Online or onsite, instructor-led live Statistics training courses demonstrate through interactive discussion and hands-on practice how to apply Statistic principles to the solving of real-world problems.
Statistics training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Statistics training can be carried out locally on customer premises in Ostrowiec Świętokrzyski or in NobleProg corporate training centers in Ostrowiec Świętokrzyski.
NobleProg -- Your Local Training Provider
Ostrowiec Świętokrzyski
Centrum Biurowo – Konferencyjne, Sandomierska 26A, Ostrowiec Świętokrzyski, Poland, 27-400
The training rooms are spacious, well-lit, and excellently equipped, providing comfortable conditions for ...
The training rooms are spacious, well-lit, and excellently equipped, providing comfortable conditions for participants. Additionally, the building features a ramp and an elevator, facilitating access for individuals with limited mobility and easing the transportation of training equipment. The facility is located just 3.5 kilometers from the city center, allowing for quick and easy access to other urban attractions. Moreover, it is only 600 meters away from the nearest bus stop, making it convenient for participants using public transportation.
This instructor-led, live training in Ostrowiec Świętokrzyski (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 Ostrowiec Świętokrzyski (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 Ostrowiec Świętokrzyski (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 Ostrowiec Świętokrzyski (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 Ostrowiec Świętokrzyski (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.
This instructor-led, live training in Ostrowiec Świętokrzyski (online or onsite) is aimed at data analysts and anyone who is interested to learn how to use and integrate Tableau, Python, R, and SQL for data visualization and analysis.
By the end of this training, participants will be able to:
Perform data analysis using Python, R, and SQL.
Create insights through data visualization with Tableau.
Make data-driven decisions for business operations.
This instructor-led, live training in Ostrowiec Świętokrzyski (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 Ostrowiec Świętokrzyski (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 Ostrowiec Świętokrzyski (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 Ostrowiec Świętokrzyski (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.
This instructor-led, live training in Ostrowiec Świętokrzyski (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.
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
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.
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.
It is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data.
This instructor-led, live course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements.
By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance.
Format of the Course
Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
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.
Audience
Financial or market analysts, managers, accountants
Course Objectives
Facilitate and automate all kinds of financial analysis with Microsoft Excel
This instructor-led, live training in Ostrowiec Świętokrzyski (online or onsite) is aimed at data analysts who wish to program in R for Excel.
By the end of this training, participants will be able to:
Toggle and move data between Excel and R.
Use R Tidyverse and R features for data analytic solutions in Excel.
Extend their data analytical skills by learning R.
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 use R to develop practical applications for solving a number of specific finance related problems.
By the end of this training, participants will be able to:
Understand the fundamentals of the R programming language
Select and utilize R packages and techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
Troubleshoot, integrate deploy and optimize an R application
Audience
Developers
Analysts
Quants
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
Note
This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.
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.
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
This instructor-led, live training in Ostrowiec Świętokrzyski (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.
This instructor-led, live training in Ostrowiec Świętokrzyski (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.
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.
This instructor-led, live training in Ostrowiec Świętokrzyski (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.
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.
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
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
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.
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 instructor-led, live training in Ostrowiec Świętokrzyski (online or onsite) is aimed at data scientists who wish to program in Python and R for KNIME.
By the end of this training, participants will be able to:
Plan, build, and deploy machine learning models in KNIME.
In this instructor-led, live training, participants will learn how to apply machine learning techniques and tools for solving real-world problems in the banking industry. R will be used as the programming language.
Participants first learn the key principles, then put their knowledge into practice by building their own machine learning models and using them to complete a number of live projects.
Audience
Developers
Data scientists
Banking professionals with a technical background
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. 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 apply machine learning techniques and tools for solving real-world problems in the finance industry. R will be used as the programming language.
Participants first learn the key principles, then put their knowledge into practice by building their own machine learning models and using them to complete a number of team projects.
By the end of this training, participants will be able to:
Understand the fundamental concepts in machine learning
Learn the applications and uses of machine learning in finance
Develop their own algorithmic trading strategy using machine learning with R
Audience
Developers
Data scientists
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
Audience
Business owners (marketing managers, product managers, customer base managers) and their teams; customer insights professionals.
Overview
The course follows the customer life cycle from acquiring new customers, managing the existing customers for profitability, retaining good customers, and finally understanding which customers are leaving us and why. We will be working with real (if anonymous) data from a variety of industries including telecommunications, insurance, media, and high tech.
Format
Instructor-led training over the course of five half-day sessions with in-class exercises as well as homework. It can be delivered as a classroom or distance (online) course.
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.
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 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.
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 the fundamentals of R programming as they walk through coding in R using financial examples.
By the end of this training, participants will be able to:
Understand the basics of R programming
Use R to manipulate their data to perform basic financial operations
Audience
Programmers
Finance professionals
IT Professionals
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
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 is for data scientists and statisticians that already have basic R & C++ coding skills and R code and need advanced R coding skills.
The purpose is to give a practical advanced R programming course to participants interested in applying the methods at work.
Sector specific examples are used to make the training relevant to the audience
Shiny is an open source R package that provides a web framework for building interactive web applications using R.
In this instructor-led, live training, participants will learn how to combine data science and web development using Shiny, R, and HTML.
By the end of this training, participants will be able to:
Build interactive web applications with R using Shiny
Audience
Data scientists
Web developers
Statisticians
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
This instructor-led, live training in Ostrowiec Świętokrzyski (online or onsite) is aimed at data analysts who wish to use Stata and R to analyze big data for statistical analysis.
By the end of this training, participants will be able to:
Create statistic models for predicting key interest variables and events.
Generate descriptive visualizations, summary tables, frequencies, and more.
Manage and structure large databases to preapare for data analysis.
This instructor-led, live training in Ostrowiec Świętokrzyski (online or onsite) is aimed at data scientists who wish to program in R for Tableau.
By the end of this training, participants will be able to:
Implement Tableau analytics with R.
Return values to Tableau with learning algorithms in R.
Structure and visualize R functions in Tableau.
Make data driven decisions for business operations.
Description:
This is a course designed to teach R users how to create web apps without needing to learn cross-browser HTML, Javascript, and CSS.
Objective:
Covers the basics of how Shiny apps work.
Covers all commonly used input/output/rendering/paneling functions from the Shiny library.
Audience
This course has been created for analysts, forecasters wanting to introduce or improve forecasting which can be related to sale forecasting, economic forecasting, technology forecasting, supply chain management and demand or supply forecasting.
Description
This course guides delegates through series of methodologies, frameworks and algorithms which are useful when choosing how to predict the future based on historical data.
It uses standard tools like Microsoft Excel or some Open Source programs (notably R project).
The principles covered in this course can be implemented by any software (e.g. SAS, SPSS, Statistica, MINITAB ...)
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
Audience:
The course is intended for IT specialists looking for a solution to store and process large data sets in a distributed system environment
Goal:
Deep knowledge on Hadoop cluster administration.
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.
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.
Data Science in business plays a key role in using data to make better business decisions. and includes data analysis, data collection and cleaning, examining data in search of patterns, relationships and trends, which allows for a better understanding of business activities, forecasting and modeling, as well as optimization of business processes. Data Science contributes to business transformation by using powerful data analysis tools and techniques. It allows for a better understanding of customers, streamlining business processes, improving marketing strategies and making more informed decisions, which in turn may lead to an increase in the efficiency and competitiveness of the company.
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.
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.
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.
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
This instructor-led, live training in Ostrowiec Świętokrzyski (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.
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.
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.
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...
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)
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.
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 covers the manipulation of objects in R including reading data, accessing R packages, writing R functions, and making informative graphs. It includes analyzing data using common statistical models. The course teaches how to use the R software (https://www.r-project.org) both on a command line and in a graphical user interface (GUI).
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Testimonials (25)
Well thought out and high grade planning materials.
Andrew - Office of Projects Victoria - Department of Treasury & Finance
Course - Forecasting with R
the clarity with which he explained the entire course, as well as the willingness to return to the syllabus when necessary
Carlos Eloy - AMERICAN EXPRESS COMPANY MEXICO
Course - Data Analytics With R
Machine Translated
Wasn't boring, the trainer could keep the attention, the topics were covered in depth.
Marta - Ministerstwo Zdrowia
Course - Advanced R Programming
I learned new things so that is a good point
Daria - LKQ Polska Sp. z o. o.
Course - Analysing Financial Data in Excel
Trenerka w jasny i usystematyzowany sposób prowadziła zajęcia, będąc przy tym bardzo elastyczną. Posiadała ogromną wiedzę, którą potrafiła się podzielić i cierpliwie tłumaczyła, jeśli pojawiły się jakieś wątpliwości albo kod nie działał. Mam nadzieję, że spotkamy się jeszcze na jakimś kursie :)
Anna - Uniwersytet Jagielloński Collegium Medicum
Course - Introduction to R
We were using road accident data for practicals
Maphahamiso Ralienyane - Road Safety Department
Course - Statistical Analysis using SPSS
I liked the excercises and how great it was to follow
Elizabeth Seed - Terumo Aortic
Course - Minitab for Statistical Data Analysis
At the end of the class, we had a great overview of the language, we were provided tools to continue learning and were provided suggestions on how to continue learning. We covered AI/ML information.
Victor Prado - Global Knowledge Network Training Ltd
Course - R
Sposób prowadzenia szkolenia
Andrzej Zaczek - Fundacja DKMS
Course - Excel For Statistical Data Analysis
duża wiedza, praca na rzeczywistych danych
Tomasz Popiołek - Orange Szkolenia Sp. z o.o.
Course - Data Science w biznesie
Mr Andrew easily understood and responded so well to participants' answers.
Junaidah Ahmad - GAS MALAYSIA DISTRIBUTION SDN BHD
Course - Market Forecasting
Forma przekazania wiedzy poprzez dokładne wyjaśnienie zagadnienia.
Katarzyna Stańczak - Mowi Poland SA
Course - Data Mining and Analysis
The exercises.
Elena Velkova - CEED Bulgaria
Course - Predictive Modelling with R
Good detail on what R is used for and how to start using it right away
Hoss Shenassa - Trimac Management Services LP
Course - Introduction to R with Time Series Analysis
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 - Birmingham City University
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
dużo ćwiczeń, które bezpośrednio mogę wykorzystać w mojej pracy
Alior Bank S.A.
Course - Sieci Neuronowe w R
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
The subject matter and the pace were perfect.
Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course - Programming with Big Data in R
I really was benefit from the real life practical examples.
Wioleta
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
otwartość, dobra atmosfera, współpraca z prowadzącym
PAA
Course - Mathematica - wprowadzenie, wizualizacja i prezentacja danych
I genuinely enjoyed the many hands-on sessions.
Jacek Pieczątka
Course - Administrator Training for Apache Hadoop
Very tailored to needs.
Yashan Wang
Course - Data Mining with R
The trainer was so knowledgeable and included areas I was interested in.
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