Statistics Training in the UAE

This instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level engineers and designers who wish to use DFSS to ensure that quality is built into the product or process from the start of the design phase.

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

• Understand the principles and concepts of Design Six Sigma (DFSS).
• Learn the DMAIC (Define, Measure, Analyze, Improve, Control) and DMADV (Define, Measure, Analyze, Design, Verify) methodologies.
• Apply DFSS tools and techniques to design and optimize processes.
• Develop skills to manage and lead DFSS projects effectively.

This instructor-led, live training in the UAE (online or onsite) is aimed at advanced-level professionals who wish to gain an in-depth understanding of the Six Sigma DMAIC methodology at a Black Belt level.

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

• Develop a comprehensive understanding of the Define, Measure, Analyze, Improve, and Control phases with a focus on complex projects.
• Gain expertise in advanced statistical analysis techniques for data-driven decision-making.
• Lead large-scale Six Sigma projects and manage project teams effectively.
• Implement significant process improvements that align with organizational goals and strategies.

This instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level professionals who wish to have a comprehensive understanding of the DMAIC methodology and prepare for the role of an effective Six Sigma Green Belts.

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

• Gain a thorough knowledge of the Define, Measure, Analyze, Improve, and Control phases of Six Sigma.
• Apply a wide range of Six Sigma tools and techniques effectively within each phase of DMAIC.
• Perform and interpret statistical analyses for process improvement.
• Plan, execute, and manage a Six Sigma project.

This instructor-led, live training in the UAE (online or onsite) is aimed at beginner-level professionals who wish to have a fundamental understanding of Six Sigma and Lean principles to integrate them and improve business processes.

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

• Obtain a solid understanding of Lean Six Sigma principles.
• Use Six Sigma methodologies to improve process quality by removing the causes of defects and minimizing variability.
• Integrate Lean and Six Sigma methodologies to achieve more efficient and effective process improvements.
• Teach basic Lean Six Sigma tools and techniques that Yellow Belts can apply in process improvement projects, such as 5S, Kaizen, and process mapping.

This instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level professionals who wish to understand both Six Sigma and Lean principles in order to lead significant process improvement projects in their organizations.

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

• Develop a comprehensive understanding of how Lean and Six Sigma methodologies can be integrated for process improvement.
• Gain in-depth knowledge and application skills in the Define, Measure, Analyze, Improve, and Control phases.
• Apply advanced statistical tools for data-driven decision-making and process analysis.
• Lead and manage Lean Six Sigma projects effectively.

This instructor-led, live training in the UAE (online or onsite) is aimed at advanced-level professionals who wish to gain the skills to handle complex Six Sigma projects and take a leadership role in Six Sigma and Lean implementations.

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

• Develop an in-depth understanding of advanced Six Sigma and Lean methodologies and tools.
• Lead complex process improvement projects that align with organizational strategies.
• Perform complex statistical analyses and make data-driven decisions.
• Effectively lead change initiatives and build a culture of continuous improvement.

This instructor-led, live training in the UAE (online or onsite) is aimed at beginner-level professionals who wish to have a deeper understanding of the Six Sigma methodology and its principles and master the DMAIC process.

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

• Gain knowledge beyond the basic principles covered in the White Belt course.
• Master the DMAIC process and learn advanced Six Sigma tools.
• Learn how to effectively contribute to a Six Sigma project team and collaborate with Green and Black Belts.
• Apply Six Sigma methodologies to real-world business processes for improvement.

This instructor-led, live training in the UAE (online or onsite) is aimed at beginner-level professionals who wish to have a basic understanding of the Six Sigma methodology and its principles.

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

• Understand the basics of Six Sigma and learn the DMAIC process.
• Understand the specific roles and responsibilities of a White Belt in the context of a Six Sigma project.
• Learn how to apply Six Sigma principles to identify improvement opportunities and support Six Sigma projects within an organization.

This instructor-led, live training in the UAE (online or onsite) is aimed at scientists who wish to learn and use the Design of Experiments (DoE) to understand the cause-and-effect relationship between multiple factors.

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

• Understand the advantages of designed experiments over other approaches.
• Understand the cause-and-effect relationships and interactions between factors.
• Learn the best practices and guidelines for conducting successful experimentation.

This instructor-led, live training in the UAE (online or onsite) is aimed at anyone who wishes to learn and master the fundamentals of econometric analysis and modeling.

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

• Learn and understand the fundamentals of econometrics.
• Utilize Eviews and risk simulators.

R is a widely-used, open-source environment for statistical computing, data analysis, and graphics. This course provides an introduction to the R programming language for students. It delves into the basics of the language, key libraries, and advanced topics. The curriculum also includes practical applications in advanced data analytics and graphing using real-world datasets.

Audience

Developers / Data Analysts

Duration

3 days

Format

Lectures and Hands-on Sessions

Audience

Analysts, researchers, scientists, graduates, students, and anyone interested in enhancing their ability to conduct statistical analysis using Microsoft Excel.

Course Objectives

This course aims to boost your proficiency with both Excel and statistics, thereby elevating the quality and speed of your work or research.

The curriculum covers the utilization of the Analysis ToolPak in Microsoft Excel, various statistical functions, and fundamental statistical methods. It will also address Excel's limitations and provide strategies to circumvent them.

Data analytics plays a vital role in modern business operations. Throughout this program, we will concentrate on honing practical data analysis skills. Our goal is to equip participants with the ability to provide evidence-based responses to key questions:

What has transpired?

• processing and examining data
• creating insightful data visualizations

What will occur?

• predicting future performance
• assessing forecast accuracy

What actions should be taken?

• transforming data into evidence-driven business decisions
• streamlining processes for optimization

The course can be conducted as a 6-day classroom session or remotely, spread over several weeks, if preferred. We are flexible and can tailor the delivery method to best meet your requirements.

It is projected that unstructured data constitutes over 90 percent of all data, with a significant portion existing as text. This includes blog posts, tweets, social media updates, and other digital content that continually expands this vast dataset.

This instructor-led course focuses on deriving insights and meaning from such data. By leveraging the R programming language and Natural Language Processing (NLP) libraries, we integrate concepts and methodologies from computer science, artificial intelligence, and computational linguistics to algorithmically interpret text data. Data samples are provided in multiple languages based on customer needs.

Upon completion of this training, participants will be equipped to prepare datasets—both large and small—from various sources, and apply appropriate algorithms for analysis and reporting their significance.

Course Format

• The course includes lectures, discussions, extensive hands-on practice, and occasional assessments to evaluate understanding.

This instructor-led live training (online or onsite) is designed for HR professionals and recruitment specialists looking to enhance organizational performance through analytical methods. The course encompasses both qualitative and quantitative approaches, as well as empirical and statistical techniques.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical sessions.

Customization Options

• To request a tailored training session, please contact us to make arrangements.

Audience

Financial analysts, market analysts, managers, and accountants

Course Objectives

Enhance and streamline various types of financial analysis using Microsoft Excel

R is a widely-used programming language in the financial sector. It is employed across various financial applications, from core trading systems to risk management platforms.

During this instructor-led live training session, participants will learn how to leverage R for developing practical solutions to address specific finance-related challenges.

By the conclusion of the course, attendees will be able to:

• Grasp the foundational aspects of the R programming language
• Select and apply appropriate R packages and methodologies to organize, visualize, and analyze financial data from multiple sources (CSV files, Excel spreadsheets, databases, web resources, etc.)
• Create applications that tackle issues such as asset allocation, risk assessment, investment performance analysis, and more
• Debug, integrate, deploy, and optimize R applications effectively

Audience

• Software Developers
• Data Analysts
• Quantitative Analysts (Quants)

Course Format

• The course includes a mix of lectures, discussions, exercises, and extensive hands-on practice.

Note

• This training is designed to address key challenges faced by finance professionals. If you have specific topics, tools, or techniques that you would like us to cover in more detail, please contact us to arrange accordingly.

This instructor-led live training (online or onsite) is designed for HR professionals looking to enhance organizational performance through analytical methods. The course encompasses both qualitative and quantitative approaches, as well as empirical and statistical techniques.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical applications.

Customization Options

• To request a tailored training session, please contact us to make arrangements.

This course delves into advanced concepts in R programming.

Objective:

To become proficient in independently utilizing the SPSS program for advanced applications, including dialog boxes and command language syntax for chosen analytical methods.

Audience:

This course is designed for analysts, researchers, scientists, students, and anyone interested in gaining expertise in using the SPSS package at an advanced level and learning selected statistical models. The training addresses common analysis challenges across various industries.

Audience:

This course is designed for IT professionals seeking solutions to manage and analyze extensive data sets within a distributed system framework.

Goal:

To gain comprehensive expertise in the administration of Hadoop clusters.

This instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level data scientists and statisticians who wish to prepare data, build models, and apply machine learning techniques effectively in their professional domains.

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

• Understand and implement various Machine Learning algorithms.
• Prepare data and models for machine learning applications.
• Conduct post hoc analyses and visualize results effectively.
• Apply machine learning techniques to real-world, sector-specific scenarios.

Big Data encompasses solutions designed for managing and analyzing extensive datasets. Initially developed by Google, these Big Data solutions have advanced significantly and have spurred numerous comparable initiatives, many of which are now offered as open-source options. In the financial sector, R is a widely-used programming language.

Objective:

Participants will be able to analyze large data sets, identify patterns, select the appropriate variables influencing the outcomes, and develop a new model with accurate predictive results.

R is an open-source programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly utilized by managers and data analysts in both corporate environments and academic settings. R offers a broad range of packages specifically tailored for data mining.

R is an open-source, freely available programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly adopted by managers and data analysts in both corporate environments and academic institutions. R offers a broad range of packages specifically tailored for data mining.

R is an open-source, freely available programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly adopted by managers and data analysts within both corporate environments and academic institutions. R offers a broad range of packages specifically tailored for data mining.

This course is intended for people that already have a background in data science and statistics. The explanations given are designed to either serve as a reminder to those that are already familiar with the concepts or inform those with a suitable background.

Audience

Business owners such as marketing managers, product managers, and customer base managers, along with their teams; professionals specializing in customer insights.

Overview

This course covers the entire customer lifecycle, from attracting new customers to managing existing ones for profitability, retaining loyal customers, and understanding why some customers leave. We will use real (though anonymous) data from various sectors including telecommunications, insurance, media, and high tech.

Format

The training is instructor-led over five half-day sessions, featuring both in-class exercises and homework assignments. It can be conducted either in a classroom setting or online.

This course is designed for individuals who are keen on statistical analysis. It offers an introduction to Minitab, enhancing the efficacy and speed of your data analysis while deepening your understanding of statistics.

R is an open-source, freely available programming language designed for statistical computing, data analysis, and graphical representation. It is increasingly adopted by numerous managers and data analysts within corporate settings and academic institutions. R offers a broad range of packages specifically tailored for data mining.

In this instructor-led, live training, participants will learn advanced techniques for Machine Learning with R as they step through the creation of a real-world application.

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

• Understand and implement unsupervised learning techniques
• Apply clustering and classification to make predictions based on real world data.
• Visualize data to quicly gain insights, make decisions and further refine analysis.
• Improve the performance of a machine learning model using hyper-parameter tuning.
• Put a model into production for use in a larger application.
• Apply advanced machine learning techniques to answer questions involving social network data, big data, and more.

R is an open-source programming language designed for statistical computing, data analysis, and graphics. It is increasingly adopted by managers and data analysts in both corporate settings and academic institutions. R appeals to statisticians, engineers, and scientists who may not have extensive computer programming experience due to its user-friendly nature. Its widespread use can be attributed to the growing importance of data mining for diverse objectives such as setting advertisement prices, accelerating drug discovery, or refining financial models. R offers a broad range of packages specifically tailored for data mining.

This course provides an overview of utilizing neural networks to solve practical problems through the use of R-project software.

This course is designed for data scientists and statisticians who already possess foundational R and C++ coding skills and wish to enhance their advanced R programming abilities.

The aim is to provide a practical, advanced R programming course for participants looking to apply these techniques in their professional roles.

Sector-specific examples are incorporated to ensure the training is pertinent to the audience.

This course is a component of the Data Scientist skill set (Domain: Data and Technology).

Organisation – Laboratory work and practical examples using real data

Students will apply Six Sigma principles at the Green Belt level.

This instructor-led, live training in the UAE (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to perform statistical analysis using SPSS to interpret data accurately, run complex statistical tests, and generate meaningful insights.

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

• Navigate the SPSS interface and manage datasets efficiently.
• Perform descriptive and inferential statistical analyses.
• Conduct t-tests, ANOVA, MANOVA, regression, and correlation analyses.
• Apply non-parametric tests, principal component analysis, and factor analysis for advanced data interpretation.

Objective:

Achieving independent proficiency in using SPSS

Target Audience:

This course is designed for analysts, researchers, scientists, students, and anyone else interested in mastering the SPSS software package and gaining knowledge of widely-used data mining techniques.

This course has been designed for leaders who aim to comprehend calculations and analyses rather than perform them, enabling them to select appropriate statistical methods for their organization's strategic planning.

For instance, a potential participant might need to determine the number of samples required before deciding whether to launch a product.

If you require a more comprehensive course that delves into the fundamentals of statistical thinking, consider our 5-day "Statistics for Managers" training program.

This course is designed for individuals seeking foundational statistical skills. It can be customized to focus on specific fields such as market research, biology, manufacturing, public sector analysis, and more.

This training course delves into advanced statistical methods. It elucidates a variety of tools frequently utilized in research, analysis, and forecasting, offering concise theoretical explanations behind the formulas.

The course is not confined to any particular field of study but can be customized if all participants share similar backgrounds and objectives.

Basic computer tools such as Excel and OpenOffice are employed throughout the course.

This course is designed to provide researchers with an in-depth comprehension of the foundational concepts of statistical design and analysis, and their application across various scientific fields.

It includes coverage of probability and statistical methods primarily through practical examples. The training consists of approximately 30% lectures and 70% guided quizzes and lab sessions.

If the course is closed, we can customize the examples and materials to align with a specific field such as psychology, public sector work, biology, genetics, or others.

For open courses, a diverse range of examples is utilized.

While various software tools are employed throughout the course (ranging from Microsoft Excel to SPSS and Statgraphics), the primary emphasis remains on grasping the underlying principles and methodologies that guide research, reasoning, and conclusions.

The course can also be offered in a blended format, incorporating homework and assignments.

Tableau enables individuals to visualize and comprehend data effectively.

Tableau enables individuals to visualize and comprehend data effectively.

The Tidyverse is a suite of flexible R packages designed for data cleaning, processing, modeling, and visualization. Key components include ggplot2, dplyr, tidyr, readr, purrr, and tibble.

During this instructor-led live training session, participants will learn how to manipulate and visualize data using the tools provided by the Tidyverse.

By the end of the course, participants will be able to:

• Analyze data and generate compelling visualizations
• Derive meaningful insights from various sample datasets
• Filter, sort, and summarize data to address exploratory questions
• Create informative line plots, bar charts, and histograms from processed data
• Import and filter data from a variety of sources such as Excel, CSV, and SPSS files

Audience

• Beginners to the R programming language
• Newcomers to data analysis and visualization

Course Format

• The course includes lectures, discussions, exercises, and extensive hands-on practice.

Description: 

This course is tailored for R users aiming to develop web applications without delving into cross-browser HTML, JavaScript, and CSS.

Objective:

It provides an introduction to the fundamental workings of Shiny apps.

It encompasses all frequently utilized input/output/rendering/paneling functions within the Shiny library.

This instructor-led, live training in the UAE (online or onsite) is aimed at intermediate-level data analysts and business professionals who wish to perform time series forecasting and automate data analysis workflows using R.

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

• Understand the fundamentals of forecasting techniques in R.
• Apply exponential smoothing and ARIMA models for time series analysis.
• Utilize the ‘forecast’ package to generate accurate forecasting models.
• Automate forecasting workflows for business and research applications.

Audience

• Managers
• Developers
• Scientists
• Students

Course Format

Online instruction and discussion OR in-person workshops

R is an open-source programming language designed for statistical computing, data analysis, and graphics. It is increasingly utilized by managers and data analysts within corporations and academic institutions. R has also gained popularity among statisticians, engineers, and scientists who may not have extensive computer programming experience but find it user-friendly. Its widespread adoption can be attributed to the growing importance of data mining for various purposes such as setting ad prices, accelerating drug discovery, or refining financial models. R offers a broad range of packages specifically tailored for data mining.

This course focuses on handling objects in R, including importing data, utilizing R packages, creating R functions, and generating insightful graphs. It also covers the analysis of data using common statistical models. The course provides instruction on how to use the R software (https://www.r-project.org) both through command-line operations and within a graphical user interface (GUI).