating Game Designs, Understanding the Game Industry
Systems Biology and Transcriptomics
- Virtual lab infrastructure: High-Performance Computing (HPC) Clusters, Cloud Infrastructure and Services, Virtualized Server Infrastructure
- Technologies: Metabolomics Analysis Software (e.g. XCMS, MetaboAnalyst), Systems Biology Simulation Software (e.g. Copasi, SBML), Data Science and Big Data Analytics Tools (e.g. Apache Spark, Hadoop), Software Development and Programming Languages (e.g. Python, R, bash scripting)