I corsi di formazione sul data mining locali e istruiti dimostrano attraverso la pratica pratica i fondamenti del data mining, le sue fonti di metodi, tra cui l'intelligenza artificiale, l'apprendimento automatico, i sistemi di statistiche e database e il suo uso e applicazioni L'addestramento sul data mining è disponibile come "allenamento dal vivo in loco" o "allenamento dal vivo a distanza" La formazione on-site in loco può essere svolta localmente presso la sede del cliente in Italia o nei centri di formazione aziendale NobleProg in Italia La formazione in remoto dal vivo viene effettuata tramite un desktop remoto interattivo NobleProg Il tuo fornitore di formazione locale.
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Recensioni
gamma di materiali
Maciej Jonczyk
Corso: From Data to Decision with Big Data and Predictive Analytics
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sistematizzare le conoscenze nel campo della ML
Orange Polska
Corso: From Data to Decision with Big Data and Predictive Analytics
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Un sacco di problemi che possono essere esplorati dopo la formazione
Klaudia Kłębek
Corso: Data Mining z wykorzystaniem R
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L'allenatore era così preparato e comprendeva le aree che mi interessavano.
Mohamed Salama
Corso: Data Mining & Machine Learning with R
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Molto su misura per esigenze.
Yashan Wang
Corso: Data Mining with R
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Mi piacciono gli esercizi fatti.
Nour Assaf
Corso: Data Mining and Analysis
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L'esercizio pratico e la capacità del formatore di spiegare argomenti complessi in termini semplici.
youssef chamoun
Corso: Data Mining and Analysis
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Le informazioni fornite sono state interessanti e la parte migliore è stata verso la fine quando ci sono stati forniti i dati di Durex e abbiamo lavorato su dati con cui abbiamo familiarità e che eseguiamo operazioni per ottenere risultati.
Jessica Chaar
Corso: Data Mining and Analysis
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Ho pensato che l'informazione fosse interessante.
Allison May
Corso: Data Visualization
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Ho davvero apprezzato il fatto che Jeff abbia utilizzato dati ed esempi applicabili ai dati sull'istruzione. Lo ha reso interessante e interattivo.
Carol Wells Bazzichi
Corso: Data Visualization
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Informazioni su tutti i tipi di grafici e su cosa sono utilizzati. Imparare il valore del disordine. Informazioni sui metodi per mostrare i dati temporali.
Susan Williams
Corso: Data Visualization
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L'allenatore era entusiasta.
Diane Lucas
Corso: Data Visualization
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Mi è piaciuto molto il contenuto / Istruttore.
Craig Roberson
Corso: Data Visualization
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Sono uno studente pratico e questo è stato qualcosa che ha fatto molto.
Lisa Comfort
Corso: Data Visualization
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Mi sono piaciuti gli esempi.
Peter Coleman
Corso: Data Visualization
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Generalmente ho tratto beneficio dagli esempi.
Peter Coleman
Corso: Data Visualization
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Mi sono piaciuti i buoni esempi del mondo reale, le recensioni dei rapporti esistenti.
Ronald Parrish
Corso: Data Visualization
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Esercizi di esempio, condivisione pratica di esperienze lavorative
澳新银行
Corso: Data Vault: Building a Scalable Data Warehouse
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Cubo e DV
Alan Xie
Corso: Data Vault: Building a Scalable Data Warehouse
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L'insegnante ha una conoscenza completa del data warehouse.
澳新银行
Corso: Data Vault: Building a Scalable Data Warehouse
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L'insegnante ha spiegato in dettaglio e discusso l'atmosfera
澳新银行
Corso: Data Vault: Building a Scalable Data Warehouse
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L'esempio e il materiale di formazione erano sufficienti e hanno reso facile capire cosa stai facendo.
Teboho Makenete
Corso: Data Science for Big Data Analytics
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Lo stile di formazione di Richard lo rendeva interessante, gli esempi del mondo reale usati contribuivano a portare a casa i concetti.
Jamie Martin-Royle - NBrown Group
Corso: From Data to Decision with Big Data and Predictive Analytics
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Il contenuto, come ho trovato molto interessante e penso che mi avrebbe aiutato nel mio ultimo anno all'Università.
Krishan Mistry - NBrown Group
Corso: From Data to Decision with Big Data and Predictive Analytics
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Applicazione pratica, aiuto nello spiegare molti diversi dubbi
SGB-Bank S.A.
Corso: Data Vault: Building a Scalable Data Warehouse
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La capacità dello strumento
Gerardo Avila - Reckitt Benckizer
Corso: KNIME Analytics Platform for BI
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Imparare un nuovo strumento
MARIA ELENA DOMINGUEZ ESCUDERO - Reckitt Benckizer
Corso: KNIME Analytics Platform for BI
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Mi è piaciuto molto il tutto il meglio.
Halil polat - Amazon Development Center Poland Sp. z o.o.
Corso: Data Mining and Analysis
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Il formatore si è concentrato sugli argomenti chiave.
Amazon Development Center Poland Sp. z o.o.
Corso: Data Mining and Analysis
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Competenza e grande conoscenza del formatore.
Amazon Development Center Poland Sp. z o.o.
Corso: Data Mining and Analysis
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Ho potuto trarre beneficio dalla guida e condividere esempi di vita + rispondendo a tutte le domande.
Marta Melloch - Amazon Development Center Poland Sp. z o.o.
Corso: Data Mining and Analysis
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Mi è piaciuto molto imparare cose nuove e interessanti.
SIVECO Romania SA
Corso: Data Mining
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Ho potuto trarre beneficio dai buoni esempi e dall'opportunità di seguirmi.
Environmental and Climate Change Canada
Corso: Foundation R
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Ho davvero apprezzato le mani passati esercizi.
Yunfa Zhu - Environmental and Climate Change Canada
Corso: Foundation R
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Il formatore era molto preoccupato per la comprensione individuale.
Muhammad Surajo Sanusi - Birmingham City University
Corso: Foundation R
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Excel prestato la presentazione e mi dà fiducia per sviluppare le conoscenze acquisite.
Birmingham City University
Corso: Foundation R
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Conoscenza di base e "provenienza" del formatore.
Francis McGonigal - Birmingham City University
Corso: Foundation R
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risorse
Hafiz Rana - Birmingham City University
Corso: Foundation R
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Go spiegazioni su come facciamo le cose
Birmingham City University
Corso: Foundation R
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Mi sento più sicuro con la programmazione ora. Non l'ho mai fatto prima, ma ora capisco che non è scienza missilistica e posso farlo quando necessario.
Anna Yartseva - Birmingham City University
Corso: Foundation R
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Conoscenza trasferita molto bene dall'insegnante Nessuna domanda senza risposta.
Karolin Papaj - Mowi Poland SA
Corso: Data Mining and Analysis
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presentando in forma grafica e discutendo il passaggio successivo, che verrà eseguito in SQL
Volkswagen Financial Services Polska Sp. z o.o.,
Corso: Data Vault: Building a Scalable Data Warehouse
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Sottocategorie Data Mining
Schema generale del corso Data Mining
Nome del corso
Durata
Overview
Nome del corso
Durata
Overview
14 hours
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 hours
Overview
Course can be provided with any tools, including free open-source data mining software and applications
21 hours
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 hours
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 hours
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 hours
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 hours
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 hours
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 hours
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 hours
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.
28 hours
Overview
In this instructor-led, live training in Italia, 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 hours
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 hours
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 hours
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 hours
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 hours
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 hours
Overview
This instructor-led, live training in Italia (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 hours
Overview
This instructor-led, live training in Italia (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 hours
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 hours
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 hours
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 hours
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.
Prossimi corsi Data Mining
31-08-2021 09:30
28 ore
02-09-2021 09:30
14 ore
14-09-2021 09:30
14 ore
04-10-2021 09:30
28 ore
12-10-2021 09:30
28 ore
Other countries
Consulting
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