Statistik Schulungen

Statistik Schulungen

Practical Applied Statistics courses

Erfahrungsberichte

Minitab for Statistical Data Analysis

the training was adaptable and personalised to our needs

Dominique Soulie - BAE Systems Surface Ships Ltd

Data and Analytics - from the ground up

The way the trainer made complex subjects easy to understand.

Adam Drewry - Digital Jersey

Data Mining and Analysis

I like the exercices done

Nour Assaf - Murex Services S.A.L (Offshore)

Data and Analytics - from the ground up

First session. Very intensive and quick.

Digital Jersey

Prognosen mit R

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

HSH Nordbank AG

A practical introduction to Data Analysis and Big Data

Willingness to share more

Balaram Chandra Paul - MOL Information Technology Asia Limited

Data Mining and Analysis

The information given was interesting and the best part was towards the end when we were provided with Data from Murex and worked on Data we are familiar with and perform operations to get results.

Jessica Chaar - Murex Services S.A.L (Offshore)

Statistics Level 2

Flexibility of the trainer

Irina Ostapenko - Dr. Volker Türck Ingenieurbüro

Administrator Training for Apache Hadoop

Many hands-on sessions.

Jacek Pieczątka - OPITZ CONSULTING Deutschland GmbH

Data and Analytics - from the ground up

learning how to use excel properly

Torin Mitchell - Digital Jersey

Forecasting with R

Overview and understanding how big the topic is

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

Neural Network in R

new insights in deep machine learning

Josip Arneric - Faculty of Economics and Business Zagreb

Data Mining & Machine Learning with R

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

Mohamed Salama - Edmonton Police Service

Advanced R

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

Jenny Tickner - Nestlé

Applied Machine Learning

ref material to use later was very good

PAUL BEALES - Seagate Technology

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

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

real life practical examples

Wioleta (Vicky) Celinska-Drozd - Digital Jersey

Minitab for Statistical Data Analysis

2nd day we done lots of examples of gauge R&R & Criticality assessments

Vascutek Ltd

Data Mining and Analysis

The hands on exercise and the trainer capacity to explain complex topics in simple terms

youssef chamoun - Murex Services S.A.L (Offshore)

Minitab for Statistical Data Analysis

exercises - use of Minitab

Vascutek Ltd

Forecasting with R

his knowlede and practical exemples

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

Administrator Training for Apache Hadoop

Trainer give reallive Examples

Simon Hahn - OPITZ CONSULTING Deutschland GmbH

A practical introduction to Data Analysis and Big Data

It covered a broad range of information.

Continental AG / Abteilung: CF IT Finance

Introduction to R

Hands on examples were the most helpful.

Sean Kaukas - NGAM Advisors, L.P.

Data Mining with R

very tailored to needs

Yashan Wang - MoneyGram International

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

Minitab for Statistical Data Analysis

The use of examples, though even these were demonstrated at some considerable speed.

Vascutek Ltd

A practical introduction to Data Analysis and Big Data

Overall the Content was good.

Sameer Rohadia - Continental AG / Abteilung: CF IT Finance

Tableau Advanced

exercises as it's the only way to learn, by repitition

David Rushe - PaddyPower Betfair

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

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

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

Minitab for Statistical Data Analysis

The practical exercises were extremely beneficial

Vascutek Ltd

Neural Network in R

Graphs in R :)))

- Faculty of Economics and Business Zagreb

A practical introduction to Data Analysis and Big Data

presentation of technologies

Continental AG / Abteilung: CF IT Finance

Administrator Training for Apache Hadoop

Big competences of Trainer

Grzegorz Gorski - OPITZ CONSULTING Deutschland GmbH

Predictive Modelling with R

He was very informative and helpful.

Pratheep Ravy - UPC Schweiz GmbH

Introduction to R

Working with 1:1 with Gunnar.

Bryant Ives - EY

Tableau Advanced

Trainer's helping.

Urszula Kuza - UBS Business Solutions Poland Sp. z o.o.

Statistik Schulungsübersicht

Code Name Dauer Übersicht
sixsigmayb Six Sigma Yellow Belt 21 hours Yellow Belt covers the basics of the Six Sigma Define Measure Analyse Improve Control (DMAIC) approach enabling delegates to take part and lead team based waste and defect reduction projects and initiatives. In addition emphasis is placed on applying the problem solving tools into daily roles. At the end of the course you will be equipped to look at your immediate team and role, determine what can be improved and create a business improvement project on a selected opportunity that is aligned to customer requirements. You will be able to analyse the process using visualization tools and identify the waste (non-value adding) components and work to eliminate these from the process. You will apply root cause analysis techniques to identify the underlying causes of defects in the process. The course uses simulations, case study exercises and work based projects to enable delegates to 'learn through doing'. Notes: This course has a minimum class size of 4. And if requested this course can be delivered in 2 days with some reductions to the course content and level of detail in some areas, notably Customer needs; Graphical analysis and Process handover.
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.
datavisR1 Introduction to Data Visualization with R 28 hours 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  
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
sixsigmabb Six Sigma Black Belt 84 hours Six Sigma is a data driven approach that tackles variation to improve the performance of products, services and processes, combining practical problem solving and the best scientific approaches found in experimentation and optimisation of systems. The approach has been widely and successfully applied in industry, notably by Motorola, AlliedSignal & General Electric. Black Belt is a qualification for improvement managers in a Six Sigma organisation. You will learn the tools and techniques to take an improvement project through the Define, Measure, Analyse, Improve and Control phases (DMAIC). These techniques include Process Mapping, Measurement System Evaluation, Regression Analysis, Design of Experiments, Statistical Tolerancing, Monte Carlo Simulation and Lean Thinking. The content of the course takes the participants through the DMAIC phases as well as introducing subjects such as Lean Thinking, Design for Six Sigma and discussing important leadership issues and experiences in deploying a Six Sigma programme. Week 1 Foundation: covers the fundamentals of the Lean Six Sigma Define Measure Analyse Improve Control (DMAIC) approach enabling participants to take part and lead waste and defect reduction projects and initiatives. Week 2 Practitioner: provides additional data analysis and lean tools for participants to lead well scoped process improvement projects related to their regular job function. Week 3 Expert: provides regression, design of experiment and data analysis techniques to enable participants to tackle complex problem solving projects that require understanding of the relationships between multiple variables. The trainer has 16 years experience with Six Sigma and as well as leading the deployment of Six Sigma at a number of businesses he has trained and coached over 300 Black Belts. Here are a few comments from previous participants: “Probably the most valuable course I will ever pass” “The content was very well delivered. The examples very relevant. Thank you” “The course was excellent and I am able to use part of it to coach my lean teams here” (Company supervisor who attended with KTP associate)
octaveda Octave for Data Analysis 14 hours Audience: This course is for data scientists and statisticians that have some familiarity statistical methods and would like to use the Octave programming language at work. The purpose of this course is to give a practical introduction in Octave programming to participants interested in using this programming language at work.
tbladv Tableau Advanced 14 hours Tableau helps people see and understand data.
scilab Scilab 14 hours 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
mtstatda Minitab für statistische Datenanalyse 14 hours 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.
surveyrste Survey Research, Sampling Techniques & Estimation 14 hours
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.
sixsigmabbfast Six Sigma Black Belt - Fast Track 35 hours Six Sigma is a data driven approach that tackles variation to improve the performance of products, services and processes, combining practical problem solving and the best scientific approaches found in experimentation and optimisation of systems. The approach has been widely and successfully applied in industry, notably by Motorola, AlliedSignal & General Electric. Black Belt is a qualification for improvement managers in a Six Sigma organisation. You will learn the tools and techniques to take an improvement project through the Define, Measure, Analyse, Improve and Control phases (DMAIC). These techniques include Process Mapping, Measurement System Evaluation, Regression Analysis, Design of Experiments, Statistical Tolerancing, Monte Carlo Simulation and Lean Thinking. The content of the course takes the participants through the DMAIC phases as well as introducing subjects such as Lean Thinking, Design for Six Sigma and discussing important leadership issues and experiences in deploying a Six Sigma programme. Week 1 Foundation: covers the fundamentals of the Lean Six Sigma Define Measure Analyse Improve Control (DMAIC) approach enabling participants to take part and lead waste and defect reduction projects and initiatives. Week 2 Practitioner: provides additional data analysis and lean tools for participants to lead well scoped process improvement projects related to their regular job function. Week 3 Expert: provides regression, design of experiment and data analysis techniques to enable participants to tackle complex problem solving projects that require understanding of the relationships between multiple variables. The trainer has 16 years experience with Six Sigma and as well as leading the deployment of Six Sigma at a number of businesses he has trained and coached over 300 Black Belts. Here are a few comments from previous participants: “Probably the most valuable course I will ever pass” “The content was very well delivered. The examples very relevant. Thank you” “The course was excellent and I am able to use part of it to coach my lean teams here” (Company supervisor who attended with KTP associate) This is the fast track program that paces up the original training dividing the training three blocks - each of almost 1.5 days duration. This training is for individuals who wants to grasp quick concepts. 
excelstatsda Excel für statistische Datenanalyse 14 hours 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.
datashrinkgov Data Shrinkage for Government 14 hours
spssanal Statistical Analysis using SPSS 21 hours SPSS is software for editing and analyzing data.
sixsigmagbfast Six Sigma Green Belt - Fast Track 28 hours Green Belts participate in and lead Lean and Six Sigma projects from within their regular job function. They can tackle projects as part of a cross functional team or projects scoped within their normal job. Each session of Green Belt training is separated by 3 or 4 weeks when the Green Belts apply their training to their improvement projects. We recommend supporting the Green Belts on their projects in between training sessions and holding stage gate reviews along with leadership and Lean Six Sigma Champions to ensure DMAIC methodology is being rigorously applied. Week 1 Foundation: covers the fundamentals of the Lean Six Sigma Define Measure Analyse Improve Control (DMAIC) approach enabling participants to take part and lead waste and defect reduction projects and initiatives. Week 2 Practitioner: provides additional data analysis and lean tools for participants to lead well scoped process improvement projects related to their regular job function.   This is the fast track program that paces up the original training dividing the training two blocks - each of 2 days duration. This training is for individuals who wants to grasp quick concepts. 
stats2 Statistik Level 2 28 hours This statistics course covers advanced statistics. It explains most of the tools commonly used in research, analysis, forecasting. It provides very short explanation of theory behind the formulas. This course does not related to any specific field of knowledge, but can be tailored if all the delegates have the same background and goals. Some basic computers tools are used during this course (notably Excel and OpenOffice)
advspsspas Statistik für Fortgeschrittene - Umgang mit SPSS Predictive Analytics SoftWare 28 hours 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
StaEcoMod Statistical and Econometric Modelling 21 hours
tableau1 Data analysis with Tableau 14 hours Tableau helps people see and understand data.
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.
stats1 Statistik Level 1 14 hours 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...
xcelsius Xcelsius 14 hours   Description: In this Xcelsius Training course, students will use Xcelsius Present to create interactive visualizations for presenting complex data in a simple way, and to conduct analysis to make critical decisions. Students will also create complete dashboards that present business, project, and human resources information, all consolidated and presented in a user-friendly manner. Finally, students will publish dashboards into various file formats such as Adobe Flash, Microsoft Office PowerPoint, Adobe PDF, and also to the web. Objectives: Upon successful completion of this course, students will be able to: Explore the Xcelsius workspace and an already created dashboard. Create simple visualizations. Conduct data analysis using Xcelsius components that give dynamic functionality to the specified data. Create a Project Management dashboard. Create a dashboard to consolidate and present the Human Resources information of an organization. Finalize dashboards and export them to different file formats. Audience: This course is designed for professionals who conduct data analysis and need to present robust and timely data in an interactive display.  
statsqa Statistical Quality Analysis 7 hours This course covers the fundamentals of statistical process control and how these quality tools can provide the necessary evidence to improve and control processes. Know when and where to use the various types of control charts available in Minitab for your own processes. And learn how to use capability analysis tools to evaluate your processes.
advr Advanced R 7 hours This course covers advanced topics in R programming.
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.
statsres Statistik für Forscher 35 hours 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, Statgraphs, 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.
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.
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
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
statsman Statistik für Manager 35 hours This course has been created for decision makers whose primary goal is not to do the calculation and the analysis, but to understand them. The course uses a lot of pictures, diagrams, computer simulations, anecdotes and sense of humour to explain concepts and pitfalls of statistics.
statdm Statistical Thinking for Decision Makers 7 hours 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.
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.
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.
sixsigmagb Six Sigma Green Belt 70 hours Green Belts participate in and lead Lean and Six Sigma projects from within their regular job function. They can tackle projects as part of a cross functional team or projects scoped within their normal job. Each session of Green Belt training is separated by 3 or 4 weeks when the Green Belts apply their training to their improvement projects. We recommend supporting the Green Belts on their projects in between training sessions and holding stage gate reviews along with leadership and Lean Six Sigma Champions to ensure DMAIC methodology is being rigorously applied. Week 1 Foundation: covers the fundamentals of the Lean Six Sigma Define Measure Analyse Improve Control (DMAIC) approach enabling participants to take part and lead waste and defect reduction projects and initiatives. Week 2 Practitioner: provides additional data analysis and lean tools for participants to lead well scoped process improvement projects related to their regular job function.
apacheh Administrator Training for Apache Hadoop 35 hours 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.
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.
Piwik Getting started with Piwik 21 hours Audience Web analysist Data analysists Market researchers Marketing and sales professionals System administrators Format of course     Part lecture, part discussion, heavy hands-on practice
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.
datama Data Mining and Analysis 28 hours 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.
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  
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 ...)
appliedml Angewandtes Maschinelles Lernen 14 hours Der Übungskurs ist für alle diejenigen gedacht, die "Machine Learning" in praktischen Applikationen anwenden möchten Teilnehmer Dieser Kurs ist für Data Scientists und Statistiker, die Grundkenntnisse in Statistik haben und wissen, wie man R programmiert. Der Schwerpunkt des Kurses liegt auf dem praktischen Aspekt von Daten/Modell-Vorbereitung, Execution, post hoc Analyse und Visualisierung. Das Ziel ist es, den Teilnehmern praktische Kenntnisse im Maschinellen Lernen  zu vermitteln.  Bereichsspezifische Beispiele erhöhen die Relevanz der Schulung für die Teilnehmer. 
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.
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.
mlintro Introduction to Machine Learning 7 hours This training course is for people that would like to apply basic Machine Learning techniques in practical applications. Audience Data scientists and statisticians that have some familiarity with machine learning and know how to program R. 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 a practical introduction 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.
tableauvra Visual Reporting and Analysis with Tableau 7 hours Tableau helps people see and understand data.
druid Druid: Build a fast, real-time data analysis system 21 hours Druid is an open-source, column-oriented, distributed data store written in Java. It was designed to quickly ingest massive quantities of event data and execute low-latency OLAP queries on that data. Druid is commonly used in business intelligence applications to analyze high volumes of real-time and historical data. It is also well suited for powering fast, interactive, analytic dashboards for end-users. Druid is used by companies such as Alibaba, Airbnb, Cisco, eBay, Netflix, Paypal, and Yahoo. In this course we explore some of the limitations of data warehouse solutions and discuss how Druid can compliment those technologies to form a flexible and scalable streaming analytics stack. We walk through many examples, offering participants the chance to implement and test Druid-based solutions in a lab environment. Audience     Application developers     Software engineers     Technical consultants     DevOps professionals     Architecture engineers Format of the course     Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
excelafd Analyse von Finanzdaten in Excel 14 hours Audience Financial or market analysts, managers, accountants Course Objectives Facilitate and automate all kinds of financial analysis with Microsoft Excel
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.
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.
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
pgmt Der Praktikerguide für mulitvariate Techniken 14 hours The introduction of the digital computer, and now the widespread availability of computer packages, has opened up a hitherto difficult area of statistics; multivariate analysis. Previously the formidable computing effort associated with these procedures presented a real barrier. That barrier has now disappeared and the analyst can therefore concentrate on an appreciation and an interpretation of the findings.
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
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.
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.
sspsspas Statistik mit SPSS Predictive Analytics SoftWare 14 hours 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.
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.
rprogda R Programming for Data Analysis 14 hours This course is part of the Data Scientist skill set (Domain: Data and Technology)
mlentre Machine Learning Concepts for Entrepreneurs and Managers 21 hours This training course is for people that would like to apply Machine Learning in practical applications for their team.  The training will not dive into technicalities and revolve around basic concepts and business/operational applications of the same. Target Audience Investors and AI entrepreneurs Managers and Engineers whose company is venturing into AI space Business Analysts & Investors
samr Statistische Analysen in der Marktforschung 28 hours Goal: Improving consumer behavior researcher workshop products and services Addressees  The researchers, market analysts, managers and employees of marketing departments, sales departments primarily pharmaceutical and FMCG, students of socio-economic and everyone interested in market research
bigdatar Programming with Big Data in R 21 hours
bigddbsysfun Big Data & Database Systems Fundamentals 14 hours The course is part of the Data Scientist skill set (Domain: Data and Technology).
kylin Apache Kylin: From classic OLAP to real-time data warehouse 14 hours Apache Kylin is an extreme, distributed analytics engine for big data. In this instructor-led live training, participants will learn how to use Apache Kylin to set up a real-time data warehouse. By the end of this training, participants will be able to: Consume real-time streaming data using Kylin Utilize Apache Kylin's powerful features, including snowflake schema support, a rich SQL interface, spark cubing and subsecond query latency Note We use the latest version of Kylin (as of this writing, Apache Kylin v2.0) Audience Big data engineers Big Data analysts Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
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)
Statistik Level 2 - BernDi, 2018-02-06 09:303890EUR / 4690EUR
Statistik für Forscher - ZürichMo, 2018-03-19 09:304540EUR / 5490EUR
Six Sigma Green Belt - Fast Track - BaselMo, 2018-05-21 09:3012740EUR / 13540EUR

Other regions

Statistik Schulung, Statistik boot camp, Statistik Abendkurse, Statistik Wochenendkurse , Statistik Kurs, Statistik Privatkurs, Statistik Training, Statistik Coaching, Statistik Seminar, Statistik Seminare

Spezialangebote

Course Ort Schulungsdatum Kurspreis (Fernkurs / Schulungsraum)
Puppet Advanced Bern Di, 2018-04-10 09:30 3132EUR / 3782EUR
Einführung von Business-Regeln mit SBVR Bern Di, 2018-05-08 09:30 1809EUR / 2309EUR
Release-Management and Bereitstellung mit Distributed Version Control System Bern Mo, 2018-06-04 09:30 891EUR / 1241EUR
Data Mining with R Bern Do, 2018-06-21 09:30 1854EUR / 2354EUR
Marktprognose Zürich Mi, 2018-06-27 09:30 1872EUR / 2372EUR

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