Local instructor-led live Data Mining training courses in България.
Oтзиви от потребители
the scope of material
Maciej Jonczyk
Course: From Data to Decision with Big Data and Predictive Analytics
systematizing knowledge in the field of ML
Orange Polska
Course: From Data to Decision with Big Data and Predictive Analytics
A lot of issues that can be explored after the training
Klaudia Kłębek
Course: Data Mining with R
The trainer was so knowledgeable and included areas I was interested in
Mohamed Salama
Course: Data Mining & Machine Learning with R
very tailored to needs
Yashan Wang
Course: Data Mining with R
I like the exercices done
Nour Assaf
Course: Data Mining and Analysis
The hands on exercise and the trainer capacity to explain complex topics in simple terms
youssef chamoun
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 Murex and worked on Data we are familiar with and perform operations to get results.
Jessica Chaar
Course: Data Mining and Analysis
I thought that the information was interesting.
Allison May
Course: Data Visualization
I really appreciated that Jeff utilized data and examples that were applicable to education data. He made it interesting and interactive.
Carol Wells Bazzichi
Course: Data Visualization
Learning about all the chart types and what they are used for. Learning the value of decluttering. Learning about the methods to show time data.
Susan Williams
Course: Data Visualization
Trainer was enthusiastic.
Diane Lucas
Course: Data Visualization
Content / Instructor
Craig Roberson
Course: Data Visualization
I am a hands-on learner and this was something that he did a lot of.
Lisa Comfort
Course: Data Visualization
I liked the examples.
Peter Coleman
Course: Data Visualization
The examples.
Peter Coleman
Course: Data Visualization
Good real world examples, reviews of existing reports
Ronald Parrish
Course: Data Visualization
Example exercises; Practical work experience sharing
澳新银行
Course: Data Vault: Building a Scalable Data Warehouse
The teacher's knowledge of the data warehouse is comprehensive, and he praises it!
澳新银行
Course: Data Vault: Building a Scalable Data Warehouse
The teacher explained in detail and discussed the atmosphere
澳新银行
Course: Data Vault: Building a Scalable Data Warehouse
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
Richard's training style kept it interesting, the real world examples used helped to drive the concepts home.
Jamie Martin-Royle - NBrown Group
Course: From Data to Decision with Big Data and Predictive Analytics
The content, as I found it very interesting and think it would help me in my final year at University.
Krishan Mistry - NBrown Group
Course: From Data to Decision with Big Data and Predictive Analytics
Practical application, help in explaining many different doubts
SGB-Bank S.A.
Course: Data Vault: Building a Scalable Data Warehouse
The capacitance of the tool
Gerardo Avila - Reckitt Benckizer
Course: KNIME Analytics Platform for BI
Learning a new tool
MARIA ELENA DOMINGUEZ ESCUDERO - Reckitt Benckizer
Course: KNIME Analytics Platform for BI
I really enjoyed the all the best.
Halil polat - Amazon Development Center Poland Sp. z o.o.
Course: Data Mining and Analysis
The trainer concentrated on the key topics.
Amazon Development Center Poland Sp. z o.o.
Course: Data Mining and Analysis
Expertise and huge knowledge of the trainer.
Amazon Development Center Poland Sp. z o.o.
Course: Data Mining and Analysis
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 learning new and interesting things.
SIVECO Romania SA
Course: Data Mining
I was benefit from the good examples and opportunity to follow along.
Environmental and Climate Change Canada
Course: Foundation R
I genuinely enjoyed the hands passed exercises.
Yunfa Zhu - Environmental and Climate Change Canada
Course: Foundation R
The trainer was very concern about individual understanding.
Muhammad Surajo Sanusi - Birmingham City University
Course: Foundation R
Excellent presentation and it gives me confidence to build on knowledge gained.
Birmingham City University
Course: Foundation R
Background knowledge and 'provenance' of trainer.
Francis McGonigal - Birmingham City University
Course: Foundation R
Resources
Hafiz Rana - Birmingham City University
Course: Foundation R
Good explanations on how we do things
Birmingham City University
Course: Foundation R
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 Yartseva - Birmingham City University
Course: Foundation R
The Topic
Accenture Inc.
Course: Data Vault: Building a Scalable Data Warehouse
Very well transferred knowledge by the teacher. No unanswered questions.
Karolin Papaj - Mowi Poland SA
Course: Data Mining and Analysis
Intensity, Training materials and expertise, Clarity, Excellent communication with Alessandra
Marija Hornis Dmitrovic - Marija Hornis
Course: Data Science for Big Data Analytics
Data Mining Subcategories
Data Mining Course Outlines
This instructor-led, live training (onsite or remote) 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.
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.
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
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.
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
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.
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
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.
This instructor-led, live training (onsite or remote) 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.
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.
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
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.
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.
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.
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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