I corsi di formazione R (R Language) live con istruttore locale dimostrano attraverso handson vari aspetti del linguaggio R, inclusi i fondamenti della programmazione R, la programmazione avanzata R e l´analisi dei dati e la visualizzazione dei dati I nostri esercizi di allenamento riguardano problemi e soluzioni del mondo reale in settori quali finanza, banche e assicurazioni. I corsi di formazione NobleProg R vanno dai corsi per principianti ai corsi avanzati e sono popolari tra le aziende che desiderano adottare R per lo sviluppo di applicazioni di Machine Learning e Deep Learning. La formazione R è disponibile come formazione dal vivo in loco o formazione dal vivo a distanza. La formazione on-site in loco può essere svolta localmente presso la sede del cliente a Italia o nei centri di formazione aziendale NobleProg a Italia. La formazione in remoto dal vivo viene effettuata tramite un desktop remoto interattivo. NobleProg, il tuo fornitore di formazione locale.
Recensioni
Lui è stato molto istruttivo e utile.
Pratheep Ravy
Corso: Predictive Modelling with R
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Ottengo risposte su tutte le mie domande.
Natalia Gladii
Corso: Data Analytics With R
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Un sacco di problemi che possono essere esplorati dopo la formazione
Klaudia Kłębek
Corso: Data Mining z wykorzystaniem R
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L'allenatore era così preparato e comprendeva le aree che mi interessavano.
Mohamed Salama
Corso: Data Mining & Machine Learning with R
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Molto su misura per esigenze.
Yashan Wang
Corso: Data Mining with R
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Mi è davvero piaciuto lavorare 1: 1 con Gunner.
Bryant Ives
Corso: Introduction to R
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Mi sono piaciute le nuove intuizioni nel deep machine learning.
Josip Arneric
Corso: Neural Network in R
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Abbiamo acquisito una certa conoscenza di NN in generale, e quello che è stato il più interessante per me sono stati i nuovi tipi di NN che sono popolari al giorno d'oggi.
Tea Poklepovic
Corso: Neural Network in R
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Ho apprezzato soprattutto i grafici in R :))).
Faculty of Economics and Business Zagreb
Corso: Neural Network in R
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Lo stile flessibile e amichevole. Imparare esattamente ciò che è stato utile e rilevante per me.
Jenny Tickner
Corso: Advanced R
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Mi sono piaciuti i fogli Excel forniti con gli esercizi con esempi. Ciò significava che se Tamil fosse stato trattenuto ad aiutare altre persone, avrei potuto proseguire con le parti successive.
Luke Pontin
Corso: Data and Analytics - from the ground up
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Imparare come usare eccellentemente.
Torin Mitchell
Corso: Data and Analytics - from the ground up
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Il modo in cui il formatore ha reso le materie complesse facili da capire.
Adam Drewry
Corso: Data and Analytics - from the ground up
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Istruzioni dettagliate e complete fornite da esperti esperti e ben informati sull'argomento.
Justin Roche
Corso: Data and Analytics - from the ground up
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Tamil è una persona molto esperta e simpatica, ho imparato molto da lui.
Aleksandra Szubert
Corso: Data and Analytics - from the ground up
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Mi è piaciuta la prima sessione. Molto intenso e veloce.
Digital Jersey
Corso: Data and Analytics - from the ground up
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Mi è piaciuta soprattutto la pazienza di Tamil.
Laszlo Maros
Corso: Data and Analytics - from the ground up
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Ho davvero tratto beneficio dagli esempi pratici della vita reale.
Wioleta (Vicky) Celinska-Drozd
Corso: Data and Analytics - from the ground up
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Ho risposto a tutte le richieste dell'argomento e ho impiegato molto tempo per rispondere.
HSH Nordbank AG
Corso: Prognosen mit R
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Gli esercizi gratuiti.
Sabine Stammberger
Corso: Prognosen mit R
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Un sacco di conoscenza - teorica e pratica.
Anna Alechno
Corso: Forecasting with R
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Mi è davvero piaciuta la sua conoscenza ed esempi pratici.
Irina Tulgara
Corso: Forecasting with R
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Panoramica e comprensione di quanto è grande l'argomento.
British American Shared Services Europe BAT GBS Finance, WER/Centre/EEMEA
Corso: Forecasting with R
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buona interazione con il formatore, scambio dinamico di conoscenze
NIIT Limited
Corso: Data Analytics With R
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Le mani sugli esempi sono state le più utili.
Sean Kaukas
Corso: Introduction to R
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Michael il formatore è molto esperto e abile circa il tema di Big Data e R. È molto flessibile e personalizza rapidamente la formazione soddisfacendo le esigenze dei clienti. È anche molto capace di risolvere problemi tecnici e di argomento in movimento. Formazione fantastica e professionale !.
Xiaoyuan Geng - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Corso: Programming with Big Data in R
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Ho davvero apprezzato l'introduzione di nuovi pacchetti.
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Corso: Programming with Big Data in R
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Il tutor, il signor Michael Yan, ha interagito molto bene con il pubblico, le istruzioni erano chiare. Il tutor può anche aggiungere ulteriori informazioni in base alle richieste degli studenti durante la formazione.
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Corso: Programming with Big Data in R
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L'argomento e il ritmo erano perfetti.
Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Corso: Programming with Big Data in R
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Buona panoramica di R e buona gamma di argomenti. Il trainer è stato felice di rispondere a tutte le domande.
Symphony EYC
Corso: R
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Ho davvero apprezzato la conoscenza del trainer.
Stephanie Seiermann
Corso: R
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E 'stato molto istruttivo e tenuto professionalmente. Il livello di conoscenza di Wojteks era così avanzato che poteva sostanzialmente rispondere a qualsiasi domanda ed era disposto a impegnarsi per adeguare la formazione ai miei bisogni personali.
Sonja Steiner - BearingPoint GmbH
Corso: R Programming for Data Analysis
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un sacco di esercizi che posso usare direttamente nel mio lavoro.
Alior Bank S.A.
Corso: Sieci Neuronowe w R
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Esempi su dati reali.
Alior Bank S.A.
Corso: Sieci Neuronowe w R
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neuralnet, pROC in un ciclo.
Alior Bank S.A.
Corso: Sieci Neuronowe w R
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Mi sono piaciuti molto gli esercizi sulla modellazione delle serie temporali.
Teleperformance
Corso: Data Analytics With R
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Nuovo strumento che è "R" e trovo interessante conoscere l'esistenza di tale strumento per l'analisi dei dati.
Michael Lopez - Teleperformance
Corso: Data Analytics With R
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Lo strumento è stato interessante e vedo l'uso. Mi piacerebbe saperne di più su di esso.
Teleperformance
Corso: Data Analytics With R
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Un sacco di pratica
Centrum Innowacji ProLearning Agnieszka Kołodziejczyk
Corso: R
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Conoscenza sostanziale del trainer e dell'esperienza, vari esempi
Anna Wysocka - Centrum Innowacji ProLearning Agnieszka Kołodziejczyk
Corso: R
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la questione è stata ben presentata e in modo ordinato.
Marylin Houle - Ivanhoe Cambridge
Corso: Introduction to R with Time Series Analysis
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Ha davvero spiegato tutto bene e ha usato esempi.
royal bank of Canada
Corso: R
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Mi sono piaciuta l'auto-apprendimento attraverso esercizi e suggerimenti e scorciatoie condivise.
Competition Bureau
Corso: R for Data Analysis and Research
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Sono stato beneficiare delle note dettagliate per mantenere e lavorare attraverso dopo il corso.
Public Health Wales NHS Trust
Corso: Introduction to Data Visualization with Tidyverse and R
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Il ritmo era giusto e l'atmosfera rilassata ha fatto sentire i candidati a proprio agio a fare domande.
Rhian Hughes - Public Health Wales NHS Trust
Corso: Introduction to Data Visualization with Tidyverse and R
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Ho potuto trarre beneficio dai buoni esempi e dall'opportunità di seguirmi.
Environmental and Climate Change Canada
Corso: Foundation R
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Ho davvero apprezzato le mani passati esercizi.
Yunfa Zhu - Environmental and Climate Change Canada
Corso: Foundation R
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Il trainer, il cibo, e lo spazio erano tutti fantastici.
Canada Revenue Agency
Corso: R
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Mi piace scrivere codice con dati di esempio e annotare lo script per riferimenti futuri.
Canada Revenue Agency
Corso: R
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Gli script pre-fatti utilizzati per il materiale di formazione è stato molto utile. La formazione interattiva ha permesso una chiara comprensione di ogni argomento.
Canada Revenue Agency
Corso: R
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Sottocategorie R
Schema generale del corso R
Nome del corso
Durata
Overview
Nome del corso
Durata
Overview
21 hours
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.
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.
14 hours
This course is an introduction to applying neural networks in real world problems using R-project software.
7 hours
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
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
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.
14 hours
The aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the R programming platform and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results.
Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
21 hours
R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.
21 hours
R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.
7 hours
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.
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.
28 hours
R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.
21 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
Audience
Developers / data analytics
Duration
3 days
Format
Lectures and Hands-on
14 hours
This course is part of the Data Scientist skill set (Domain: Data and Technology)
14 hours
R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.
14 hours
R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.
21 hours
R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.
21 hours
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 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
42 hours
Data analytics is a crucial tool in business today. We will focus throughout on developing skills for practical hands on data analysis. The aim is to help delegates to give evidence-based answers to questions:
What has happened?
- processing and analyzing data
- producing informative data visualizations
What will happen?
- forecasting future performance
- evaluating forecasts
What should happen?
- turning data into evidence-based business decisions
- optimizing processes
The course itself can be delivered either as a 6 day classroom course or [remotely](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.
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.
21 hours
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.
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.
28 hours
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
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
28 hours
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.
21 hours
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
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
21 hours
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 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
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
28 hours
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
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
28 hours
Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks. R is a popular programming language in the financial industry. It is used in financial applications ranging from core trading programs to risk management systems.
In this instructor-led, live training, participants will learn how to implement deep learning models for finance using R as they step through the creation of a deep learning stock price prediction model.
By the end of this training, participants will be able to:
- Understand the fundamental concepts of deep learning
- Learn the applications and uses of deep learning in finance
- Use R to create deep learning models for finance
- Build their own deep learning stock price prediction model using R
Audience
- Developers
- Data scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
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
28 hours
Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks. R is a popular programming language in the financial industry. It is used in financial applications ranging from core trading programs to risk management systems.
In this instructor-led, live training, participants will learn how to implement deep learning models for banking using R as they step through the creation of a deep learning credit risk model.
By the end of this training, participants will be able to:
- Understand the fundamental concepts of deep learning
- Learn the applications and uses of deep learning in banking
- Use R to create deep learning models for banking
- Build their own deep learning credit risk model using R
Audience
- Developers
- Data scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
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
7 hours
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
7 hours
The objective of the course is to enable participants to gain a mastery of the fundamentals of R and how to work with data.
14 hours
This instructor-led, live training in Italia (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.
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.
Last Updated:
Prossimi corsi R
28-12-2021 09:30
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10-01-2022 09:30
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27-01-2022 09:30
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31-01-2022 09:30
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Other countries
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