Explore Our Courses

Data Mining with Weka

 14 時間
Waikato Environment for Knowledge Analysis (Weka) is an open-source data mining visualization software. It provides a collection of machine learning algorithms for data preparation, classification, clustering, and other data mining activities. This instructor-led, live training (online or onsite) is aimed at beginner to intermediate-level data analysts and data scientists who wish to use Weka to perform data mining tasks. By the end of this training, participants will be able to:
  • Install and configure Weka.
  • Understand the Weka environment and workbench.
  • Perform data mining tasks using Weka.
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.
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SPSS Modeler

 14 時間
IBM SPSS Modeler is a software used for data mining and text analytics. It provides a set of data mining tools that can build predictive models and perform data analytic tasks. This instructor-led, live training (online or onsite) is aimed at data analysts or anyone who wishes to use SPSS Modeler to perform data mining activities. By the end of this training, participants will be able to:
  • Understand the fundamentals of data mining.
  • Learn how to import and assess data quality with the Modeler.
  • Develop, deploy, and evaluate data models efficiently.
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.
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Knowledge Discovery in Databases (KDD)

 21 時間
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.
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Data Mining with Excel

 14 時間
Data mining is the process of identifying patterns in big data with data science methods such as machine learning. Using Excel as a data analytical suite, users can perform data mining and analysis. This instructor-led, live training (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.
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.
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Oracle SQL Intermediate - Data Extraction

 14 時間
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.
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Cluster Analysis with R and SAS

 14 時間
R is a programming language and software environment for statistical computing. SAS is a statistical software platform for predictive analysis, data management, advanced analytics, and more. With R in SAS, users can find natural groups of data for cluster analysis that are essential to data mining. This instructor-led, live training (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.
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.
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From Data to Decision with Big Data and Predictive Analytics

 21 時間
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.
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Data Mining and Analysis

28 時間
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.
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Data Mining

 21 時間
Course can be provided with any tools, including free open-source data mining software and applications
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Data Mining with Python

 14 時間
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.
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Data Mining with R

 14 時間
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.
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Data Vault: Building a Scalable Data Warehouse

 28 時間
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
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Data Visualization

 28 時間
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.
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Data Mining & Machine Learning with R

 14 時間
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.
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Data Science for Big Data Analytics

 35 時間
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.
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Foundation R

 7 時間
The objective of the course is to enable participants to gain a mastery of the fundamentals of R and how to work with data.
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KNIME Analytics Platform for BI

 21 時間
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
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Platforma analityczna KNIME - szkolenie kompleksowe

 35 時間
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.
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MATLAB for Financial Applications

 21 時間
MATLAB is a numerical computing environment and programming language developed by MathWorks.
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MonetDB

 28 時間
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
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Introductory R for Biologists

 28 時間
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.
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Statistics with SPSS Predictive Analytics Software

 14 時間
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.
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Process Mining

 21 時間
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.
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お客様の声(9)

how the trainor shows his knowledge in the subject he's teachign

john ernesto ii fernandez - Philippine AXA Life Insurance Corporation
コース - Data Vault: Building a Scalable Data Warehouse

I learned a lot - not only in theoretical knowledge but I also applied that knowledge during the training and therefore I really understood what process mining is and how it works. Thanks a lot!

Julia Dörre - Techniker Krankenkasse
コース - Process Mining

Very useful in because it helps me understand what we can do with the data in our context. It will also help me

Nicolas NEMORIN - Adecco Groupe France
コース - KNIME Analytics Platform for BI

Intensity, Training materials and expertise, Clarity, Excellent communication with Alessandra

Marija Hornis Dmitrovic - Marija Hornis
コース - Data Science for Big Data Analytics

今ではコーディングに自信が持てるようになりました。これまでやったことはありませんでしたが、今ではそれがロケット科学ではないことを理解しており、必要に応じて実行できます。

Anna - Birmingham City University
コース - Foundation R

Machine Translated

内容は非常に興味深かったので、大学最後の年に役立つと思いました。

Krishan - NBrown Group
コース - From Data to Decision with Big Data and Predictive Analytics

Machine Translated

I enjoyed the good real world examples, reviews of existing reports.

Ronald Parrish
コース - Data Visualization

Very tailored to needs.

Yashan Wang
コース - Data Mining with R

The trainer was so knowledgeable and included areas I was interested in.

Mohamed Salama
コース - Data Mining & Machine Learning with R

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