Process Miningのトレーニングコース

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.

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.

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

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.

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.

Insurtech (a.k.a Digital Insurance) refers to the convergence of insurance + new technologies. In the field of Insurtech "digital insurers" apply technology innovations to their business and operating models in order to reduce costs, improve the customer experience and enhance the agility of their operations.

In this instructor-led training, participants will gain an understanding of the technologies, methods and mindset needed to bring about a digital transformation within their organizations and in the industry at large. The training is aimed at managers who need to gain a big picture understanding, break down the hype and jargon, and take the first steps in establishing an Insurtech strategy.

By the end of this training, participants will be able to:

• Discuss Insurtech and all its component parts intelligently and systematically
• Identify and demystify the role of each key technology within Insurtech.
• Draft a general strategy for implementing Insurtech within their organization

Audience

• Insurers
• Technologists within the insurance industry
• Insurance stakeholders
• Consultants and business analysts

Format of the course

• Part lecture, part discussion, exercises and case study group activities

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.

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.

In this instructor-led, live training in 日本, participants will gain an understanding of the technologies, methods and mindset needed to implement a Fintech strategy.

This training is aimed at managers who need to gain a "big picture" understanding of Fintech, break down the hype and jargon, and take tangible first steps towards the adoption of new technologies applicable to financial business and services.

By the end of this training, participants will be able to

• Present viable Fintech strategies for their organization.
• Understand and explain the role and functionality of key technologies.
• Draft an action plan for introducing new technologies in step-by-step fashion.

Model Based Development (MBD) is a software development methodology that enables faster, more cost-effective development of dynamic systems such as control systems, signal processing and communication systems. It relies on graphic modeling rather than the traditional text based programming.

In this instructor-led, live training participants will learn how to apply MBD methodologies to reduce development costs and accelerate the time to market of their embedded software products.

By the end of this training, participants will be able to

• Select and utilize the right tools for implementing MBD.
• Use MBD to carry out rapid development in the early stages of their embedded software project.
• Shorten the release of their embedded software into the market.

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

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.

This instructor-led, live training in 日本 (online or onsite) is aimed at persons who wish to understand requirements analysis and conduct requirements analysis efficiently and accurately using analysis techniques for their projects.

By the end of this training, participants will be able to:

• identify different types of requirements.
• understand the overall concepts of, and activities within, requirements analysis.
• be familiar with the requirements analysis methodology.
• use different requirements analysis techniques to their advantage.
• structure requirements in order to communicate efficiently with architects and developers through an iterative requirement gathering process.

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.

This course demonstrates through hands-on practice the fundamentals and applications of software engineering, requirements engineering and testing.

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.