Explore Our Courses

Design for Six Sigma (DFSS)

 21 Hours
This instructor-led, live training in the UK (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.
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Six Sigma LEAN Yellow Belt

 14 Hours
This instructor-led, live training in the UK (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.
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Six Sigma DMAIC Black Belt

 21 Hours
This instructor-led, live training in the UK (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.
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Six Sigma LEAN Black Belt

 21 Hours
This instructor-led, live training in the UK (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.
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Six Sigma DMAIC Green Belt

 21 Hours
This instructor-led, live training in the UK (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.
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Six Sigma LEAN Green Belt

 21 Hours
This instructor-led, live training in the UK (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.
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Six Sigma Yellow Belt

 14 Hours
This instructor-led, live training in the UK (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.
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Six Sigma White Belt

 14 Hours
This instructor-led, live training in the UK (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.
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Design of Experiments (DoE)

 7 Hours
This instructor-led, live training in the UK (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.
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Econometrics: Eviews and Risk Simulator

 21 Hours
This instructor-led, live training in the UK (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.
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Data Analytics With R

 21 Hours
R is a very popular, open source environment for statistical computing, data analytics and graphics. This course introduces R programming language to students.  It covers language fundamentals, libraries and advanced concepts.  Advanced data analytics and graphing with real world data. Audience Developers / data analytics Duration 3 days Format Lectures and Hands-on
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Excel For Statistical Data Analysis

 14 Hours
Audience Analysts, researchers, scientists, graduates and students and anyone who is interested in learning how to facilitate statistical analysis in Microsoft Excel. Course Objectives This course will help improve your familiarity with Excel and statistics and as a result increase the effectiveness and efficiency of your work or research. This course describes how to use the Analysis ToolPack in Microsoft Excel, statistical functions and how to perform basic statistical procedures. It will explain what Excel limitation are and how to overcome them.
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Data and Analytics - from the ground up

42 Hours
Data analytics is a crucial tool in business today. We will focus throughout on developing skills for practical hands on data analysis. The aim is to help delegates to give evidence-based answers to questions: What has happened?
  • processing and analyzing data
  • producing informative data visualizations
What will happen?
  • forecasting future performance
  • evaluating forecasts
What should happen?
  • turning data into evidence-based business decisions
  • optimizing processes
The course itself can be delivered either as a 6 day classroom course or remotely over a period of weeks if preferred. We can work with you to deliver the course to best suit your needs.
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Talent Acquisition Analytics

 14 Hours
This instructor-led, live training (online or onsite) is aimed at HR professionals and recruitment specialists who wish to use analytical methods improve organisational performance. This course covers qualitative as well as quantitative, empirical and statistical approaches.Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
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Analysing Financial Data in Excel

 14 Hours
Audience Financial or market analysts, managers, accountants Course Objectives Facilitate and automate all kinds of financial analysis with Microsoft Excel
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HR Analytics for Public Organisations

 14 Hours
This instructor-led, live training (online or onsite) is aimed at HR professionals who wish to use analytical methods improve organisational performance. This course covers qualitative as well as quantitative, empirical and statistical approaches.Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
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Advanced Statistics using SPSS Predictive Analytics Software

 28 Hours
Goal:Mastering the skill work independently with the program SPSS for advanced use, dialog boxes, and command language syntax for the selected analytical techniques.The addressees:Analysts, researchers, scientists, students and all those who want to acquire the ability to use SPSS package and advanced level and learn the selected statistical models. Training takes universal analysis problems and it is dedicated to a specific industry
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Administrator Training for Apache Hadoop

 35 Hours
Audience:The course is intended for IT specialists looking for a solution to store and process large data sets in a distributed system environmentGoal:Deep knowledge on Hadoop cluster administration.
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Applied Machine Learning

 14 Hours
This training course is for people that would like to apply Machine Learning in practical applications. Audience This course is for data scientists and statisticians that have some familiarity with statistics and know how to program R (or Python or other chosen language). The emphasis of this course is on the practical aspects of data/model preparation, execution, post hoc analysis and visualization. The purpose is to give practical applications to Machine Learning to participants interested in applying the methods at work. Sector specific examples are used to make the training relevant to the audience.
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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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Introduction to R with Time Series Analysis

 21 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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Statistics and Probabilistic Programming in Julia

 21 Hours
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. 
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Mathematica - introduction, visualization and presentation of data

 14 Hours
The "Mathematica - introduction, visualization and presentation of data" training is aimed at participants with basic mathematical knowledge. Mathematica, as a powerful mathematical engine, enables effective calculations, creating text documents, building charts and presenting data. Participants will gain practical skills in working with Mathematica, used, among others, in mathematics, physics, biology, financial analysis and other fields.
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Minitab for Statistical Data Analysis

 14 Hours
The course is aimed at anyone interested in statistical analysis. It provides familiarity with Minitab and will increase the effectiveness and efficiency of your data analysis and improve your knowledge of statistics.
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R

 21 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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R for Statistical Analysis

 14 Hours
Organization – Lab work and practical examples on real data
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Scilab

 14 Hours
Scilab is a well-developed, free, and open-source high-level language for scientific data manipulation. Used for statistics, graphics and animation, simulation, signal processing, physics, optimization, and more, its central data structure is the matrix, simplifying many types of problems compared to alternatives such as FORTRAN and C derivatives. It is compatible with languages such as C, Java, and Python, making it suitable as for use as a supplement to existing systems. In this instructor-led training, participants will learn the advantages of Scilab compared to alternatives like Matlab, the basics of the Scilab syntax as well as some advanced functions, and interface with other widely used languages, depending on demand. The course will conclude with a brief project focusing on image processing. By the end of this training, participants will have a grasp of the basic functions and some advanced functions of Scilab, and have the resources to continue expanding their knowledge. Audience
  • Data scientists and engineers, especially with interest in image processing and facial recognition
Format of the course
  • Part lecture, part discussion, exercises and intensive hands-on practice, with a final project
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Six Sigma with Minitab

 14 Hours
This instructor-led, live training in the UK (online or onsite) is aimed at data analysts who wish to apply Minitab statistical analysis to Six Sigma projects. By the end of this training, participants will be able to:
  • Use Minitab for performing advanced statistical analysis.
  • Apply Six Sigma methodology to specific projects.
  • Gain knowledge on Six Sigma projects across industries.
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Statistical Analysis using SPSS

 21 Hours
SPSS is software for editing and analyzing data.
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Statistics with SPSS Predictive Analytics Software

 14 Hours
Goal:Learning to work with SPSS at the level of independenceThe 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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Statistical Thinking for Decision Makers

 7 Hours
This course has been created for decision makers whose primary goal is not to do the calculation and the analysis, but to understand them and be able to choose what kind of statistical methods are relevant in strategic planning of the organization. For example, a prospect participant needs to make decision how many samples needs to be collected before they can make the decision whether the product is going to be launched or not. If you need longer course which covers the very basics of statistical thinking have a look at 5 day "Statistics for Managers" training.
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Statistics Level 1

 14 Hours
This course has been created for people who require general statistics skills. This course can be tailored to a specific area of expertise like market research, biology, manufacturing, public sector research, etc...
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Statistics Level 2

 28 Hours
This training course covers advanced statistics. It explains most of the tools commonly used in research, analysis and forecasting. It provides short explanations of the theory behind the formulas.This course does not relate to any specific field of knowledge, but can be tailored if all the delegates have the same background and goals.Some basic computer tools are used during this course (notably Excel and OpenOffice)
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Statistics for Researchers

 35 Hours
This course aims to give researchers an understanding of the principles of statistical design and analysis and their relevance to research in a range of scientific disciplines.It covers some probability and statistical methods, mainly through examples. This training contains around 30% of lectures, 70% of guided quizzes and labs.In the case of closed course we can tailor the examples and materials to a specific branch (like psychology tests, public sector, biology, genetics, etc...)In the case of public courses, mixed examples are used.Though various software is used during this course (Microsoft Excel to SPSS, Statgraphics, etc...) its main focus is on understanding principles and processes guiding research, reasoning and conclusion.This course can be delivered as a blended course i.e. with homework and assignments.
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Tableau Advanced

 14 Hours
Tableau helps people see and understand data.
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Tableau Intermediate Training Course

 14 Hours
Tableau helps people see and understand data.
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Data Science: Analysis and Presentation

 7 Hours
The Wolfram System's integrated environment makes it an efficient tool for both analyzing and presenting data. This course covers aspects of the Wolfram Language relevant to analytics, including statistical computation, visualization, data import and export and automatic generation of reports.
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Introduction to Data Visualization with Tidyverse and R

 7 Hours
The Tidyverse is a collection of versatile R packages for cleaning, processing, modeling, and visualizing data. Some of the packages included are: ggplot2, dplyr, tidyr, readr, purrr, and tibble. In this instructor-led, live training, participants will learn how to manipulate and visualize data using the tools included in the Tidyverse. By the end of this training, participants will be able to:
  • Perform data analysis and create appealing visualizations
  • Draw useful conclusions from various datasets of sample data
  • Filter, sort and summarize data to answer exploratory questions
  • Turn processed data into informative line plots, bar plots, histograms
  • Import and filter data from diverse data sources, including Excel, CSV, and SPSS files
Audience
  • Beginners to the R language
  • Beginners to data analysis and data visualization
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Advanced R

 14 Hours
This course covers advanced topics in R programming.
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Algorithmic Trading with Python and R

 14 Hours
This instructor-led, live training in the UK (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.By the end of this training, participants will be able to:
  • Employ algorithms to buy and sell securities at specialized increments rapidly.
  • Reduce costs associated with trade using algorithmic trading.
  • Automatically monitor stock prices and place trades.
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Anomaly Detection with Python and R

 14 Hours
This instructor-led, live training in the UK (online or onsite) is aimed at data scientists and data analysts who wish to program in R and Python for outlier detection. By the end of this training, participants will be able to:
  • Identify whether data is an anomaly or is an expected value.
  • Implement algorithms for anomaly detection.
  • Use various techniques and methods to detect anomalies.
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Programming with Big Data in R

 21 Hours
Big Data is a term that refers to solutions destined for storing and processing large data sets. Developed by Google initially, these Big Data solutions have evolved and inspired other similar projects, many of which are available as open-source. R is a popular programming language in the financial industry.
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R Fundamentals

 21 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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Cluster Analysis with R and SAS

 14 Hours
This instructor-led, live training in the UK (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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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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Deep Learning for Finance (with R)

 28 Hours
Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks. R is a popular programming language in the financial industry. It is used in financial applications ranging from core trading programs to risk management systems. In this instructor-led, live training, participants will learn how to implement deep learning models for finance using R as they step through the creation of a deep learning stock price prediction model. By the end of this training, participants will be able to:
  • Understand the fundamental concepts of deep learning
  • Learn the applications and uses of deep learning in finance
  • Use R to create deep learning models for finance
  • Build their own deep learning stock price prediction model using R
Audience
  • Developers
  • Data scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Deep Learning for Banking (with R)

 28 Hours
Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks. R is a popular programming language in the financial industry. It is used in financial applications ranging from core trading programs to risk management systems. In this instructor-led, live training, participants will learn how to implement deep learning models for banking using R as they step through the creation of a deep learning credit risk model. By the end of this training, participants will be able to:
  • Understand the fundamental concepts of deep learning
  • Learn the applications and uses of deep learning in banking
  • Use R to create deep learning models for banking
  • Build their own deep learning credit risk model using R
Audience
  • Developers
  • Data scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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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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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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Forecasting with R

 14 Hours
This course allows delegate to fully automate the process of forecasting with R
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R for Data Analysis and Research

7 Hours
Audience
  • managers
  • developers
  • scientists
  • students
Format of the course on-line instruction and discussion OR face-to-face workshops
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Testimonials(25)

Many examples and exercises related to the topic of the training.

Tomasz - Ministerstwo Zdrowia

Course - Advanced R Programming

the trainer had patience, and was eager to make sure we all understood the topics, the classes were fun to attend

Mamonyane Taoana - Road Safety Department

Course - Statistical Analysis using SPSS

Weronika created a really friendly, informal atmosphere. The training involved a lot of useful knowledge transfer, technical skills exercises and theory, as well as best practices and guidance on how to handle our own data.

Julia Kuczma - DLA Piper GSC Poland Sp. z o.o.

Course - Tableau Intermediate Training Course

Day 1 and Day 2 were really straight forward for me and really enjoyed that experience.

Mareca Sithole - Africa Health Research Institute

Course - R Fundamentals

The tips for many of the functions that the trainer presented, which we can easily remember and implement in our future work

Emilija Stoilova - EPFL HBP PCO

Course - Analysing Financial Data in Excel

Machine learning, python, data manipulation

Siphelo Mapolisa - University Of South Africa

Course - Data Science: Analysis and Presentation

1.The presentation style of Mr. Andrew, engaging with the style of audience.

MUHAMMAD ZAID SALMAN - GAS MALAYSIA DISTRIBUTION SDN BHD

Course - Market Forecasting

The fact he had dif excel and data sheets with exercises for us to do.

Deepakie Singh Sodhi - Queens College, CUNY

Course - Excel For Statistical Data Analysis

that i was getting my all answers and knowledge i want.

Ismail Ahli - Dubai Civil Aviation Authority

Course - R for Statistical Analysis

I genuinely enjoyed the hands passed exercises.

Yunfa Zhu - Environmental and Climate Change Canada

Course - Foundation R

The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.

Rhian Hughes - Public Health Wales NHS Trust

Course - Introduction to Data Visualization with Tidyverse and R

The fact that we had the time to cover some useful extras.

Alina Vishniakova - TUI Business Services GmbH

Course - Statistics Level 1

the matter was well presented and in an orderly manner.

Marylin Houle - Ivanhoe Cambridge

Course - Introduction to R with Time Series Analysis

It was very informative and professionally held. Wojteks knowledge level was so advanced that he could basically answer any question and he was willing to put effort into fitting the training to my personal needs.

Sonja Steiner - BearingPoint GmbH

Course - R Programming for Data Analysis

I really enjoyed the knowledge of the trainer.

Stephanie Seiermann

Course - R

Michael the trainer is very knowledgeable and skillful about the subject of Big Data and R. He is very flexible and quickly customize the training meeting clients' need. He is also very capable to solve technical and subject matter problems on the go. Fantastic and professional training!.

Xiaoyuan Geng - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada

Course - Programming with Big Data in R

A lot of knowledge - theoretical and practical.

Anna Alechno

Course - Forecasting with R

I enjoyed the Excel sheets provided having the exercises with examples. This meant that if Tamil was held up helping other people, I could crack on with the next parts.

Luke Pontin

Course - Data and Analytics - from the ground up

The flexible and friendly style. Learning exactly what was useful and relevant for me.

Jenny

Course - Advanced R

I genuinely was benefit from the flexibility of the trainer.

Irina Ostapenko

Course - Statistics Level 2

I liked the new insights in deep machine learning.

Josip Arneric

Course - Neural Network in R

I mostly liked the trainer giving real live Examples.

Simon Hahn

Course - Administrator Training for Apache Hadoop

I like the exercises done.

Nour Assaf

Course - Data Mining and Analysis

I genuinely enjoyed working 1:1 with Gunner.

Bryant Ives

Course - Introduction to R

Very tailored to needs.

Yashan Wang

Course - Data Mining with R

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