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Publisher:Domein Applied Science

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MBO

July 2, 2025

Intro to python programming

Learning Outcomes for Python Programming Modules 1. Develop and Document Python Code in Jupyter Notebooks Learners will create, document, and execute Python code using Jupyter Notebooks, effectively utilizing Markdown for readable and well-structured analysis. 2. Understand and Apply Python Data Types and Operations Learners will identify and manipulate core Python data types, perform data operations, and utilize comprehensions for efficient data processing. 3. Implement Program Logic and Functions Learners will control program flow using conditionals and loops, encapsulate logic within functions, and handle errors using Python’s exception mechanism. 4. Read, Write, and Process Data Files Learners will read from and write to files, apply regular expressions for text processing, and leverage core library functions for common data tasks. 5. Apply Object-Oriented Programming and Prepare for Data Analysis Learners will design and use classes, including data classes, and set up a Python environment with (Ana)conda, preparing to work with data analysis libraries such as pandas. Consists of 18 lessons (5EC).

Website

Michiel Noback

July 2, 2025

Introduction - Java

Learning outcomes: Demonstrate proficiency in creating, structuring, and documenting Java projects using IntelliJ, applying keyboard shortcuts and best practices for naming and commenting code. • Apply fundamental Java programming concepts including data types, arrays, operators, flow control, methods, constructors, packages, and imports to build well-structured applications. • Design and implement object-oriented solutions using classes, interfaces, inheritance, encapsulation, access modifiers, inner classes, and core API features such as collections, generics, and exception handling. • Employ advanced Java APIs and techniques such as functional programming, streams, multithreading, concurrency, file I/O, regular expressions, annotations, and unit testing with JUnit 5. • Build and deploy web applications using Spring Boot, implementing RESTful services, MVC patterns, dependency injection, Thymeleaf templating, session management, database integration, Ajax, and web security features.

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Michiel Noback

July 2, 2025

Bereiden van buffers en oplossingen

Studenten kunnen chemische evenwichtsreacties correct opstellen en de bijbehorende evenwichtsvergelijkingen formuleren. 2. Studenten kunnen berekeningen uitvoeren aan chemische evenwichten, inclusief het toepassen van de zuurconstante (Ka), baseconstante (Kb) en de waterconstante (Kw). 3. Studenten kunnen het principe van Le Chatelier toepassen om te voorspellen en verklaren hoe een evenwicht verschuift bij veranderingen in concentratie, druk of temperatuur. 4. Studenten kunnen de eigenschappen van zuren, basen, zuur-base paren, meerwaardige zuren en amfolieten uitleggen en relevante berekeningen maken met pKa- en pKb-waarden. 5. Studenten kunnen de werking en het belang van buffers uitleggen, bufferoplossingen berekenen en toepassen, en hun vaardigheden oefenen met diverse opgaven. Duur van het vak is 14 lessen (4EC)

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Jurre Hageman

July 2, 2025

Induction of heat shock mRNA in Caenorhabditis elegans by heat shock

Experiment to show the heat shock induction in C. elegans using qPCR. Duration: 2 days. Learning outcome: students will learn how to use the qPCR to quantify the differences in Heat shock proteins.

Document

Jurre Hageman

July 2, 2025

Data Analysis and Visualization using R

Course is in English Learning outcomes: Apply Core R Programming Skills Learners will be able to write and execute R scripts using basic and complex data types, utilize built-in functions, and implement flow control structures to automate data analysis tasks. 2. Import, Clean, and Manipulate Data Learners will demonstrate the ability to read various data file formats, tidy and transform dataframes using both traditional methods and modern packages such as tidyr and dplyr, and handle date-time and text data efficiently. 3. Visualize Data Effectively Learners will create and customize data visualizations using the ggplot2 package, including revisiting advanced plotting techniques and adding interactivity to graphical outputs. 4. Perform Exploratory Data Analysis (EDA) Learners will conduct EDA using R, applying appropriate statistical summaries and visualizations to uncover patterns, trends, and insights from datasets. 5. Utilize R Packages and Resources Independently Learners will identify, install, and apply relevant R packages to extend functionality, troubleshoot code, and solve data analysis problems, including working through exercises and interpreting provided solutions. Duration Consists of 18 lessons Study points: 5 EC

Website

Michiel Noback

July 2, 2025

Data Analysis and visualization BML

Learning Outcomes You can explain the fundamental concepts of data, including data types, data structures, and the importance of data quality, and you can apply these concepts in the context of both Excel and R. You can import data from various sources (such as CSV, TXT, Excel files) into both Excel and R, and you are able to select the appropriate methods and functions for different data formats and structures. You can clean and prepare data for analysis in both Excel and R by applying techniques for identifying and handling missing values, outliers, inconsistencies, and duplicates. You can apply and interpret various data analysis functions in both Excel and R, including determining minimum and maximum values, calculating percentiles, selecting specific data based on criteria, applying conditional formatting to visually identify patterns, and sorting data to gain insights. You can create effective data visualizations in both Excel and R (such as bar charts, line charts, pie charts, and box plots) to communicate patterns, trends, and relationships in data, and you can customize the visualizations for a clear and purpose-driven presentation. Duration: 18 lessons (5EC).

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Jurre Hageman

September 15, 2022

Kennisclip: Aantoonbaarheidsgrens

Een kennisclip over de aantoonbaarheidsgrens. Het doel is inzicht te krijgen in de betekenis van dit prestatiekenmerk. Lengte 10 min

Video

Author unknown

March 24, 2022

Kennisclip: Atmospheric pressure chemical ionization (APCI)

Een kennisclip over APCI in LCMS analyse. Dit is een onderdeel uit een analytische chemie module in het derde leerjaar. Lengte 8 min

Video

Author unknown

January 29, 2022

Kennisclip: Concentratie berekenen met een kalibratielijn

Het berekenen van de concentratie met een kalibratielijn. De berekening van de onzekerheid in de berekende concentratie. Kennisclip 17min

Video

Natasja Carol-Visser

January 27, 2022

Kennisclip: Werken met de 100% methode

Een kennisclip over het gebruik van de 100% bij chromatografie.

Video

Natasja Carol-Visser