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Certificates: Certificate "MATLAB and Simulink"
Statistics" certificate -
Examination: Practical project work with final presentations
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Teaching Times: Full-timeMonday to Friday from 8:30 a.m. to 3:35 p.m. (in weeks with public holidays from 8:30 a.m. to 5:10 p.m.)
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Language of Instruction: German
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Duration: 8 Weeks
Mathematical modeling with MATLAB and Simulink
MATLAB basics (approx. 2 days)
MATLAB user interface
Reading data from a file
Variables, arrays, operators, basic functions
Graphical representation of data
Customizing diagrams
Exporting graphics
Variables and commands (approx. 2 days)
Relational and logical operators
Sets, sets with 2D solids (polyshape)
Performing mathematical and statistical calculations with vectors
Graphics in statistics
Analysis and visualization (approx. 1 day)
Creating and modifying matrices
Mathematical operations with matrices
Graphical representation of matrix data
Matrix applications: Mappings, rotation, systems of linear equations, least square method
Artificial intelligence (AI) in the work process
Presentation of specific AI technologies
and possible applications in the professional environment
Data processing (approx. 1 day)
Data types: Structure arrays, cell arrays, string vs. char, categorical, datetime and much more.
Creating and organizing tabular data
Conditional data selection
Importing/exporting with Matlab: folder structures, .mat data, table data, continuous texts
MATLAB programming (approx. 3 days)
Control structures: loops, if-else, exceptions
Functions
Object-oriented programming
App design
Simulation in MATLAB (approx. 5 days)
Numerical integration and differentiation
Basics of simulation of ordinary differential equations, Matlab ODE and solver options
Simulation technology in Matlab: input parameters, data interpolation, simulation studies
Simulation control: event functions (zero crossing), output functions
Application examples, e.g. simulation of an electric motor, simulation of a rocket
Simulink (approx. 4 days)
Basics of Simulink: Diagrams, functions, signals and differential equations
Functions, subsystems and libraries
Import/export, lookup tables, control
Zero-crossing, automation of simulation tasks (Matlab access)
Application examples, e.g. simulation of an aircraft drive train
Project work (approx. 2 days)
To consolidate the content learned
Presentation of the project results
Statistics
Statistical basics (approx. 6 days)
Measurement theory basics (population and sample, sample types, measurement and scale levels)
Univariate descriptive statistics (frequency distributions, central measures, measures of dispersion, standard value, histograms, bar charts, pie charts, line charts and box plots)
Bivariate descriptive statistics (measures of correlation, correlation coefficients, crosstabs, scatter plots and grouped bar charts)
Basics of inductive inferential statistics (probability distribution, normal distribution, mean value distribution, significance test, Fisher's null hypothesis test, effect size, parameter estimation, confidence intervals, error bar charts, power analyses and determining the optimum sample size)
Artificial intelligence (AI) in the work process
Presentation of specific AI technologies
and possible applications in the professional environment
Methods for comparing two groups (approx. 5 days)
z- and t-test for a sample (deviation from a specified value)
t-test for the mean difference between two independent/connected samples
Testing the effectiveness of actions, measures, interventions and other changes with t-tests (pretest-posttest designs with two groups)
Supporting significance tests (Anderson-Darling test, Ryan-Joiner test, Levene test, Bonnet test, significance test for correlations)
Nonparametric methods (Wilcoxon test, sign test, Mann-Whitney test)
Contingency analyses (binomial test, Fisher's exact test, chi-square test, cross-tabulations with measures of association)
Methods for comparing the means of several groups (approx. 5 days)
One- and two-factorial analysis of variance (simple and balanced ANOVA)
Multi-factorial analysis of variance (general linear model)
Fixed, random, crossed and nested factors
Multiple comparison methods (Tukey-HSD, Dunnett, Hsu-MCB, Games-Howell)
Interaction analysis (analysis of interaction effects)
Selectivity and power analysis for variance analyses
Introduction to Design of Experiments (DoE) (approx. 1 day)
Full and partial factorial experimental designs
Project work (approx. 3 days)
To consolidate the content learned
Presentation of the project results
Changes are possible. The course content is updated regularly.
After this course, you will have the necessary specialist knowledge and know the specific terminology for mathematical modeling with MATLAB and Simulink. You will have mastered the MATLAB software tools and the MATLAB programming language. You are also familiar with the modeling of numerical systems using Simulink software.
You will also understand the basics of statistics, be able to process and evaluate data and present, explain and interpret statistical data analyses and results using graphics.
The course is aimed at students of mathematics, science and engineering.
You will learn standard mathematical programs for engineering and science with MATLAB and Simulink. Specialists with knowledge of data simulation are in demand in numerous industrial fields and can be employed, for example, in weather and climate research, energy consumption modeling, the development of control algorithms for aircraft or function development in the automotive sector.
Your meaningful certificate provides a detailed insight into the qualifications you have acquired and improves your career prospects.
Didactic concept
Your lecturers are highly qualified both professionally and didactically and will teach you from the first to the last day (no self-study system).
You will learn in effective small groups. The courses usually consist of 6 to 25 participants. The general lessons are supplemented by numerous practical exercises in all course modules. The practice phase is an important part of the course, as it is during this time that you process what you have just learned and gain confidence and routine in its application. The final section of the course involves a project, a case study or a final exam.
Virtual classroom alfaview®
Lessons take place using modern alfaview® video technology - either from the comfort of your own home or at our premises at Bildungszentrum. The entire course can see each other face-to-face via alfaview®, communicate with each other in lip-sync voice quality and work on joint projects. Of course, you can also see and talk to your connected trainers live at any time and you will be taught by your lecturers in real time for the entire duration of the course. The lessons are not e-learning, but real live face-to-face lessons via video technology.
The courses at alfatraining are funded by Agentur für Arbeit and are certified in accordance with the AZAV approval regulation. When submitting a Bildungsgutscheinor Aktivierungs- und Vermittlungsgutschein, the entire course costs are usually covered by your funding body.
Funding is also possible via Europäischen Sozialfonds (ESF), Deutsche Rentenversicherung (DRV) or regional funding programs. As a regular soldier, you have the option of attending further training courses via Berufsförderungsdienst (BFD). Companies can also have their employees qualified via funding from Agentur für Arbeit (Qualifizierungschancengesetz).