로컬 및 강사 데이터 마이닝 교육 과정은 Handson 연습을 통해 데이터 마이닝의 기초, 인공 지능, 기계 학습, 통계 및 데이터베이스 시스템, 사용 및 응용 프로그램을 포함한 방법 소스를 보여줍니다 Data Mining 교육은 "현장 실습"또는 "원격 실습"으로 제공됩니다 현장 실습은 고객 구내에서 현지에서 실시 할 수 있습니다 대한민국 또는 NobleProg 기업 교육 센터에서 대한민국 원격 라이브 교육은 대화 형 원격 데스크톱을 통해 수행됩니다 NobleProg 지역 교육 제공자.
Machine Translated
회원 평가
물질의 범위 Maciej
Maciej Jonczyk
Course: From Data to Decision with Big Data and Predictive Analytics
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ML 분야의 체계화 된 지식 - Orange Pol
Orange Polska
Course: From Data to Decision with Big Data and Predictive Analytics
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교육 후에 탐구 할 수있는 많은 문제 Klaudia Kłębek
Klaudia Kłębek
Course: Data Mining z wykorzystaniem R
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트레이너는 매우 지식이 많았고 내가 관심이있는 영역을 포함했습니다.
Mohamed Salama
Course: Data Mining & Machine Learning with R
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필요에 매우 맞춘
Yashan Wang
Course: Data Mining with R
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나는 운동을 좋아한다.
Nour Assaf
Course: Data Mining and Analysis
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복잡한 주제를 간단한 용어로 설명 할 수있는 운동 및 트레이너 역량
youssef chamoun
Course: Data Mining and Analysis
Machine Translated
주어진 정보는 흥미로 우며, 가장 중요한 부분은 우리가 Murex의 데이터를 제공 받았고 우리가 익숙한 데이터를 작업하고 결과를 얻기 위해 작업을 수행 할 때였습니다
Jessica Chaar
Course: Data Mining and Analysis
Machine Translated
정보가 재미 있다고 생각했습니다
Allison May
Course: Data Visualization
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Jeff는 교육 데이터에 적용 할 수있는 데이터와 예제를 사용했음을 정말로 감사드립니다. 그는 그것을 흥미롭고 대화식으로 만들었습니다
Carol Wells Bazzichi
Course: Data Visualization
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모든 차트 유형 및 해당 차트 유형에 대해 학습합니다. decluttering의 가치를 배우십시오. 시간 데이터를 표시하는 방법에 대해 학습합니다.
Susan Williams
Course: Data Visualization
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트레이너가 열렬했다
Diane Lucas
Course: Data Visualization
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내용 / 강사
Craig Roberson
Course: Data Visualization
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나는 손수 배우는 사람이고 이것은 그가 많이 한 일이었습니다.
Lisa Comfort
Course: Data Visualization
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예제
Peter Coleman
Course: Data Visualization
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예제
Peter Coleman
Course: Data Visualization
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좋은 실제 사례, 기존 보고서의 검토
Ronald Parrish
Course: Data Visualization
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실습 예제, 실무 경험 공유
澳新银行
Course: Data Vault: Building a Scalable Data Warehouse
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큐브 및 DV Al
Alan Xie
Course: Data Vault: Building a Scalable Data Warehouse
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데이터웨어 하우스에 대한 교사의 지식은 포괄적이며 그는 그것을 칭찬합니다!
澳新银行
Course: Data Vault: Building a Scalable Data Warehouse
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교사는 자세하게 설명하고 분위기를 토론했다. 澳新银行
澳新银行
Course: Data Vault: Building a Scalable Data Warehouse
Machine Translated
예제 및 교육 자료가 충분하고 자신이하는 일을 쉽게 이해할 수있었습니다
Teboho Makenete
Course: Data Science for Big Data Analytics
Machine Translated
리처드의 훈련 스타일은 흥미로웠다. 사용 된 실제 사례는 개념을 집으로 몰아가는 데 도움이되었다.
Jamie Martin-Royle - NBrown Group
Course: From Data to Decision with Big Data and Predictive Analytics
Machine Translated
그 내용은 매우 흥미로 웠고 대학 시절 마지막 날에 도움이 될 것이라고 생각했습니다.
Krishan Mistry - NBrown Group
Course: From Data to Decision with Big Data and Predictive Analytics
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실용적인 응용 프로그램, 많은 다른 의문을 설명하는 데 도움이
SGB-Bank S.A.
Course: Data Vault: Building a Scalable Data Warehouse
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공구의 커패시턴스
Gerardo Avila - Reckitt Benckizer
Course: KNIME Analytics Platform for BI
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새로운 도구 배우기
MARIA ELENA DOMINGUEZ ESCUDERO - Reckitt Benckizer
Course: KNIME Analytics Platform for BI
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나는 정말 모든 최고의 즐겼다.
Halil polat - Amazon Development Center Poland Sp. z o.o.
Course: Data Mining and Analysis
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트레이너는 주요 주제에 집중 했다.
Amazon Development Center Poland Sp. z o.o.
Course: Data Mining and Analysis
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전문 지식과 트레이너의 거 대 한 지식.
Amazon Development Center Poland Sp. z o.o.
Course: Data Mining and Analysis
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나는 지도와 생활의 예를 공유 하는 혜택을 했다 + 모든 질문에 대답.
Marta Melloch - Amazon Development Center Poland Sp. z o.o.
Course: Data Mining and Analysis
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정말 새롭고 흥미로운 것 들을 배우는 것을 즐겼다.
SIVECO Romania SA
Course: Data Mining
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나는 함께 따를 수 있는 좋은 모범과 기회 로부터 유익을 얻을 수 있었다.
Environmental and Climate Change Canada
Course: Foundation R
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나는 진정으로 손을 통과 연습을 즐겼다.
Yunfa Zhu - Environmental and Climate Change Canada
Course: Foundation R
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트레이너는 개인 이해에 대 한 매우 우려 했다.
Muhammad Surajo Sanusi - Birmingham City University
Course: Foundation R
Machine Translated
Excel 프레젠테이션을 빌려 주었고 지식으로 얻은 자신감을 얻을 수있었습니다.
Birmingham City University
Course: Foundation R
Machine Translated
트레이너의 배경 지식과 '출처'.
Francis McGonigal - Birmingham City University
Course: Foundation R
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자원
Hafiz Rana - Birmingham City University
Course: Foundation R
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Go 우리가 일을하는 방법에 대한 외경 설명을
Birmingham City University
Course: Foundation R
Machine Translated
나는 지금 코딩에 자신감을 느낀다. 나는 전에 그것을 해본 적이 없지만, 이제는 로켓 과학이 아니라 필요할 때 그것을 할 수 있다는 것을 이해합니다.
Anna Yartseva - Birmingham City University
Course: Foundation R
Machine Translated
교사가 잘 전달한 지식으로 대답 할 수없는 질문은 없습니다.
Karolin Papaj - Mowi Poland SA
Course: Data Mining and Analysis
Machine Translated
그래픽 형식으로 발표하고 다음 단계를 논의하며 SQL
Volkswagen Financial Services Polska Sp. z o.o.,
Course: Data Vault: Building a Scalable Data Warehouse
Machine Translated
데이터 수집서브 카테고리
데이터 수집코스 개요
코스 이름
Duration
Overview
코스 이름
Duration
Overview
14 시간
Overview
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.
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.
21 시간
Overview
Course can be provided with any tools, including free open-source data mining software and applications
21 시간
Overview
Audience
If you try to make sense out of the data you have access to or want to analyse unstructured data available on the net (like Twitter, Linked in, etc...) this course is for you.
It is mostly aimed at decision makers and people who need to choose what data is worth collecting and what is worth analyzing.
It is not aimed at people configuring the solution, those people will benefit from the big picture though.
Delivery Mode
During the course delegates will be presented with working examples of mostly open source technologies.
Short lectures will be followed by presentation and simple exercises by the participants
Content and Software used
All software used is updated each time the course is run, so we check the newest versions possible.
It covers the process from obtaining, formatting, processing and analysing the data, to explain how to automate decision making process with machine learning.
If you try to make sense out of the data you have access to or want to analyse unstructured data available on the net (like Twitter, Linked in, etc...) this course is for you.
It is mostly aimed at decision makers and people who need to choose what data is worth collecting and what is worth analyzing.
It is not aimed at people configuring the solution, those people will benefit from the big picture though.
Delivery Mode
During the course delegates will be presented with working examples of mostly open source technologies.
Short lectures will be followed by presentation and simple exercises by the participants
Content and Software used
All software used is updated each time the course is run, so we check the newest versions possible.
It covers the process from obtaining, formatting, processing and analysing the data, to explain how to automate decision making process with machine learning.
14 시간
Overview
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.
14 시간
Overview
The objective of the course is to enable participants to gain a mastery of how to work with the SQL language in Oracle database for data extraction at intermediate level.
28 시간
Overview
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.
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.
28 시간
Overview
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.
14 시간
Overview
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.
28 시간
Overview
This course is intended for engineers and decision makers working in data mining and knoweldge discovery.
You will learn how to create effective plots and ways to present and represent your data in a way that will appeal to the decision makers and help them to understand hidden information.
You will learn how to create effective plots and ways to present and represent your data in a way that will appeal to the decision makers and help them to understand hidden information.
35 시간
Overview
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.
21 시간
Overview
MATLAB is a numerical computing environment and programming language developed by MathWorks.
28 시간
Overview
In this instructor-led, live training in 대한민국, participants will learn how to build a Data Vault.
By the end of this training, participants will be able to:
- Understand the architecture and design concepts behind Data Vault 2.0, and its interaction with Big Data, NoSQL and AI.
- Use data vaulting techniques to enable auditing, tracing, and inspection of historical data in a data warehouse.
- Develop a consistent and repeatable ETL (Extract, Transform, Load) process.
- Build and deploy highly scalable and repeatable warehouses.
By the end of this training, participants will be able to:
- Understand the architecture and design concepts behind Data Vault 2.0, and its interaction with Big Data, NoSQL and AI.
- Use data vaulting techniques to enable auditing, tracing, and inspection of historical data in a data warehouse.
- Develop a consistent and repeatable ETL (Extract, Transform, Load) process.
- Build and deploy highly scalable and repeatable warehouses.
28 시간
Overview
MonetDB is an open-source database that pioneered the column-store technology approach.
In this instructor-led, live training, participants will learn how to use MonetDB and how to get the most value out of it.
By the end of this training, participants will be able to:
- Understand MonetDB and its features
- Install and get started with MonetDB
- Explore and perform different functions and tasks in MonetDB
- Accelerate the delivery of their project by maximizing MonetDB capabilities
Audience
- Developers
- Technical experts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn how to use MonetDB and how to get the most value out of it.
By the end of this training, participants will be able to:
- Understand MonetDB and its features
- Install and get started with MonetDB
- Explore and perform different functions and tasks in MonetDB
- Accelerate the delivery of their project by maximizing MonetDB capabilities
Audience
- Developers
- Technical experts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
7 시간
Overview
The objective of the course is to enable participants to gain a mastery of the fundamentals of R and how to work with data.
21 시간
Overview
KNIME Analytics Platform is a leading open source option for data-driven innovation, helping you discover the potential hidden in your data, mine for fresh insights, or predict new futures. With more than 1000 modules, hundreds of ready-to-run examples, a comprehensive range of integrated tools, and the widest choice of advanced algorithms available, KNIME Analytics Platform is the perfect toolbox for any data scientist and business analyst.
This course for KNIME Analytics Platform is an ideal opportunity for beginners, advanced users and KNIME experts to be introduced to KNIME, to learn how to use it more effectively, and how to create clear, comprehensive reports based on KNIME workflows
This course for KNIME Analytics Platform is an ideal opportunity for beginners, advanced users and KNIME experts to be introduced to KNIME, to learn how to use it more effectively, and how to create clear, comprehensive reports based on KNIME workflows
14 시간
Overview
This instructor-led, live training (online or onsite) is aimed at data analysts and data scientists who wish to implement more advanced data analytics techniques for data mining using Python.
By the end of this training, participants will be able to:
- Understand important areas of data mining, including association rule mining, text sentiment analysis, automatic text summarization, and data anomaly detection.
- Compare and implement various strategies for solving real-world data mining problems.
- Understand and interpret the results.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
By the end of this training, participants will be able to:
- Understand important areas of data mining, including association rule mining, text sentiment analysis, automatic text summarization, and data anomaly detection.
- Compare and implement various strategies for solving real-world data mining problems.
- Understand and interpret the results.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
35 시간
Overview
KNIME is a free and open-source data analytics, reporting and integration platform. KNIME integrates various components for machine learning and data mining through its modular data pipelining concept. A graphical user interface and use of JDBC allows assembly of nodes blending different data sources, including preprocessing (ETL: Extraction, Transformation, Loading), for modeling, data analysis and visualization without, or with only minimal, programming. To some extent as advanced analytics tool KNIME can be considered as a SAS alternative.
Since 2006, KNIME has been used in pharmaceutical research, it also used in other areas like CRM customer data analysis, business intelligence and financial data analysis.
Since 2006, KNIME has been used in pharmaceutical research, it also used in other areas like CRM customer data analysis, business intelligence and financial data analysis.
14 시간
Overview
This instructor-led, live training in 대한민국 (online or onsite) is aimed at data analysts who wish to program with R in SAS for cluster analysis.
By the end of this training, participants will be able to:
- Use cluster analysis for data mining
- Master R syntax for clustering solutions.
- Implement hierarchical and non-hierarchical clustering.
- Make data-driven decisions to help to improve business operations.
By the end of this training, participants will be able to:
- Use cluster analysis for data mining
- Master R syntax for clustering solutions.
- Implement hierarchical and non-hierarchical clustering.
- Make data-driven decisions to help to improve business operations.
14 시간
Overview
This instructor-led, live training in 대한민국 (online or onsite) is aimed at data scientists who wish to use Excel for data mining.
- By the end of this training, participants will be able to:
- Explore data with Excel to perform data mining and analysis.
- Use Microsoft algorithms for data mining.
- Understand concepts in Excel data mining.
- By the end of this training, participants will be able to:
- Explore data with Excel to perform data mining and analysis.
- Use Microsoft algorithms for data mining.
- Understand concepts in Excel data mining.
21 시간
Overview
Pentaho Data Integration is an open-source data integration tool for defining jobs and data transformations.
In this instructor-led, live training, participants will learn how to use Pentaho Data Integration's powerful ETL capabilities and rich GUI to manage an entire big data lifecycle and maximize the value of data within their organization.
By the end of this training, participants will be able to:
- Create, preview, and run basic data transformations containing steps and hops
- Configure and secure the Pentaho Enterprise Repository
- Harness disparate sources of data and generate a single, unified version of the truth in an analytics-ready format.
- Provide results to third-part applications for further processing
Audience
- Data Analyst
- ETL developers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn how to use Pentaho Data Integration's powerful ETL capabilities and rich GUI to manage an entire big data lifecycle and maximize the value of data within their organization.
By the end of this training, participants will be able to:
- Create, preview, and run basic data transformations containing steps and hops
- Configure and secure the Pentaho Enterprise Repository
- Harness disparate sources of data and generate a single, unified version of the truth in an analytics-ready format.
- Provide results to third-part applications for further processing
Audience
- Data Analyst
- ETL developers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
28 시간
Overview
Pentaho Open Source BI Suite Community Edition (CE) is a business intelligence package that provides data integration, reporting, dashboards, and load capabilities.
In this instructor-led, live training, participants will learn how to maximize the features of Pentaho Open Source BI Suite Community Edition (CE).
By the end of this training, participants will be able to:
- Install and configure Pentaho Open Source BI Suite Community Edition (CE)
- Understand the fundamentals of Pentaho CE tools and their features
- Build reports using Pentaho CE
- Integrate third party data into Pentaho CE
- Work with big data and analytics in Pentaho CE
Audience
- Programmers
- BI Developers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- To request a customized training for this course, please contact us to arrange.
In this instructor-led, live training, participants will learn how to maximize the features of Pentaho Open Source BI Suite Community Edition (CE).
By the end of this training, participants will be able to:
- Install and configure Pentaho Open Source BI Suite Community Edition (CE)
- Understand the fundamentals of Pentaho CE tools and their features
- Build reports using Pentaho CE
- Integrate third party data into Pentaho CE
- Work with big data and analytics in Pentaho CE
Audience
- Programmers
- BI Developers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- To request a customized training for this course, please contact us to arrange.
21 시간
Overview
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 instructor-led, live 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.
In this instructor-led, live 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.
21 시간
Overview
Process mining, or Automated Business Process Discovery (ABPD), is a technique that applies algorithms to event logs for the purpose of analyzing business processes. Process mining goes beyond data storage and data analysis; it bridges data with processes and provides insights into the trends and patterns that affect process efficiency.
Format of the Course
- The course starts with an overview of the most commonly used techniques for process mining. We discuss the various process discovery algorithms and tools used for discovering and modeling processes based on raw event data. Real-life case studies are examined and data sets are analyzed using the ProM open-source framework.
Format of the Course
- The course starts with an overview of the most commonly used techniques for process mining. We discuss the various process discovery algorithms and tools used for discovering and modeling processes based on raw event data. Real-life case studies are examined and data sets are analyzed using the ProM open-source framework.
향후데이터 수집 코스
09-08-2021 10:00
21 hours
23-08-2021 10:00
28 hours
24-08-2021 10:00
28 hours
13-09-2021 10:00
14 hours
16-09-2021 10:00
14 hours
Other countries
Consulting
주말데이터 수집코스, 밤의데이터 수집트레이닝, 데이터 수집부트 캠프, 데이터 수집 강사가 가르치는, 주말데이터 수집교육, 밤의데이터 수집과정, 데이터 수집코칭, 데이터 수집강사, 데이터 수집트레이너, 데이터 수집교육 과정, 데이터 수집클래스, 데이터 수집현장, 데이터 수집개인 강좌, 데이터 수집1 대 1 교육
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