Local, instructor-led Data Mining training courses demonstrate through hands-on practice the fundamentals of Data Mining, its sources of methods including Artificial intelligence, Machine learning, Statistics and Database systems, and its use and applications.

Data Mining training is available as "onsite live training" or "remote live training". Saudi Arabia onsite live Data Mining trainings can be carried out locally on customer premises or in NobleProg corporate training centers. Remote live training is carried out by way of an interactive, remote desktop.

NobleProg -- Your Local Training Provider

Testimonials

★★★★★

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 exercises 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 Durex 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 cluttering. Learning about the methods to show time data.

Susan Williams

Course: Data Visualization

Trainer was enthusiastic.

Diane Lucas

Course: Data Visualization

I really liked the 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

I liked the examples.

Peter Coleman

Course: Data Visualization

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

Ronald Parrish

Course: Data Visualization

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

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

Data Mining Subcategories

Data Mining Course Outlines

Title

Duration

Overview

Title

Duration

Overview

From Data to Decision with Big Data and Predictive Analytics

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.

KNIME Analytics Platform for BI

21 hours

Overview

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

Introductory R for Biologists

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.

Pentaho Data Integration Fundamentals

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

Pentaho Open Source BI Suite Community Edition (CE)

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.

Oracle SQL Intermediate - Data Extraction

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.

MonetDB

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

MATLAB for Financial Applications

21 hours

Overview

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

KNIME Analytics Platform - comprehensive training

35 hours

Overview

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.

Knowledge Discovery in Databases (KDD)

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 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.

Data Mining and Analysis

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.

Foundation R

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.

Data Science for Big Data Analytics

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.

Data Mining & Machine Learning with R

14 hours

Overview

Data Visualization

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.

Data Vault: Building a Scalable Data Warehouse

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

Data Mining with R

14 hours

Overview

Data Mining with Python

14 hours

Overview

This instructor-led, live training (onsite or remote) 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.

Data Mining

21 hours

Overview

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

Statistics with SPSS Predictive Analytics Software

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.

Process 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.

Other regions

;Jeddah Riyadh

Other countries

These courses are also available in other countries ››

Consulting

Data Mining Consulting

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