Osaka Kokusai

31/F Osaka Kokusai Building, Osaka, japan, 541-0052
Osaka's Kokusai Centre is on the top floor of a 31-storey landmark building in Honmachi within the city's main business distr...

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Knowledge Discovery in Databases (KDD)

Explore Our Courses

Data Mining with Weka

14 Hours
This instructor-led, live training in Osaka (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.
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SPSS Modeler

14 Hours
This instructor-led, live training in Osaka (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.
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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.
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Data Mining with Excel

14 Hours
This instructor-led, live training in Osaka (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.
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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.
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Cluster Analysis with R and SAS

14 Hours
This instructor-led, live training in Osaka (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.
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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.
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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.
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Data Mining

21 Hours
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 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.
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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.
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Data Vault: Building a Scalable Data Warehouse

28 Hours
In this instructor-led, live training in Osaka, 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.
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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.
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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.
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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.
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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.
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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
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Platforma analityczna KNIME - szkolenie kompleksowe

35 Hours
The "KNIME Analytics Platform" training offers a comprehensive overview of this free data analytics platform. The program includes an introduction to data processing and analysis, KNIME installation and configuration, workflow building, methodology for creating business models and data modeling. The course also covers advanced data analysis tools, workflow import and export, tool integration, ETL processes, data mining, visualization, extensions and integrations with tools such as R, Java, Python, Gephi, Neo4j. The conclusion includes an overview of reporting, integration with BIRT and KNIME WebPortal.
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MATLAB for Financial Applications

21 Hours
MATLAB is a numerical computing environment and programming language developed by MathWorks.
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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
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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.
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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.
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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.
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Testimonials (17)

The content, as I found it very interesting and think it would help me in my final year at University.

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

I was benefit from the guidance and sharing life examples + answering all questions.

Marta Melloch - Amazon Development Center Poland Sp. z o.o.
Course - Data Mining and Analysis

I really enjoyed the all the best.

Halil polat - Amazon Development Center Poland Sp. z o.o.
Course - Data Mining and Analysis

The information given was interesting and the best part was towards the end when we were provided with Data from Durex and worked on Data we are familiar with and perform operations to get results.

Jessica Chaar
Course - Data Mining and Analysis

Very tailored to needs.

Yashan Wang
Course - Data Mining with R

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

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

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

Ronald Parrish
Course - Data Visualization

I liked the examples.

Peter Coleman
Course - Data Visualization

I liked the examples.

Peter Coleman
Course - Data Visualization

I am a hands-on learner and this was something that he did a lot of.

Lisa Comfort
Course - Data Visualization

Trainer was enthusiastic.

Diane Lucas
Course - Data Visualization

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

Mohamed Salama
Course - Data Mining & Machine Learning with R

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

Marija Hornis Dmitrovic - Marija Hornis
Course - Data Science for Big Data Analytics

The example and training material were sufficient and made it easy to understand what you are doing.

Teboho Makenete
Course - Data Science for Big Data Analytics

I feel more confident with coding now. I've never done it before but now I understand that it's not rocket science and I can do it when necessary.

Anna - Birmingham City University
Course - Foundation R

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
Course - KNIME Analytics Platform for BI

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
Course - Process Mining

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