Lectures related to Computational Modeling of Systems

Python Functions: Basics and Arguments

Covers the basics of writing functions in Python and working with function arguments.

Monitoring with Icinga2

Explores the monitoring of a new VM and the use of Icinga2 for critical alerts and incident management.

Numerical Methods: Differential Equations

Covers the application of numerical methods to solve differential equations using MATLAB.

Gitlab Agent for Kubernetes (`agentk`)

Covers the setup of a Gitlab agent for Kubernetes, focusing on installation, version control, and troubleshooting.

Snowpack Modeling: Physics and Applications

Explores the physics of snowpack modeling and its practical applications in vapor transport and hydrology simulations.

HTTPie: Command-line HTTP Client

Covers DevOps topics such as hosting, DNS, deploying OS, apps, SSL, and Httpie utility.

Modeling Prisoner's Dilemma: Naive vs. Optimal

Explores the modeling of the '100 prisoners' problem and compares naive and optimal approaches.

Data Science Visualization with Pandas

Covers data manipulation and exploration using Python with a focus on visualization techniques.

File Handling: Text and Bytes

Covers file handling, string operations, and character encodings in Python.

Algorithms in Computer Science: Search and Sort Techniques

Provides an overview of essential search and sort algorithms in computer science.

Finite Element Methodology

Explores finite element methodology, covering geometric modeling, technical data, physical behavior assumptions, and mesh convergence studies.

General Introduction to Data Science

Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.

Image Processing Techniques: Seam Carving and Pixel Manipulation

Discusses image processing techniques, focusing on seam carving and pixel manipulation in Python programming.

Python Programming: File Handling and Exceptions

Explores file handling and exceptions in Python programming, covering reading, writing, and error handling strategies.

Springs and Elastisticity

Covers simulation, modeling, acceleration profiles, natural frequencies, rigidity calculations, and anti-resonance solutions for multi-axes robots.

Data Wrangling with Hive: Managing Big Data Efficiently

Covers data wrangling techniques using Apache Hive for efficient big data management.

Programming for Engineers: MATLAB Integration and Differentiation

Explores MATLAB integration, differentiation, ODE solvers, and simulation techniques for dynamic systems.

FPGA Programming with Speedgoat: Real-Time Signal Processing

Focuses on implementing a square function generator using Speedgoat FPGA technology and real-time signal processing techniques.

R Programming: Conditions, Loops, Functions & Graphics

Covers conditions, loops, functions, and graphics in R programming with practical examples.

File Handling in C: Basics and Common Issues

Covers the basics of file handling in C, common issues, and standard functions.