Scilab Training Course
Scilab is a well-developed, free, and open-source high-level language for scientific data manipulation. Used for statistics, graphics and animation, simulation, signal processing, physics, optimization, and more, its central data structure is the matrix, simplifying many types of problems compared to alternatives such as FORTRAN and C derivatives. It is compatible with languages such as C, Java, and Python, making it suitable as for use as a supplement to existing systems.
In this instructor-led training, participants will learn the advantages of Scilab compared to alternatives like Matlab, the basics of the Scilab syntax as well as some advanced functions, and interface with other widely used languages, depending on demand. The course will conclude with a brief project focusing on image processing.
By the end of this training, participants will have a grasp of the basic functions and some advanced functions of Scilab, and have the resources to continue expanding their knowledge.
Audience
- Data scientists and engineers, especially with interest in image processing and facial recognition
Format of the course
- Part lecture, part discussion, exercises and intensive hands-on practice, with a final project
Course Outline
Introduction
- Comparison with other languages
Getting started
Matrix operations
Multidimensional data
Plotting and exporting graphics
Creating an ATOMS toolbox
Interface with C, Java, and others
Final project: Image analysis
Closing remarks
- Overview of useful libraries and extensions
Requirements
- Applied mathematics up to linear algebra
- Helpful to know the basics of Matlab
Need help picking the right course?
Scilab Training Course - Enquiry
Testimonials (5)
The variation with exercise and showing.
Ida Sjoberg - Swedish National Debt Office
Course - Econometrics: Eviews and Risk Simulator
Many examples and exercises related to the topic of the training.
Tomasz - Ministerstwo Zdrowia
Course - Advanced R Programming
the trainer had patience, and was eager to make sure we all understood the topics, the classes were fun to attend
Mamonyane Taoana - Road Safety Department
Course - Statistical Analysis using SPSS
The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.
Rhian Hughes - Public Health Wales NHS Trust
Course - Introduction to Data Visualization with Tidyverse and R
I really enjoyed the knowledge of the trainer.
Stephanie Seiermann
Course - R
Upcoming Courses
Related Courses
Programming with Big Data in R
21 HoursBig Data is a term that refers to solutions destined for storing and processing large data sets. Developed by Google initially, these Big Data solutions have evolved and inspired other similar projects, many of which are available as open-source. R is a popular programming language in the financial industry.
Data Mining with R
14 HoursR is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.
Econometrics: Eviews and Risk Simulator
21 HoursThis instructor-led, live training in Kuwait (online or onsite) is aimed at anyone who wishes to learn and master the fundamentals of econometric analysis and modeling.
By the end of this training, participants will be able to:
- Learn and understand the fundamentals of econometrics.
- Utilize Eviews and risk simulators.
Fiji: Image Processing for Biotechnology and Toxicology
14 HoursThis instructor-led, live training in Kuwait (online or onsite) is aimed at beginner-level to intermediate-level researchers and laboratory professionals who wish to process and analyze images related to histological tissues, blood cells, algae, and other biological samples.
By the end of this training, participants will be able to:
- Navigate the Fiji interface and utilize ImageJ’s core functions.
- Preprocess and enhance scientific images for better analysis.
- Analyze images quantitatively, including cell counting and area measurement.
- Automate repetitive tasks using macros and plugins.
- Customize workflows for specific image analysis needs in biological research.
Forecasting with R
14 HoursThis instructor-led, live training in Kuwait (online or onsite) is aimed at intermediate-level data analysts and business professionals who wish to perform time series forecasting and automate data analysis workflows using R.
By the end of this training, participants will be able to:
- Understand the fundamentals of forecasting techniques in R.
- Apply exponential smoothing and ARIMA models for time series analysis.
- Utilize the ‘forecast’ package to generate accurate forecasting models.
- Automate forecasting workflows for business and research applications.
HR Analytics for Public Organisations
14 HoursThis instructor-led, live training (online or onsite) is aimed at HR professionals who wish to use analytical methods improve organisational performance. This course covers qualitative as well as quantitative, empirical and statistical approaches.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Marketing Analytics using R
21 HoursAudience
Business owners (marketing managers, product managers, customer base managers) and their teams; customer insights professionals.
Overview
The course follows the customer life cycle from acquiring new customers, managing the existing customers for profitability, retaining good customers, and finally understanding which customers are leaving us and why. We will be working with real (if anonymous) data from a variety of industries including telecommunications, insurance, media, and high tech.
Format
Instructor-led training over the course of five half-day sessions with in-class exercises as well as homework. It can be delivered as a classroom or distance (online) course.
R for Data Analysis and Research
7 HoursAudience
- managers
- developers
- scientists
- students
Format of the course
on-line instruction and discussion OR face-to-face workshops
Introduction to R
21 HoursR is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.
This course covers the manipulation of objects in R including reading data, accessing R packages, writing R functions, and making informative graphs. It includes analyzing data using common statistical models. The course teaches how to use the R software (https://www.r-project.org) both on a command line and in a graphical user interface (GUI).
R
21 HoursR is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.
Neural Network in R
14 HoursThis course is an introduction to applying neural networks in real world problems using R-project software.
Advanced R Programming
7 HoursThis course is for data scientists and statisticians that already have basic R & C++ coding skills and R code and need advanced R coding skills.
The purpose is to give a practical advanced R programming course to participants interested in applying the methods at work.
Sector specific examples are used to make the training relevant to the audience
Statistical Analysis using SPSS
21 HoursThis instructor-led, live training in Kuwait (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to perform statistical analysis using SPSS to interpret data accurately, run complex statistical tests, and generate meaningful insights.
By the end of this training, participants will be able to:
- Navigate the SPSS interface and manage datasets efficiently.
- Perform descriptive and inferential statistical analyses.
- Conduct t-tests, ANOVA, MANOVA, regression, and correlation analyses.
- Apply non-parametric tests, principal component analysis, and factor analysis for advanced data interpretation.
Talent Acquisition Analytics
14 HoursThis instructor-led, live training (online or onsite) is aimed at HR professionals and recruitment specialists who wish to use analytical methods improve organisational performance. This course covers qualitative as well as quantitative, empirical and statistical approaches.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Introduction to Data Visualization with Tidyverse and R
7 HoursThe Tidyverse is a collection of versatile R packages for cleaning, processing, modeling, and visualizing data. Some of the packages included are: ggplot2, dplyr, tidyr, readr, purrr, and tibble.
In this instructor-led, live training, participants will learn how to manipulate and visualize data using the tools included in the Tidyverse.
By the end of this training, participants will be able to:
- Perform data analysis and create appealing visualizations
- Draw useful conclusions from various datasets of sample data
- Filter, sort and summarize data to answer exploratory questions
- Turn processed data into informative line plots, bar plots, histograms
- Import and filter data from diverse data sources, including Excel, CSV, and SPSS files
Audience
- Beginners to the R language
- Beginners to data analysis and data visualization
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice