Statistics Training Courses

Statistics Training Courses

Τοπικά, καθοδηγούμενα από εκπαιδευτές Στατιστικά μαθήματα κατάρτισης καταδεικνύουν μέσω διαδραστικής συζήτησης και πρακτικής πρακτικής πώς να εφαρμόζουν τις Στατιστικές αρχές στην επίλυση πραγματικών προβλημάτων. Η κατάρτιση στα στατιστικά στοιχεία είναι διαθέσιμη ως "επιτόπου ζωντανή εκπαίδευση" ή "μακρινή ζωντανή κατάρτιση". Η επιτόπια κατάρτιση σε πραγματικό χρόνο μπορεί να πραγματοποιηθεί σε τοπικό επίπεδο στις εγκαταστάσεις του πελάτη Ελλάδα ή σε εταιρικά κέντρα κατάρτισης NobleProg στο Ελλάδα . Η απομακρυσμένη ζωντανή προπόνηση πραγματοποιείται μέσω μιας διαδραστικής, απομακρυσμένης επιφάνειας εργασίας. NobleProg - Ο τοπικός παροχέας εκπαίδευσης

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Statistics Subcategories

Forecasting Training CoursesForecasting
R Language Training CoursesR Language
Quantitative Analytics Training CoursesQuantitative Analytics

Statistics Course Outlines

CodeNameDurationOverview
foundrFoundation R7 hoursThe objective of the course is to enable participants to gain a mastery of the fundamentals of R and how to work with data.
scilabScilab14 hoursScilab 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
dmmlrData Mining & Machine Learning with R14 hoursR 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.
predmodrPredictive Modelling with R14 hoursR 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.
spssanalStatistical Analysis using SPSS21 hoursSPSS is software for editing and analyzing data.
introrIntroduction to R with Time Series Analysis21 hoursR 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.
tbladvTableau Advanced14 hoursTableau helps people see and understand data.
datavisR1Introduction to Data Visualization with R28 hoursThis course is intended for data engineers, decision makers and data analysts and will lead you to create very effective plots using R studio that appeal to decision makers and help them find out hidden information and take the right decisions
advrAdvanced R7 hoursThis course covers advanced topics in R programming.
wolfdataData Science: Analysis and Presentation7 hoursThe 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.
nlpwithrNLP: Natural Language Processing with R21 hoursIt 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 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.

Audience
Linguists and programmers

Format of the course
Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
mathematica1Mathematica - Elementary Programming, Visualizations and Data Presentation14 hoursMathematica consists of 20 years of creating the most powerful specialized mathematical software engine in the world.

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
danagrData and Analytics - from the ground up 42 hoursData 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](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.
radvmlAdvanced Machine Learning with R21 hoursIn 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:

- Use techniques as hyper-parameter tuning and deep learning
- Understand and implement unsupervised learning techniques
- Put a model into production for use in a larger application

Audience

- Developers
- Analysts
- Data scientists

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
dataarData Analytics With R21 hours[R](http://www.r-project.org/) 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
tidyverseIntroduction to Data Visualization with Tidyverse and R7 hoursThe 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
mlbankingrMachine Learning for Banking (with R)28 hoursIn 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
rforfinanceR Programming for Finance28 hoursR 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.
rintrofinanceIntroduction to R for Finance21 hoursR 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
rfintradingFinancial Trading with R21 hoursR 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
intermediaterforfinanceIntermediate R for Finance21 hoursR 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 advanced programming concepts in R as they walk through coding in R using financial examples.

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

- Implement advanced R programming techniques
- Use R to manipulate their data to perform more advanced financial operations

Audience

- Programmers
- Finance professionals
- IT Professionals

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
mlfinancerMachine Learning for Finance (with R)28 hoursMachine 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
dlfinancewithrDeep Learning for Finance (with R)28 hoursMachine 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
dlforbankingwithrDeep Learning for Banking (with R)28 hoursMachine 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
shinyrhtmlShiny, R and HTML: Merging Data Science and Web Development7 hoursShiny 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
rsttatanR for Statistical Analysis14 hoursOrganization – Lab work and practical examples on real data
rprogdaR Programming for Data Analysis14 hoursThis course is part of the Data Scientist skill set (Domain: Data and Technology)
rintrobIntroductory R for Biologists28 hoursR 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.
excelafdAnalysing Financial Data in Excel14 hoursAudience

Financial or market analysts, managers, accountants

Course Objectives

Facilitate and automate all kinds of financial analysis with Microsoft Excel
webappsrBuilding Web Applications in R with Shiny7 hoursDescription:

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.

Upcoming Statistics Courses

CourseCourse DateCourse Price [Remote / Classroom]
Applied Machine Learning - Πάτρα (Patras) Wed, 2019-03-06 09:303500EUR / 4100EUR
Applied Machine Learning - Nicosia, Jacovides TowerMon, 2019-03-11 09:303500EUR / 4100EUR
Applied Machine Learning - Θεσσαλονίκη (Thessaloniki) Wed, 2019-03-20 09:303500EUR / 4100EUR
Applied Machine Learning - Αθήνα (Athens), AcropolisMon, 2019-04-01 09:303500EUR / 4100EUR
Applied Machine Learning - Πάτρα (Patras) Mon, 2019-04-29 09:303500EUR / 4100EUR

Other regions

ΚύπροςΛευκωσίαΑθήναΠάτραΘεσσαλονίκη

Other countries

These courses are also available in other countries ››

Consulting

Statistics Consulting
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

Course Discounts

CourseVenueCourse DateCourse Price [Remote / Classroom]
Introduction to Embedded ComputersΑθήνα (Athens), AcropolisMon, 2019-02-25 09:303150EUR / 3750EUR
Neural computing – Data scienceΑθήνα (Athens), AcropolisMon, 2019-06-03 09:303150EUR / 3750EUR
Introduction to Ansible AutomationΘεσσαλονίκη (Thessaloniki) Mon, 2019-06-10 09:301350EUR / 1750EUR
Introduction to R with Time Series AnalysisΑθήνα (Athens), AcropolisWed, 2019-07-31 09:304725EUR / 5525EUR
AI Awareness for TelecomΠάτρα (Patras) Thu, 2019-09-05 09:303150EUR / 3750EUR

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