R Schulungen

R Schulungen

R Programming Language, R Software Environment for statistical computing and graphics courses

Erfahrungsberichte

Introduction to R

Hands on examples were the most helpful.

Sean Kaukas - NGAM Advisors, L.P.

Forecasting with R

his knowlede and practical exemples

Irina Tulgara - British American Shared Services Europe BAT GBS Finance, WER/Centre/EEMEA

Neural Network in R

We gained some knowledge about NN in general, and what was the most interesting for me were the new types of NN that are popular nowadays.

Tea Poklepovic - Faculty of Economics and Business Zagreb

Data and Analytics - from the ground up

The way the trainer made complex subjects easy to understand.

Adam Drewry - Digital Jersey

Data and Analytics - from the ground up

learning how to use excel properly

Torin Mitchell - Digital Jersey

Data and Analytics - from the ground up

I enjoyed the Excel sheets provided having the exercises with examples. This meant that if Kamil was held up helping other people, I could crack on with the next parts.

Luke Pontin - Digital Jersey

A practical introduction to Data Analysis and Big Data

Willingness to share more

Balaram Chandra Paul - MOL Information Technology Asia Limited

Data and Analytics - from the ground up

Detailed and comprehensive instruction given by experienced and clearly knowledgeable expert on the subject.

Justin Roche - Digital Jersey

Advanced R

The flexible and friendly style. Learning exactly what was useful and relevant for me

Jenny Tickner - Nestlé

Data Mining with R

very tailored to needs

Yashan Wang - MoneyGram International

A practical introduction to Data Analysis and Big Data

presentation of technologies

Continental AG / Abteilung: CF IT Finance

Data Mining & Machine Learning with R

The trainer was so knowledgeable and included areas I was interested in

Mohamed Salama - Edmonton Police Service

Data and Analytics - from the ground up

First session. Very intensive and quick.

Digital Jersey

Forecasting with R

Overview and understanding how big the topic is

British American Shared Services Europe BAT GBS Finance, WER/Centre/EEMEA

Introduction to R

Working with 1:1 with Gunnar.

Bryant Ives - EY

Forecasting with R

A lot of knowldege - theoretical and practical

Anna Alechno - British American Shared Services Europe BAT GBS Finance, WER/Centre/EEMEA

Data and Analytics - from the ground up

Kamil is very knowledgeable and nice person, I have learned from him a lot.

Aleksandra Szubert - Digital Jersey

A practical introduction to Data Analysis and Big Data

Overall the Content was good.

Sameer Rohadia - Continental AG / Abteilung: CF IT Finance

Data and Analytics - from the ground up

The patience of Kamil.

Laszlo Maros - Digital Jersey

Prognosen mit R

Die freien Übungen.

Sabine Stammberger - HSH Nordbank AG

Predictive Modelling with R

He was very informative and helpful.

Pratheep Ravy - UPC Schweiz GmbH

Prognosen mit R

Auf alle Themenwünsche eingegangen und viel Zeit für die Beantwortung genommen.

HSH Nordbank AG

Neural Network in R

new insights in deep machine learning

Josip Arneric - Faculty of Economics and Business Zagreb

A practical introduction to Data Analysis and Big Data

It covered a broad range of information.

Continental AG / Abteilung: CF IT Finance

Neural Network in R

Graphs in R :)))

- Faculty of Economics and Business Zagreb

Data and Analytics - from the ground up

real life practical examples

Wioleta (Vicky) Celinska-Drozd - Digital Jersey

R Schulungsübersicht

Code Name Dauer Übersicht
webappsr Building Web Applications in R with Shiny 7 hours Description:  This is a course designed to teach R users how to create web apps without needing to learn cross-browser HTML, Javascript, and CSS. Objective: Covers the basics of how Shiny apps work. Covers all commonly used input/output/rendering/paneling functions from the Shiny library.
rforfinance R Programming for Finance 28 hours R is a popular programming language in the financial industry. It is used in financial applications ranging from core trading programs to risk management systems. In this instructor-led, live training, participants will learn how to use R to develop practical applications for solving a number of specific finance related problems. By the end of this training, participants will be able to: Understand the fundamentals of the R programming language Select and utilize R packages and techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.) Build applications that solve problems related to asset allocation, risk analysis, investment performance and more Troubleshoot, integrate deploy and optimize an R application Audience Developers Analysts Quants Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Note This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.
rlang R 21 hours 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.
predmodr Predictive Modelling with R 14 hours 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.
dmmlr Data Mining & Machine Learning with R 14 hours 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.
rprogda R Programming for Data Analysis 14 hours This course is part of the Data Scientist skill set (Domain: Data and Technology)
mrkfct Marktprognose 14 hours Audience 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. Description 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 ...)
bigddbsysfun Big Data & Database Systems Fundamentals 14 hours The course is part of the Data Scientist skill set (Domain: Data and Technology).
intror Introduction to R with Time Series Analysis 21 hours 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.
mrkanar Marketinganalytik mit R 21 hours Audience: 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. Trainer:   The Instructor has gained 19 years experience in customer insights and customer relationship management after originally graduating in experimental particle physics and working at the CERN laboratory. He has worked with large corporations across Europe and North America to transform the way they look at their customers and derive value from data, and has held interim management roles at leading Dutch and Irish mobile phone operators building their Insights and Customer Base Management teams.   He is one of the founders of The PCA Group, which helps large corporations in Europe and South America transform their approach to marketing, and of CYBAEA, which provides analytics-as-a-service across the globe with a strong focus on commercial results.   His teaching style focuses on practical example and emphasizes results over theoretical sophistication: his courses are for practitioners who need to deliver value to their organizations and while he covers just enough theory to make sure his students are on a firm footing his teaching is not geared to more theoretical students. Expect much hands-on work and very few formula.
advr Advanced R 7 hours This course covers advanced topics in R programming.
rneuralnet Training Neural Network in R 14 hours This course is an introduction to applying neural networks in real world problems using R-project software.
datascience Data Science Training 21 hours Data Science Training Aim: Obtaining the required knowledge for application of Data Science methods and also getting consultancy for establishing a Data Science team in an insurance company
67795 Numerical Methods 14 hours This course is for data scientists and statisticians that have some familiarity with numerical methods and have at least one programming language from R, Python, Octave, and some C++ options. The emphasis of this course is on the practical aspects of data/model preparation, execution, post hoc analysis and visualization. The purpose of this course is to give a practical introduction in numerical methods to participants interested in applying the methods at work. Sector specific examples are used to make the training relevant to the audience.
dsbda Data Science for Big Data Analytics 35 hours Big data is data sets that are so voluminous and complex that traditional data processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy.
rprogadv Fortgeschrittene "R"-Programmierung 7 hours Dieser Kurs ist ausgelegt für Data Scientists and Statistiker die breits Grundkenntnisse in "R & C++ coding skills und R-Code haben und fortgeschrittene "R-coding-skills" benötigen. Es handelt sich um einen praxisorientierten Fortgeschrittenen-Kurs in der Programmiersprache "R" für alle diejenigen, die die Methoden für die Arbeit benötigen.  Bereichsspezifische Beispiele erhöhen die Relevanz der Schulung für die Teilnehmer
datamodeling Pattern Recognition 35 hours This course provides an introduction into the field of pattern recognition and machine learning. It touches on practical applications in statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. The course is interactive and includes plenty of hands-on exercises, instructor feedback, and testing of knowledge and skills acquired. Audience     Data analysts     PhD students, researchers and practitioners  
dataminr Data Mining with R 14 hours 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.
kdd Knowledge Discover in Databases (KDD) 21 hours Knowledge discovery in databases (KDD) is the process of discovering useful knowledge from a collection of data. Real-life applications for this data mining technique include marketing, fraud detection, telecommunication and manufacturing. In this course, we introduce the processes involved in KDD and carry out a series of exercises to practice the implementation of those processes. Audience     Data analysts or anyone interested in learning how to interpret data to solve problems Format of the course     After a theoretical discussion of KDD, the instructor will present real-life cases which call for the application of KDD to solve a problem. Participants will prepare, select and cleanse sample data sets and use their prior knowledge about the data to propose solutions based on the results of their observations.
bigdatar Programming with Big Data in R 21 hours
nlpwithr NLP: Natural Language Processing with R 21 hours 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 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. Audience     Linguists and programmers Format of the course     Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
MLFWR1 Machine Learning Fundamentals with R 14 hours The aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the R programming platform and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results. Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
BigData_ A practical introduction to Data Analysis and Big Data 35 hours Participants who complete this training will gain a practical, real-world understanding of Big Data and its related technologies, methodologies and tools. Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class. The course starts with an introduction to elemental concepts of Big Data, then progresses into the programming languages and methodologies used to perform Data Analysis. Finally, we discuss the tools and infrastructure that enable Big Data storage, Distributed Processing, and Scalability. Audience Developers / programmers IT consultants Format of the course Part lecture, part discussion, hands-on practice and implementation, occasional quizing to measure progress.
dataar Data Analytics With R 21 hours 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
tidyverse Introduction to Data Visualization with Tidyverse and R 7 hours The 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
rintrob Introductory R for Biologists 28 hours 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.
danagr Data and Analytics - from the ground up 42 hours 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.
rintro Einführung in R 21 hours Forecasters, statisticians, managers, analysts who want to use R software http://www.r-project.org/. It shows you how to use the software in available GUI's and command lines.
rdataana R für Datenanalyse und Forschung 7 hours Audience managers developers scientists students Format of the course on-line instruction and discussion OR face-to-face workshops
frcr Prognosen mit R 14 hours This course allows delegate to fully automate the process of forecasting with R

Kommende Kurse

CourseSchulungsdatumKurspreis (Fernkurs / Schulungsraum)
Training Neural Network in R - Frankfurt am MainDi, 2018-02-06 09:302080EUR / 2580EUR
Data Mining with R - HannoverDi, 2018-02-06 09:302060EUR / 2560EUR
Marketinganalytik mit R - DresdenMo, 2018-02-12 09:302750EUR / 3400EUR
R Schulung, R boot camp, R Abendkurse, R Wochenendkurse , R Seminare, R Training, R Privatkurs, R Lehrer , R Coaching,R Kurs

Spezialangebote

Course Ort Schulungsdatum Kurspreis (Fernkurs / Schulungsraum)
Fortgeschrittene "R"-Programmierung Hamburg Di, 2018-01-30 09:30 891EUR / 1241EUR
PHP Patterns and Refactoring München Mo, 2018-03-26 09:30 3812EUR / 4462EUR
Introduction to Machine Learning Nürnberg Mi, 2018-04-04 09:30 891EUR / 1241EUR
Drupal and Solr Stuttgart Do, 2018-05-17 09:30 2457EUR / 2957EUR
Data Mining with R Bremen Mi, 2018-06-20 09:30 1854EUR / 2354EUR
Linux LPI LPIC-1 Exam 101 Vorbereitung Köln Di, 2018-07-03 09:30 1872EUR / 2372EUR

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