Statistics Počítačové Kurzy

This instructor-led, live training in České republice (online or onsite) is aimed at data analysts and anyone who is interested to learn how to use and integrate Tableau, Python, R, and SQL for data visualization and analysis. By the end of this training, participants will be able to:

• Perform data analysis using Python, R, and SQL.
• Create insights through data visualization with Tableau.
• Make data-driven decisions for business operations.

This instructor-led, live training in České republice (online or onsite) is aimed at scientists who wish to learn and use the Design of Experiments (DoE) to understand the cause-and-effect relationship between multiple factors. By the end of this training, participants will be able to:

• Understand the advantages of designed experiments over other approaches.
• Understand the cause-and-effect relationships and interactions between factors.
• Learn the best practices and guidelines for conducting successful experimentation.

This instructor-led, live training in České republice (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.

R is a very popular, open source environment for statistical computing, data analytics and graphics. This course introduces R programming language to students.  It covers language fundamentals, libraries and advanced concepts.  Advanced data analytics and graphing with real world data. Audience Developers / data analytics Duration 3 days Format Lectures and Hands-on

Audience Analysts, researchers, scientists, graduates and students and anyone who is interested in learning how to facilitate statistical analysis in Microsoft Excel. Course Objectives 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.

Data analytics is a crucial tool in business today. We will focus throughout on developing skills for practical hands on data analysis. The aim is to help delegates to give evidence-based answers to questions:  What has happened?

• processing and analyzing data
• producing informative data visualizations

What will happen?

• forecasting future performance
• evaluating forecasts

What should happen?

• turning data into evidence-based business decisions
• optimizing processes

The course itself can be delivered either as a 6 day classroom course or remotely over a period of weeks if preferred. We can work with you to deliver the course to best suit your needs.

It is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data. This instructor-led, live course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements. By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance.

Format of the Course

• Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding

This 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.

Audience Financial or market analysts, managers, accountants Course Objectives Facilitate and automate all kinds of financial analysis with Microsoft Excel

R je populární programovací jazyk v finančním průmyslu. Používá se v finančních aplikacích od základních obchodních programů až po systémy řízení rizik. V tomto výcviku vedeném instruktorem se účastníci naučí, jak používat R k vývoji praktických aplikací pro řešení řady specifických problémů souvisejících s financí. Po ukončení tohoto tréninku budou účastníci schopni:

Pochopte základní principy programovacího jazyka R Vyberte a použijte R balíčky a techniky pro organizaci, vizualizace a analýzu finančních údajů z různých zdrojů (CSV, [0), databází, webu atd.) Vytvořte aplikace, které řeší problémy související s přidělováním aktiv, analýzou rizik, investiční výkonností a dalšími Řešení problémů, integrovaná implementace a optimalizace aplikace R

publikum

Vývojáři analytici množství

Formát kurzu

Částečná přednáška, částečná diskuse, cvičení a těžká praxe

Poznámka

Cílem tohoto školení je poskytnout řešení některých zásadních problémů, kterým čelí finanční profesionálové. Pokud však máte konkrétní téma, nástroj nebo techniku, kterou chcete doplnit nebo dále vypracovat, kontaktujte nás prosím, abyste to uspořádali.

R je programovací jazyk a softwarové prostředí pro statistické výpočty. Společně s R a Excel, uživatelé jsou schopni implementovat standardy R Tidyverse a silnější funkce R pro zlepšení analýzy dat v Excel. Tento instruktor vedený, živý trénink (online nebo on-site) je zaměřen na analytiky údajů, kteří chtějí programovat v R pro Excel. Po ukončení tohoto tréninku budou účastníci schopni:

Shromažďovat a pohybovat data mezi Excel a R. Použijte R Tidyverse a R funkce pro řešení analýzy dat v Excel. Aktualizujte své dovednosti v oblasti datových věd pomocí učení R.

Formát kurzu

Interaktivní přednáška a diskuse. Mnoho cvičení a praxe. Hands-on implementace v živém laboratoři prostředí.

Možnosti personalizace kurzu

Chcete-li požádat o přizpůsobené školení pro tento kurz, kontaktujte nás, abyste uspořádali.

This 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.

This course has been created for people who require general statistics skills. This course can be tailored to a specific area of expertise like market research, biology, manufacturing, public sector research, etc...

This training course covers advanced statistics. It explains most of the tools commonly used in research, analysis and forecasting. It provides short explanations of the theory behind the formulas. 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)

The course is aimed at anyone interested in statistical analysis. It provides familiarity with Minitab and will increase the effectiveness and efficiency of your data analysis and improve your knowledge of statistics.

This course aims to give researchers an understanding of the principles of statistical design and analysis and their relevance to research in a range of scientific disciplines. 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.

Goal: Learning to work with SPSS at the level of independence The addressees: Analysts, researchers, scientists, students and all those who want to acquire the ability to use SPSS package and learn popular data mining techniques.

Goal: Mastering the skill work independently with the program SPSS for advanced use, dialog boxes, and command language syntax for the selected analytical techniques. The addressees: 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

Audience: The course is intended for IT specialists looking for a solution to store and process large data sets in a distributed system environment Goal: Deep knowledge on Hadoop cluster administration.

This course has been created for decision makers whose primary goal is not to do the calculation and the analysis, but to understand them and be able to choose what kind of statistical methods are relevant in strategic planning of the organization. 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 training course is for people that would like to apply Machine Learning in practical applications. Audience 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.

R 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.

Objective: 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.

SPSS is software for editing and analyzing data.

R 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.

Tableau helps people see and understand data.

This course is intended for data engineers, decision makers and data analysts and will lead you to create very effective plots using R studio that appeal to decision makers and help them find out hidden information and take the right decisions  

The Wolfram System's integrated environment makes it an efficient tool for both analyzing and presenting data. This course covers aspects of the Wolfram Language relevant to analytics, including statistical computation, visualization, data import and export and automatic generation of reports.

Mathematica consists of 20 years of creating the most powerful specialized mathematical software engine in the world.    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 and symbolic 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

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