Lokální instruktorem vedené Statistics školení České republice.
Trenér byl velmi dobrý. Prezentoval materiál opravdu přístupným způsobem.
Kurz: Introduction to Data Visualization with Tidyverse and R
Statistics Návrh Školení
Financial or market analysts, managers, accountants
Facilitate and automate all kinds of financial analysis with Microsoft Excel
Analysts, researchers, scientists, graduates and students and anyone who is interested in learning how to facilitate statistical analysis in Microsoft Excel.
This course will help improve your familiarity with Excel and statistics and as a result increase the effectiveness and efficiency of your work or research.
This course describes how to use the Analysis ToolPack in Microsoft Excel, statistical functions and how to perform basic statistical procedures. It will explain what Excel limitation are and how to overcome them.
This course does not relate to any specific field of knowledge, but can be tailored if all the delegates have the same background and goals.
Some basic computer tools are used during this course (notably Excel and OpenOffice)
It covers some probability and statistical methods, mainly through examples. This training contains around 30% of lectures, 70% of guided quizzes and labs.
In the case of closed course we can tailor the examples and materials to a specific branch (like psychology tests, public sector, biology, genetics, etc...)
In the case of public courses, mixed examples are used.
Though various software is used during this course (Microsoft Excel to SPSS, Statgraphics, etc...) its main focus is on understanding principles and processes guiding research, reasoning and conclusion.
This course can be delivered as a blended course i.e. with homework and assignments.
Learning to work with SPSS at the level of independence
Analysts, researchers, scientists, students and all those who want to acquire the ability to use SPSS package and learn popular data mining techniques.
Mastering the skill work independently with the program SPSS for advanced use, dialog boxes, and command language syntax for the selected analytical techniques.
Analysts, researchers, scientists, students and all those who want to acquire the ability to use SPSS package and advanced level and learn the selected statistical models. Training takes universal analysis problems and it is dedicated to a specific industry
The course is intended for IT specialists looking for a solution to store and process large data sets in a distributed system environment
Deep knowledge on Hadoop cluster administration.
For example, a prospect participant needs to make decision how many samples needs to be collected before they can make the decision whether the product is going to be launched or not.
If you need longer course which covers the very basics of statistical thinking have a look at 5 day "Statistics for Managers" training.
This course is for data scientists and statisticians that have some familiarity with statistics and know how to program R (or Python or other chosen language). The emphasis of this course is on the practical aspects of data/model preparation, execution, post hoc analysis and visualization.
The purpose is to give practical applications to Machine Learning to participants interested in applying the methods at work.
Sector specific examples are used to make the training relevant to the audience.
Delegates be able to analyse big data sets, extract patterns, choose the right variable impacting the results so that a new model is forecasted with predictive results.
Developers / data analytics
Lectures and Hands-on
Its versatility makes it useful not only for doing basic academic calculations but also completing complicated calculations, like programming or numerical data presentations.
Mathematica integrates software engines doing numerical andsymbolic computation, as well as graph analysis software, programming language, document formats and the possibility of publishing your work results.
Thanks to multiplicity of its functions it’s a priceless tool for mathematicians, physicists, biologists, chemists, financial analysts, sociologists and many more professions that deal with data.
Participants will gain skills to
- perform calculations efficiently
- understanding program commands
- creating text documents
- building charts and graphs
- data presentations
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.
- 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
By the end of this training, participants will be able to:
- Use Minitab for performing advanced statistical analysis.
- Apply Six Sigma methodology to specific projects.
- Gain knowledge on Six Sigma projects across industries.
This course has been created for analysts, forecasters wanting to introduce or improve forecasting which can be related to sale forecasting, economic forecasting, technology forecasting, supply chain management and demand or supply forecasting.
This course guides delegates through series of methodologies, frameworks and algorithms which are useful when choosing how to predict the future based on historical data.
It uses standard tools like Microsoft Excel or some Open Source programs (notably R project).
The principles covered in this course can be implemented by any software (e.g. SAS, SPSS, Statistica, MINITAB ...)
Business owners (marketing managers, product managers, customer base managers) and their teams; customer insights professionals.
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.
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.
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