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Methods Courses

Python Workshop by Nicholas Del Grosso

The workshop will take place on five Fridays !

When: 24.01.2020, 31.01.2020, 7.02.2020, 14.02.2020 and 6.03.2020

Where: TBC

Course Description:
In this hands-on workshop, we cover the basics of the Python programming language and some of its scientific library in order to enable students to conduct data analysis using the core principles of good scientific practice, focusing on techniques for performing essential data analysis steps using real-life problems that the practicing scientist regularly encounters in his/her work. Libraries covered will be NumPy, matplotlib, Pandas, Seaborn, Scipy-Stats, and Scikit-Learn. Students will learn to write their own functions, scripts, and Jupyter Notebooks in order to perform reproducible data analyses on a wide variety of data types, with a focus on tabular and image data. No prior programming, math, or statistics knowledge is required. Participants will receive a certificate of completion at the end of the course, and will leave with increased confidence in their ability to use computational tools in their research.

Major Focuses of the Course:
Fundamentals of Programming (Scripts, Functions, Loops, Conditionals, and Modules)
Python Data Structures (Lists, Tuples, Dictionaries, Arrays, and DataFrames)
Reading and Writing to Various File Formats (CSV, HDF5, SQL, and Image Formats)
Writing Code to Building Publication-Ready Figures
Fitting Statistical Models to Data with Statsmodels, Scikit-Learn, and PyMC3
Good Coding Practices (Version Control, Code Organization, Styling Practices, Pair Programming, and Literate Programming)
Data Analysis Workflows (NbConvert and SnakeMake)
Reproducibility Practices in Open Science (Dependency Management, Executable Analysis, DOIs)
Understanding the Terminal and the Core Scientific Software Stack (Bash, Compilers, and Interpreters)

Requirements:
Laptop Computer, brought to each class day, with the (free) Anaconda software installed.

Please note that attending the 5 sessions is mandatory to be eligible for the ECTS !

Sign up per email: lsm@bio.lmu.de

Processing and Analysis of Scientific Images/Advanced Image Analysis by Jan Brocher

When: 21-24 April 2020

Where: TBC

Please bring your own laptop!

Sign up per email: lsm@bio.lmu.de

 

Please contact the lsm@bio.lmu.de if you are interested in learning a specific method.

Please note: LSM students should participate in at least two methods courses during their doctoral study.

LSM students are encouraged to attend methods workshops in foreign labs. For this purpose they can apply for the reimbursement of travel expenses and participation fees. Participation should be organized by the student.

Cancellation policy:

Once you have registered for a course provided by the LSM, you will be held responsible to participate or you will be unable to attend any further workshop provided by the LSM. Please give at least 48 hours working days´s notice to the LSM office before the course, should you be unable to attend, so that another student may take your place. If you fall ill on the day of the course, a doctor’s note is necessary.

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    Previous Methods Courses

  • Statistics R with Axel Strauß (16-20 September 2019)
  • Adobe Illustrator with Andreas Binder (18-19 July; 26-27 September 2019)
  • Bioinformatics (Linux, NGS data analysis and RNA-seq Data Analysis) with ECSEQ (2-5 April 2019)
  • GraphPad Prism with Statcon (10-12 April 2018)
  • Statistic R course, with Axel Strauß (19-23 Feb)
  • GMP course (2-6 and 9-13 Oct. 2017)
  • Statistical Literacy workshop, with Rick Scavetta (20-22 Sept. 2017)
  • Adobe Illustrator Workshop, with Dr. Andreas Binder (15 to 16 May 2017)
  • MatLab workshop, by Mathworks, with Trainer Dr. Yvonne Blum (3 to 5 May 2017)
  • Processing and Analysis of Scientific Images, Biovoxxel by Dr. Jan Brocher (16 to20 Jan. 2017)
  • Applied Statistics in Molecular biology by Dr. Axel Strauß (14 to 18 Nov. 2016)
  • Python Biobash Workshop (25 to 29 April 2016)
  • Adobe Illustrator (21/22 March 2016)
  • Comprehensive and Customized Image Processing and Analysis-BioVoxxel (2/3/4 December 2015)
  • Statistic R (12 to 16 October) extra day on 30 November.
  • Adobe Illustrator (14/15 January 2015)
  • Statistic R (October 29-5 November, 2014)
  • Applied Statistics for Molecular Biologists (November 14/15, 2013)
  • Adobe Illustrator (+Photoshop) course (July 29/30, 2013)
  • Adobe Illustrator (+Photoshop) course  (April, 18/19, 2013)

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