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SLAS2020 Short Courses

Streamlining your Laboratory with Python, an Introduction (Laptop Required)

Python is one of the most popular multi-purpose, cross-platform programming languages due to its ease of use, rich library and broad range of applications. This introductory and hands-on course will teach you the basics of Python programming and how to use it to solve authentic tasks commonly encountered in a scientific laboratory. Topics covered include data handling, analysis and report generation and task automation.

Bring your own laptop with software installed or create a free account with our cloud-hosted Data Science Platform partner.

Who Should Attend

  • Scientists working with data of all types
  • Laboratory managers interested in reducing data to interpretable results
  • Integrators with a need to monitor automated system operation
  • Students with a desire to learn how to wrangle and present their results

Course Benefits

  • Learn the basics of Python programming from seasoned instructors
  •  Learn how to load data from a variety of sources and transform into analyzable data structures
  • Perform basic data analysis and be introduced to Python’s statistical capabilities
  • Discover how to monitor the file system for changes and process data automatically
  • Explore Python’s ability to generate reports in various formats
  • Learn how to communicate results automatically
  • Package your programs for distribution to various operating systems

Course Topics

  • Introduction to Python and its role in a scientific laboratory
  • Data types and expressions
  • Sequencing of tasks, conditional execution and iteration
  • Accessing data from files, spreadsheets, databases and web services
  • Data munging, basic statistics and scientific plotting
  • CreatingWord and PDF files
  • Watching for changes on a file system
  • Sending email and SMS messages
  • Distributing your Python programs

Instructors

Mark Russo

Mark F. Russo. Ph.D.
Department of Computer Science
The College of New Jersey

Mark Russo received a Ph.D. in Biochemical Engineering in 1989. He has held positions in the biotechnology and pharmaceutical industries in the fields of scientific computing, laboratory automation, data system design and development and software architecture. Russo has served the SLAS for many years, including as a short course instructor, session and track chair and as a past editor of the Journal of Laboratory Automation (JALA). He has also published numerous scientific articles and book chapters on topics related to scientific computing and laboratory automation. Currently, he works in the pharmaceutical industry in translational bioinformatics and also teaches computer science at The College of New Jersey (Ewing).

William Neil

William Neil
West Belmar, NJ

William Neil received a B.S. in chemistry and biology from Trenton State College in 1981. For several years he worked with the Toxicology Division of Mobil Oil Corporation where he developed his interest in computer programming and laboratory automation. In 1987 he wrote his first application to automate data collection from a liquid scintillation counter and installed his first robotics system to automate a Packard biological oxidizer. He then took a two-year sabbatical to focus entirely on laboratory automation at International Flavors and Fragrances (IFF), where he automated fragrance sample compounding. It was at IFF where he learned how to ensure a 24/7 operation. Sine 1995 Neil has been employed in the pharmaceutical industry, where he has written several applications in Visual Basic and VBA to automate the drug discovery process, particularly in the area of instrument integration.


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