Event types: Workshops and courses
Machine Learning in R
6 - 7 November 2019
Heidelberg, GermanyMachine Learning in R https://www.denbi.de/training/675-machine-learning-in-r https://tess.elixir-europe.org/events/machine-learning-in-r Date Nov 6 - Nov 7 2019 Location EMBL Heidelberg Tutors and helpers - Dr. Malvika Sharan - Prof Bernd Bischl - Martin Binder - Giuseppe Casalicchio Affiliation: Ludwig-Maximilians-University Munich Course Information This two-day course, on the implementation of Machine Learning in R, using mlr package will be delivered as practical sessions on programming and data analysis. The main goal of mlr is to provide a unified interface for machine learning tasks as classification, regression, cluster analysis and survival analysis in R. Sessions will be driven by many practical exercises and case studies. Before this workshop, participants are expected to review the official material introducing the principle of Machine Learning (see the prerequisite). Course Content This 2-day course will cover hands-on sessions using `mlr` and other relevant packages. Daily schedule - 09:30-12:30 3h morning, 90 min Theory + 90 min Practical - 12:30-13:30 1h Lunchbreak - 13:30-16:30 3h afternoon, 90 min Theory + 90 min Practical - 16:30-17:00 Time for general questions Day 1 Introduction to the concepts and Practical with mlr - Performance Evaluation and Resampling (Metrics, CV, ROC) - Introduction to Boosting Day 2 Introduction to the concepts and Practical with mlr - Tuning and Nested Cross-Validation - Regularization and Feature Selection Prerequisite The course is aimed at advanced R programmers, preferably with some knowledge of statistics and data modeling (See prerequisite materials from Day-1, 2, & 4). In this course, our learners will learn more about machine learning and its application and implementation through the hands-on sessions and use cases. Optional: Discussion-Based Session On The Principle of Machine Learning Anna Kreshuk (EMBL Group Leader) will lead a one-day discussion-based session on 14 October 2019 to address your questions on the prerequisite materials on the principle of Machine Learning. This will also allow you to connect with other participants of this workshop informally, and discuss the materials in smaller groups. Please register for this workshop separately: https://bio-it.embl.de/events/machine-learning-discussion-workshop-2019/. Registration Please register on this page: https://bio-it.embl.de/events/machine-learning-in-r-2019/ Please note that the maximum capacity of this course is 40 participants and registration is required to secure a place. If you have any questions, please contact Malvika Sharan. In your registration, please mention your EMBL group name, or institute's name (e.g. DKFZ, Uni-HD) if you are registering as an external participant. Costs 60,00 EUR Keywords: Machine Learning, R 2019-11-06 09:00:00 UTC 2019-11-07 17:00:00 UTC de.NBI Heidelberg, Heidelberg, Germany Heidelberg Heidelberg Karlsruhe Germany    workshops_and_courses  
Data Carpentry Workshop 2020
28 - 30 January 2020
Metagenomic Bioinformatics Analysis
18 - 19 February 2020
Heidelberg, GermanyMetagenomic Bioinformatics Analysis https://www.denbi.de/training/773-metagenomic-bioinformatics-analysis https://tess.elixir-europe.org/events/metagenomic-bioinformatics-analysis Educators: Laura Carroll, Nicolai Karcher, Alessio Milanese, Jakob Wirbel, Georg Zeller (HD-HuB) Date: 18/02/2020 - 19/02/2020 09:00 - 17:00 Location: ATC Computer Training Lab, European Molecular Biology Laboratory (EMBL) Contents: Shotgun metagenomic sequencing approaches are being increasingly employed to characterize the human microbiome. Such complex metagenomics data sets are a rich source for generating functional hypotheses about the roles that gut microbiota play in human health and disease. In this bioinformatics course, participants will be exposed to computational and statistical approaches for the analysis of shotgun metagenomic data. Through a combination of theory-centric lectures and hands-on, practical exercises, the course will cover topics such as taxonomic profiling (i.e., determining “who’s there” in a microbial community), functional analysis (i.e., broadly assessing the functional and metabolic potential of a microbial community, and also mining for specific gene families such as toxins), and comparative metagenomics (i.e., identifying taxa or microbial functions associated with a disease of interest). Learning goals: - Pre-processing and quality control of Illumina metagenomic data - Taxonomic profiling - Exploratory analyses and visualization methods for metagenomic data - Functional metagenomic profiling (using both general purpose databases and targeted approaches) - Comparative analysis of metagenomic data Prerequisites: - Familiarity with the Linux command line interface (e.g., running programs from the command line, creating and moving between directories, accessing a remote host via SSH) - Basic knowledge of the R programming language (e.g., loading data into R, manipulating data frames, creating basic plots) Keywords: Metagenomics 2020-02-18 09:00:00 UTC 2020-02-19 17:00:00 UTC de.NBI Heidelberg, Heidelberg, Germany Heidelberg Heidelberg Karlsruhe Germany    workshops_and_courses  
Introduction to Regular Expressions
18 March 2020
Heidelberg, GermanyIntroduction to Regular Expressions https://www.denbi.de/training/774-introduction-to-regular-expressions https://tess.elixir-europe.org/events/introduction-to-regular-expressions Educators: Supriya Khedkar, Toby Hodges (HD-HuB) Date: 18/03/2020 09:30 - 16:00 Location: EMBL Heidelberg; Room 202 Contents: Do you often work with lots of data files on the computer, are you often trying to spot particular files or lines of text in them that are important for you? If so, then using regular expressions could save you a lot of time and frustration! Regular expressions (regex/REs) are a language designed to describe patterns of characters that you want to match in a body of text. For example, if you want to extract every Ensembl Gene ID in a GFF file, find tandem repeats in a large set of sequences, or extract every email address in a large document, regular expressions are the perfect tool. Regular expressions are incorporated into a wide range of software and programming languages, and the workshop will include examples of their use on the UNIX command line and in R and Python. Learning goals: This workshop will provide an introduction to REs and cover some of the simple but powerful ways that these can be used to find patterns in large volumes of text data. The workshop will be interactive and driven by examples to demonstrate how you might use regular expressions in your work. Prerequisites: Participants are required to bring their own laptop to the workshop, with a text editor suitable for programming (e.g. Atom, Sublime Text, VSCode, Notepad++) installed. Keywords: UNIX command line, R, Python Tools: UNIX command line, R, Python 2020-03-18 09:00:00 UTC 2020-03-18 17:00:00 UTC de.NBI Heidelberg, Heidelberg, Germany Heidelberg Heidelberg Karlsruhe Germany    workshops_and_courses  
Computing Skills for Reproducible Research: Software Carpentry Course 2020
19 - 23 October 2020Computing Skills for Reproducible Research: Software Carpentry Course 2020 https://www.denbi.de/training/789-software-carpentry-course-2020 https://tess.elixir-europe.org/events/computing-skills-for-reproducible-research-software-carpentry-course-2020 Educators: Renato Alves (HD-HuB) Date: 19-10-2020 - 23-10-2020 09:00-18:00 Location: Online Contents: Computation is an integral part of today's research as data has grown too large or too complex to be analysed by hand. An ever-growing fraction of science is performed computationally and many wet-lab biologists spend part of their time on the computer. Many scientists struggle with this aspect of research as they have not been properly trained in the necessary set of skills. The result is that too much time is spent using inefficient tools when progress could be faster. This course provides training in several key tools, with a focus on good development practices that encourage efficient and reproducible research computing. Topics covered include: Introduction to Python scripting Introduction to the Unix shell and usage of cluster resources Version control with Git and Github Analysis pipeline management Scientific Python & working with biological data Literate programming with Jupyter notebooks Learning goals: This course aims to teach software writing skills and best practices to researchers in biology who wish to analyse data, and to introduce a toolset that can help them in their work. The goal is to enable them to be more productive and to make their science better and more reproducible. Prerequisites: This is a course for researchers in the life sciences who are using computers for their analyses, even if not full time. The target student will be familiar with some command line/programmatic computer usage, will want to become more confident using these tools efficiently and reproducibly. A target student will have written a for loop in some language before, but will not know what git is (or at least not be very comfortable using git). Keywords: Programming; Command Line; Version Control; Bioinformatics; Data Analysis; Cluster Computing Tools: Python; Bash; Unix/Linux; Git; GitHub; SnakeMake; Biopython; Pandas; Numpy; SciPy; Matplotlib 2020-10-19 09:00:00 UTC 2020-10-23 17:00:00 UTC de.NBI Heidelberg, Heidelberg, Germany Heidelberg Heidelberg Karlsruhe Germany    workshops_and_courses  
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