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 trainings in Lithuania can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Testimonials
I genuinely liked the exercises - use of Minicab.
Vascutek Ltd
Course: Minitab for Statistical Data Analysis
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
I really enjoyed the introduction of new packages.
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
The tutor, Mr. Michael An, interacted with the audience very well, the instruction was clear. The tutor also go extent to add more information based on the requests from the students during the training.
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
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
Good overview of R and good range of topics. Trainer was happy to answer all questions.
Symphony EYC
Course: R
I really enjoyed the knowledge of the trainer.
Stephanie Seiermann
Course: 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
It was very hands-on, we spent half the time actually doing things in Clouded/Hardtop, running different commands, checking the system, and so on. The extra materials (books, websites, etc. .) were really appreciated, we will have to continue to learn. The installations were quite fun, and very handy, the cluster setup from scratch was really good.
Ericsson
Course: Administrator Training for Apache Hadoop
I really liked the exercises on time series modeling.
Teleperformance
Course: Data Analytics With R
New tool which is “R” and I find it interesting to know the existence of such tool for data analysis.
Michael Lopez - Teleperformance
Course: Data Analytics With R
The tool was interesting and I see the use. I would like to learn about more about it.
Teleperformance
Course: Data Analytics With R
The training felt very personal and customised to what I wanted out of it. It was so non judgemental that I felt comfortable in asking whatever questions I needed to, and the trainer was able to competently answer all my questions. It was a very good overview of useful statistical techniques and there was a good balance between statistical theory and how to use minitab.
Cambridge Consultants
Course: Minitab for Statistical Data Analysis
Lot of hands-on exercises.
Ericsson
Course: Administrator Training for Apache Hadoop
Ambari management tool. Ability to discuss practical Hadoop experiences from other business case than telecom.
Ericsson
Course: Administrator Training for Apache Hadoop
I generally liked the trainer Knowledge.
SAP Business Objects
Course: Statistics Level 1
I mostly was benefit from learning about Gantt charts.
Sarah Drummond - Siemens Gamesa c/o Hemsley Fraser
Course: Tableau Advanced
the matter was well presented and in an orderly manner.
Marylin Houle - Ivanhoe Cambridge
Course: Introduction to R with Time Series Analysis
The fact that we had the time to cover some useful extras.
Alina Vishniakova - TUI Business Services GmbH
Course: Statistics Level 1
He really explained everything well and used examples.
royal bank of Canada
Course: R
The trainer listened to the needs of his audience as best as possible and we were able to train relevant to our needs, Costas prepared material specifically around questions asked on the basic training for the advanced training, a lot of effort and work had been put in and it was appreciated.
Chloe Horton - Siemens Gamesa c/o Hemsley Fraser
Course: Tableau Advanced
I enjoyed the self-learning through exercises and the tips and shortcuts shared.
Competition Bureau
Course: R for Data Analysis and Research
I really enjoyed the all the best.
Halil polat - Amazon Development Center Poland Sp. z o.o.
Course: Data Mining and Analysis
The trainer concentrated on the key topics.
Amazon Development Center Poland Sp. z o.o.
Course: Data Mining and Analysis
Expertise and huge knowledge of the trainer.
Amazon Development Center Poland Sp. z o.o.
Course: Data Mining and Analysis
I was benefit from the guidance and sharing life examples + answering all questions.
Marta Melloch - Amazon Development Center Poland Sp. z o.o.
Course: Data Mining and Analysis
I was benefit from the detailed notes to keep and work through after the course.
Public Health Wales NHS Trust
Course: Introduction to Data Visualization with Tidyverse and 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
I was benefit from the good examples and opportunity to follow along.
Environmental and Climate Change Canada
Course: Foundation R
I genuinely enjoyed the hands passed exercises.
Yunfa Zhu - Environmental and Climate Change Canada
Course: Foundation R
The trainer, the food, and the space were all great.
Canada Revenue Agency
Course: R
I like actually writing code with sample data and annotating the script for future reference.
Canada Revenue Agency
Course: R
The pre-made scripts used for training material was very useful. The interactive training allowed for a clear understanding of each topic.
Canada Revenue Agency
Course: R
The trainer was very concern about individual understanding.
Muhammad Surajo Sanusi - Birmingham City University
Course: Foundation R
Excellent presentation and it gives me confidence to build on knowledge gained.
Birmingham City University
Course: Foundation R
Background knowledge and 'provenance' of trainer.
Francis McGonigal - Birmingham City University
Course: Foundation R
Resources
Hafiz Rana - Birmingham City University
Course: Foundation R
Good explanations on how we do things
Birmingham City University
Course: Foundation R
I feel more confident with coding now. I've never done it before but now I understand that it's not rocket science and I can do it when necessary.
Anna Yartseva - Birmingham City University
Course: Foundation R
that i was getting my all answers and knowledge i want.
Ismail Ahli - Dubai Civil Aviation Authority
Course: R for Statistical Analysis
Modeling and how to fit the data to model
USDA
Course: R for Data Analysis and Research
The remote classroom setting worked very well
Trimac Management Services LP
Course: Introduction to R with Time Series Analysis
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
The many practical examples / assignments that we went through were great. For me, I learn better by seeing examples and applying them elsewhere. The use of real data and applying what was taught against it was extremely valuable. Michaels PowerPoint presentations and his ability to work through each solution was invaluable.
Trimac Management Services LP
Course: Introduction to R with Time Series Analysis
The trainer was very good. He presented the material in a really accessible way.
Hydrock
Course: Introduction to Data Visualization with Tidyverse and R
The exercises.
Elena Velkova - CEED Bulgaria
Course: Predictive Modelling with R
Practical exercises with R were very helpful.
CEED Bulgaria
Course: Predictive Modelling with R
Examples
Saudi Health Council
Course: Introduction to R
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
Steve was willing to answer every questions and worked diligently to address any individual concerns or technical issues as they arose in the class. He also did a great job of presenting the technical details in a way that made it less intimidating to even the least tech savvy people in the room. Personally, learning about some useful shortcuts in Excel that I didn't know about will certainly improve my overall workflow when using Excel in the future! I am so appreciative of those little details that I was exposed to during the two-day training.
Alan Gonzalez - Queens College, CUNY
Course: Excel For Statistical Data Analysis
Statistics Subcategories in Lithuania
Statistics Course Outlines in Lithuania
Course Name
Duration
Overview
Course Name
Duration
Overview
7 hours
Overview
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
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
14 hours
Overview
R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.
21 hours
Overview
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.
21 hours
Overview
This instructor-led, live training in Lithuania (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.
21 hours
Overview
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 basics of financial trading as they step through building and implementing basic trading strategies and actions in R using quantstrat.
By the end of this training, participants will be able to:
- Understand the fundamental concepts in trading
- Create and implement their first trading strategy using R
- Analyze the performance of their strategy using R
Audience
- Programmers
- Finance professionals
- IT Professionals
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn the basics of financial trading as they step through building and implementing basic trading strategies and actions in R using quantstrat.
By the end of this training, participants will be able to:
- Understand the fundamental concepts in trading
- Create and implement their first trading strategy using R
- Analyze the performance of their strategy using R
Audience
- Programmers
- Finance professionals
- IT Professionals
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
28 hours
Overview
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.
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.
28 hours
Overview
R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.
21 hours
Overview
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
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
21 hours
Overview
R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.
14 hours
Overview
This course is an introduction to applying neural networks in real world problems using R-project software.
7 hours
Overview
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
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
14 hours
Overview
This course is part of the Data Scientist skill set (Domain: Data and Technology)
14 hours
Overview
Organization – Lab work and practical examples on real data
14 hours
Overview
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
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
14 hours
Overview
This instructor-led, live training in Lithuania (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.
28 hours
Overview
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
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
14 hours
Overview
Goal:
Learning to work with SPSS at the level of independence
The addressees:
Analysts, researchers, scientists, students and all those who want to acquire the ability to use SPSS package and learn popular data mining techniques.
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.
21 hours
Overview
The objective of the course is to enable participants to gain a mastery of the fundamentals of statistical and econometric modelling.
7 hours
Overview
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.
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.
14 hours
Overview
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...
28 hours
Overview
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 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)
35 hours
Overview
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.
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.
35 hours
Overview
This instructor-led, live training in Lithuania (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.
14 hours
Overview
This instructor-led, live training in Lithuania (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.
14 hours
Overview
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.
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.
14 hours
Overview
Tableau helps people see and understand data.
7 hours
Overview
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
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
Upcoming Statistics Courses in Lithuania
2020-08-24 09:30:00
14 hours
2020-09-08 09:30:00
14 hours
2020-10-14 09:30:00
14 hours
2020-12-03 09:30:00
14 hours
2021-01-25 09:30:00
14 hours
Other countries
Consulting in Lithuania
Online Statistics courses, Weekend Statistics courses, Evening Statistics training, Statistics boot camp, Statistics instructor-led, Weekend Statistics training, Evening Statistics courses, Statistics coaching, Statistics instructor, Statistics trainer, Statistics training courses, Statistics classes, Statistics on-site, Statistics private courses, Statistics one on one training
.png "european space agency (esa)")
.jpg "procter & gamble (p&g)")
.jpg "american international group (aig)")
.png "european central bank (ecb)")
.jpg "european molecular biology laboratory (embl)")
