
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
The material covered was interesting and the trainer was knowledgeable.
Neghat Khan
Course: Modelling and Forecasting for Government
Good rapport with the audience, good & accessible explanation/presentation and he relates 'tech' stuff to real life examples which makes things easier to understand.
Ray Rusike
Course: Modelling and Forecasting for Government
I was benefit from the excellent knowledge of the trainer, useful examples.
Jonathan Harrison
Course: Modelling and Forecasting for Government
The topics were relevant to my role and I will be able to use this immediately in my work and in the future.
Rani Nandra
Course: Modelling and Forecasting for Government
He was very informative and helpful.
Pratheep Ravy
Course: Predictive Modelling with R
I genuinely enjoyed the trainer's helping.
Urszula Kuza
Course: Tableau Advanced
I get answers on all my questions.
Natalia Gladii
Course: Data Analytics With R
The training was adaptable and personalized to our needs.
Dominique Soulie
Course: Minitab for Statistical Data Analysis
I liked the exercises as it's the only way to learn, by repetition.
David Rushe
Course: Tableau Advanced
The trainer was so knowledgeable and included areas I was interested in.
Mohamed Salama
Course: Data Mining & Machine Learning with R
Very tailored to needs.
Yashan Wang
Course: Data Mining with R
I genuinely enjoyed working 1:1 with Gunner.
Bryant Ives
Course: Introduction to R
A very coherent and systematic refresher on forecasting models and useful applications.
Marco D'Alterio
Course: Modelling and Forecasting for Government
I enjoyed the stats refresher and using software for exercises.
Rabeeah Shah
Course: Modelling and Forecasting for Government
I like the exercises done.
Nour Assaf
Course: Data Mining and Analysis
The hands-on exercise and the trainer capacity to explain complex topics in simple terms.
youssef chamoun
Course: Data Mining and Analysis
I learned about a lot of techniques I didn't know about before.
Alexandra Torok
Course: Modelling and Forecasting for Government
The information given was interesting and the best part was towards the end when we were provided with Data from Durex and worked on Data we are familiar with and perform operations to get results.
Jessica Chaar
Course: Data Mining and Analysis
I mostly liked the trainer giving real live Examples.
Simon Hahn
Course: Administrator Training for Apache Hadoop
I genuinely enjoyed the big competences of Trainer.
Grzegorz Gorski
Course: Administrator Training for Apache Hadoop
I genuinely enjoyed the many hands-on sessions.
Jacek Pieczątka
Course: Administrator Training for Apache Hadoop
I liked the new insights in deep machine learning.
Josip Arneric
Course: Neural Network in R
We gained some knowledge about NN in general, and what was the most interesting for me were the new types of NN that are popular nowadays.
Tea Poklepovic
Course: Neural Network in R
I mostly enjoyed the graphs in R :))).
Faculty of Economics and Business Zagreb
Course: Neural Network in R
I genuinely was benefit from the flexibility of the trainer.
Irina Ostapenko
Course: Statistics Level 2
The flexible and friendly style. Learning exactly what was useful and relevant for me.
Jenny Tickner
Course: Advanced 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
Learning how to use excel properly.
Torin Mitchell
Course: Data and Analytics - from the ground up
The way the trainer made complex subjects easy to understand.
Adam Drewry
Course: Data and Analytics - from the ground up
Detailed and comprehensive instruction given by experienced and clearly knowledgeable expert on the subject.
Justin Roche
Course: Data and Analytics - from the ground up
Tamil is very knowledgeable and nice person, I have learned from him a lot.
Aleksandra Szubert
Course: Data and Analytics - from the ground up
I liked the first session. Very intensive and quick.
Digital Jersey
Course: Data and Analytics - from the ground up
I mostly liked the patience of Tamil.
Laszlo Maros
Course: Data and Analytics - from the ground up
I really was benefit from the real life practical examples.
Wioleta (Vicky) Celinska-Drozd
Course: Data and Analytics - from the ground up
A lot of knowledge - theoretical and practical.
Anna Alechno
Course: Forecasting with R
I genuinely liked his knowledge and practical examples.
Irina Tulgara
Course: Forecasting with R
Overview and understanding how big the topic is.
British American Shared Services Europe BAT GBS Finance, WER/Centre/EEMEA
Course: Forecasting with R
Hands on examples were the most helpful.
Sean Kaukas
Course: Introduction to R
I enjoyed the 2nd day we did lots of examples of gauge R&R.
Vascutek Ltd
Course: Minitab for Statistical Data Analysis
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
Statistics Subcategories in Lithuania
Statistics Course Outlines in Lithuania
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.
Audience
Developers / data analytics
Duration
3 days
Format
Lectures and Hands-on
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.
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](https://www.nobleprog.co.uk/instructor-led-online-training-courses) over a period of weeks if preferred. We can work with you to deliver the course to best suit your needs.
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
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.
Financial or market analysts, managers, accountants
Course Objectives
Facilitate and automate all kinds of financial analysis with Microsoft Excel
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.
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.
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.
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)
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.
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.
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
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.
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.
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.
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.
Its versatility makes it useful not only for doing basic academic calculations but also completing complicated calculations, like programming or numerical data presentations.
Mathematica integrates software engines doing numerical andsymbolic computation, as well as graph analysis software, programming language, document formats and the possibility of publishing your work results.
Thanks to multiplicity of its functions it’s a priceless tool for mathematicians, physicists, biologists, chemists, financial analysts, sociologists and many more professions that deal with data.
Participants will gain skills to
- perform calculations efficiently
- understanding program commands
- creating text documents
- building charts and graphs
- data presentations
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
Last Updated: