Data Mining Training Courses

Data Mining Training Courses

Τα τοπικά μαθήματα κατάρτισης Data Mining υπό την καθοδήγηση του διδακτικού προσωπικού καταδεικνύουν με πρακτική εφαρμογή τα βασικά στοιχεία της Εξόρυξης Δεδομένων, τις πηγές μεθόδων της, συμπεριλαμβανομένης της Τεχνητής Νοημοσύνης, της Μηχανικής Μάθησης, των Στατιστικών και των Βάσεων Δεδομένων, καθώς και τη χρήση και εφαρμογές της. Η εκπαίδευση εξόρυξης δεδομένων είναι διαθέσιμη ως "επιτόπου ζωντανή εκπαίδευση" ή "μακρινή ζωντανή εκπαίδευση". Η επιτόπια κατάρτιση σε πραγματικό χρόνο μπορεί να πραγματοποιηθεί σε τοπικό επίπεδο στις εγκαταστάσεις του πελάτη Ελλάδα ή σε εταιρικά κέντρα κατάρτισης NobleProg στο Ελλάδα . Η απομακρυσμένη ζωντανή προπόνηση πραγματοποιείται μέσω μιας διαδραστικής, απομακρυσμένης επιφάνειας εργασίας. NobleProg - Ο τοπικός παροχέας εκπαίδευσης

Testimonials

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Data Mining Course Outlines

Title
Duration
Overview
Title
Duration
Overview
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.
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 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.
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.
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.

Audience
Data science professionals
Anyone interested in understanding and applying process modeling and 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, maximizing the value of data to the 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.
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
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
21 hours
Overview
MATLAB is a numerical computing environment and programming language developed by MathWorks.
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.
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.
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.
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.
28 hours
Overview
Data Vault Modeling is a database modeling technique that provides long-term historical storage of data that originates from multiple sources. A data vault stores a single version of the facts, or "all the data, all the time". Its flexible, scalable, consistent and adaptable design encompasses the best aspects of 3rd normal form (3NF) and star schema.

In this instructor-led, live training, 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.

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
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
αυτή η καθοδηγούμενη από εκπαιδευτές, ζωντανή εκπαίδευση (επιτόπου ή απομακρυσμένη) απευθύνεται σε αναλυτές δεδομένων και επιστήμονες δεδομένων που επιθυμούν να εφαρμόσουν πιο προηγμένες τεχνικές ανάλυσης δεδομένων για την εξόρυξη δεδομένων χρησιμοποιώντας την Python.

μέχρι το τέλος αυτής της εκπαίδευσης, οι συμμετέχοντες θα είναι σε θέση να:

- κατανοούν σημαντικούς τομείς εξόρυξης δεδομένων, συμπεριλαμβανομένης της εξόρυξης κανόνων σύνδεσης, της ανάλυσης συναισθήματος κειμένου, του αυτόματου Σύνοψη κειμένου και της ανίχνευσης ανωμαλιών δεδομένων.
- συγκρίνετε και να εφαρμόσουν διάφορες στρατηγικές για την επίλυση προβλημάτων εξόρυξης δεδομένων πραγματικού κόσμου.
- Κατανοήστε και ερμηνεύστε τα αποτελέσματα.

μορφή του μαθήματος

- διαδραστική διάλεξη και συζήτηση.
- πολλές ασκήσεις και εξάσκηση.
- εφαρμογή σε περιβάλλον ζωντανού εργαστηρίου.

επιλογές προσαρμογής μαθήματος

- για να ζητήσετε μια προσαρμοσμένη εκπαίδευση για αυτό το μάθημα, παρακαλούμε επικοινωνήστε μαζί μας για να κανονίσετε.
21 hours
Overview
Course can be provided with any tools, including free open-source data mining software and applications
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.

Upcoming Data Mining Courses

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