Data Mining Kurzusok

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Data Mining Kurzusok

A helyi, oktatói adatbányászati ​​tréningek a Handson gyakorlatban bemutatják az adatbányászat alapjait, a módszerek forrásait, beleértve a mesterséges intelligenciát, a gépi tanulást, a statisztikát és az adatbázis-rendszereket, valamint annak használatát és alkalmazását Az adatbányászati ​​tréning "helyszíni élő képzés" vagy "távoli élő képzés" formájában érhető el A helyszíni élő képzés helyi szinten valósulhat meg az ügyfél telephelyén Magyarország vagy a NobleProg vállalati oktatóközpontjaiban Magyarország A távoli élőképzés interaktív, távoli asztal segítségével történik NobleProg Az Ön Helyi Képzési Szolgáltatója.

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Data Mining Subcategories

Pentaho KurzusokPentaho
Knowledge Discovery in Databases (KDD) KurzusokKnowledge Discovery in Databases (KDD)

Data Mining Course Outlines

Kurzusnév
Időtartalma
Összefoglaló
Kurzusnév
Időtartalma
Összefoglaló

Statistics with 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.

Data Mining

21 hours
Course can be provided with any tools, including free open-source data mining software and applications

From Data to Decision with Big Data and Predictive Analytics

21 hours
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.

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.

Oracle SQL Intermediate - Data Extraction

14 hours
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.

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.

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.

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.

Data Visualization

28 hours
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.

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.

Data Vault: Building a Scalable Data Warehouse

28 hours
In this instructor-led, live training in Magyarország, 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.

MonetDB

28 hours
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

Foundation R

7 hours
The objective of the course is to enable participants to gain a mastery of the fundamentals of R and how to work with data.

KNIME Analytics Platform for BI

21 hours
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

Platforma analityczna KNIME - szkolenie kompleksowe

35 hours
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.

Cluster Analysis with R and SAS

14 hours
This instructor-led, live training in Magyarország (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.

Data Mining with Excel

14 hours
This instructor-led, live training in Magyarország (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.

Pentaho Data Integration Fundamentals

21 hours
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

Pentaho Open Source BI Suite Community Edition (CE)

28 hours
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.

Knowledge Discovery 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 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.

Data Mining with Python

14 hours
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.

Process Mining

21 hours
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.

Last Updated:

Upcoming Data Mining Courses

Data Mining and Analysis

17-01-2022 09:30
28 hours
Távoktatás 3400 EUR Tanterem N/A
Olvass tovább

Data Science for Big Data Analytics

17-01-2022 09:30
35 hours
Távoktatás 4250 EUR Tanterem N/A
Olvass tovább

Data Mining & Machine Learning with R

19-01-2022 09:30
14 hours
Távoktatás 1700 EUR Tanterem N/A
Olvass tovább

Introductory R for Biologists

14-02-2022 09:30
28 hours
Távoktatás 3400 EUR Tanterem N/A
Olvass tovább

Data Visualization

15-02-2022 09:30
28 hours
Távoktatás 3400 EUR Tanterem N/A
Olvass tovább

Other countries

Consulting

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Kedvezmények tanfolyamokra

Advanced R

07-01-2022 09:30
7 hours
Online850 EUR 765 EUR Tanterem1250 EUR N/A
Olvass tovább

Marketing Analytics using R

12-01-2022 09:30
21 hours
Online2550 EUR 2295 EUR Tanterem3350 EUR N/A
Olvass tovább

R for Data Analysis and Research

17-01-2022 09:30
7 hours
Online850 EUR 765 EUR Tanterem1250 EUR N/A
Olvass tovább

Basic MATLAB Programming

19-01-2022 09:30
21 hours
Online2550 EUR 2295 EUR Tanterem3350 EUR N/A
Olvass tovább

Machine Learning with Python

09-02-2022 09:30
28 hours
Online3400 EUR 3060 EUR Tanterem4400 EUR N/A
Olvass tovább
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Néhány ügyfelünk

is growing fast!

We are looking for a good mixture of IT and soft skills in Hungary!

As a NobleProg Trainer you will be responsible for:

  • delivering training and consultancy Worldwide
  • preparing training materials
  • creating new courses outlines
  • delivering consultancy
  • quality management

At the moment we are focusing on the following areas:

  • Statistic, Forecasting, Big Data Analysis, Data Mining, Evolution Alogrithm, Natural Language Processing, Machine Learning (recommender system, neural networks .etc...)
  • SOA, BPM, BPMN
  • Hibernate/Spring, Scala, Spark, jBPM, Drools
  • R, Python
  • Mobile Development (iOS, Android)
  • LAMP, Drupal, Mediawiki, Symfony, MEAN, jQuery
  • You need to have patience and ability to explain to non-technical people

To apply, please create your trainer-profile by going to the link below:

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