本地的，有指导的实时统计培训课程通过互动讨论和实践练习，展示如何将统计原理应用于解决现实世界问题。统计培训可作为“现场实时培训”或“远程实时培训”。现场实地培训可在当地客户现场进行中国或者在NobleProg公司的培训中心中国 。远程实时培训通过交互式远程桌面进行。 NobleProg您当地的培训提供商。

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## 客户评论

他的信息非常丰富，乐于助人。

Pratheep Ravy

课程: Predictive Modelling with R

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我真的很喜欢教练的帮助。

Urszula Kuza

课程: Tableau Advanced

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我在所有问题上得到答案..

Natalia Gladii

课程: Data Analytics With R

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培训后可以探索很多问题。

Klaudia Kłębek

课程: Data Mining z wykorzystaniem R

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培训适应性强，个性化，符合我们的需求。

Dominique Soulie

课程: Minitab for Statistical Data Analysis

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我喜欢练习，因为这是通过重复学习的唯一方法。

David Rushe

课程: Tableau Advanced

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培训师知识渊博，包括我感兴趣的领域。

Mohamed Salama

课程: Data Mining & Machine Learning with R

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非常适合需求。

Yashan Wang

课程: Data Mining with R

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我真的很喜欢与Gunner一起工作1：1。

Bryant Ives

课程: Introduction to R

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我喜欢做的练习。

Nour Assaf

课程: Data Mining and Analysis

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动手练习和培训师能够用简单的术语解释复杂的主题。

youssef chamoun

课程: Data Mining and Analysis

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所提供的信息很有意思，最好的部分是在我们从Durex获得数据并且处理我们熟悉的数据并执行操作以获得结果时。

Jessica Chaar

课程: Data Mining and Analysis

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我最喜欢教练提供真实的实例。

Simon Hahn

课程: Administrator Training for Apache Hadoop

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我真的很享受培训师的巨大能力。

Grzegorz Gorski

课程: Administrator Training for Apache Hadoop

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我真的很喜欢这些实践课程。

Jacek Pieczątka

课程: Administrator Training for Apache Hadoop

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我喜欢深度机器学习的新见解。

Josip Arneric

课程: Neural Network in R

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我们获得了一些关于NN的知识，对我来说最有趣的是现在流行的新型NN。

Tea Poklepovic

课程: Neural Network in R

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我最喜欢R :)））中的图表。

Faculty of Economics and Business Zagreb

课程: Neural Network in R

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开放，良好的氛围，与老师的合作。

PAA

课程: Mathematica - wprowadzenie, wizualizacja i prezentacja danych

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讲师的知识Bartos

Bartosz Stefańczyk

课程: Minitab dla Statystyków i Analityków

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我真的受益于培训师的灵活性。

Irina Ostapenko

课程: Statistics Level 2

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灵活友好的风格。准确学习什么对我有用和相关。

Jenny Tickner

课程: Advanced R

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我喜欢提供带有示例练习的Excel表格。这意味着，如果泰米尔语被阻止帮助其他人，我可以继续使用下一部分。

Luke Pontin

课程: Data and Analytics - from the ground up

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学习如何正确使用excel。

Torin Mitchell

课程: Data and Analytics - from the ground up

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培训师使复杂科目易于理解的方式。

Adam Drewry

课程: Data and Analytics - from the ground up

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由经验丰富，知识渊博的专家就此主题提供的详细而全面的指导。

Justin Roche

课程: Data and Analytics - from the ground up

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泰米尔人是一位知识渊博，善良的人，我从他身上学到了很多东西。

Aleksandra Szubert

课程: Data and Analytics - from the ground up

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我喜欢第一次会议。非常密集和快速。

Digital Jersey

课程: Data and Analytics - from the ground up

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我最喜欢泰米尔人的耐心。

Laszlo Maros

课程: Data and Analytics - from the ground up

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我真的受益于现实生活中的实际例子。

Wioleta (Vicky) Celinska-Drozd

课程: Data and Analytics - from the ground up

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回答了所有的主题请求并花了很多时间回答。

HSH Nordbank AG

课程: Prognosen mit R

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免费练习。

Sabine Stammberger

课程: Prognosen mit R

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很多知识 - 理论和实践。

Anna Alechno

课程: Forecasting with R

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我真的很喜欢他的知识和实际例子。

Irina Tulgara

课程: Forecasting with R

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概述和理解主题有多大。

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

课程: Forecasting with R

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与培训师良好的互动，知识的动态交流。

NIIT Limited

课程: Data Analytics With R

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动手实例最有帮助。

Sean Kaukas

课程: Introduction to R

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我很享受第二天我们做了很多规格R＆R的例子。

Vascutek Ltd

课程: Minitab for Statistical Data Analysis

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我真的很喜欢这些练习 - 使用Minicab。

Vascutek Ltd

课程: Minitab for Statistical Data Analysis

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迈克尔培训师对大数据和R的主题非常了解和熟练。他非常灵活，能够快速定制满足客户需求的培训。他也非常有能力在旅途中解决技术和主题问题。神奇而专业的训练！

Xiaoyuan Geng - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada

课程: Programming with Big Data in R

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我非常喜欢推出新包装。

Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada

课程: Programming with Big Data in R

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导师Michael Yan先生很好地与观众互动，指导很明确。导师还可以根据培训期间学生的要求添加更多信息。

Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada

课程: Programming with Big Data in R

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主题和节奏是完美的。

Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada

课程: Programming with Big Data in R

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R的良好概述和良好的主题范围。培训师很乐意回答所有问题。

Symphony EYC

课程: R

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我非常喜欢教练的知识。

Stephanie Seiermann

课程: R

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这是非常翔实和专业的举办。 Wojteks的知识水平非常先进，他基本上可以回答任何问题，他愿意努力使培训符合我的个人需求。

Sonja Steiner - BearingPoint GmbH

课程: R Programming for Data Analysis

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很多练习，我可以直接在我的工作中使用。

Alior Bank S.A.

课程: Sieci Neuronowe w R

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真实数据的例子。

Alior Bank S.A.

课程: Sieci Neuronowe w R

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神经网络，循环中的pROC。

Alior Bank S.A.

课程: Sieci Neuronowe w R

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这是非常亲力亲为的，我们花了一半的时间实际在Clouded / Hardtop做事，运行不同的命令，检查系统，等等。额外的材料（书籍，网站等）真的很感激，我们将不得不继续学习。安装非常有趣，而且非常方便，从头开始的集群设置非常好。

Ericsson

课程: Administrator Training for Apache Hadoop

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## 统计课程大纲

Financial or market analysts, managers, accountants

Course Objectives

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.

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.

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

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.

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

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.

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.

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.

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.

Audience

Developers / data analytics

Duration

3 days

Format

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.

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

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.

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 ...)

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.

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