Local, 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 "onsite live training" or "remote live training". Onsite live Statistics training can be carried out locally on customer premises in India or in NobleProg corporate training centers in India. Remote live training is carried out by way of an interactive, remote desktop.

NobleProg -- Your Local Training Provider

Testimonials

★★★★★

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

The practical exercises were extremely beneficial.

Vascutek Ltd

Course: Minitab for Statistical Data Analysis

The use of examples, though even these were demonstrated at some considerable speed.

Vascutek Ltd

Course: Minitab for Statistical Data Analysis

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

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

Statistics Subcategories

Statistics Course Outlines

Title

Duration

Overview

Title

Duration

Overview

Advanced R

7 hours

Overview

This course covers advanced topics in R programming.

Scilab

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

Predictive Modelling with R

14 hours

Overview

Advanced Machine Learning with R

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.

Audience

- Developers
- Analysts
- Data scientists

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

Financial Trading with 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

R Programming for Finance

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.

Introductory R for Biologists

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.

Introduction to R for Finance

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

R

21 hours

Overview

Neural Network in R

14 hours

Overview

This course is an introduction to applying neural networks in real world problems using R-project software.

Advanced R Programming

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

R Programming for Data Analysis

14 hours

Overview

This course is part of the Data Scientist skill set (Domain: Data and Technology)

R for Statistical Analysis

14 hours

Overview

Organization – Lab work and practical examples on real data

Shiny, R and HTML: Merging Data Science and Web Development

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

Advanced Statistics using SPSS Predictive Analytics Software

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

Statistical Analysis using SPSS

21 hours

Overview

SPSS is software for editing and analyzing data.

Statistics with SPSS Predictive Analytics Software

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.

Statistical and Econometric Modelling

21 hours

Overview

The objective of the course is to enable participants to gain a mastery of the fundamentals of statistical and econometric modelling.

Statistical Thinking for Decision Makers

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.

Statistics Level 1

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...

Statistics Level 2

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)

Statistics for Researchers

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.

Talent Acquisition Analytics

14 hours

Overview

This instructor-led, live training (onsite or remote) 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.

Tableau Advanced

14 hours

Overview

Tableau helps people see and understand data.

Tableau Intermediate Training Course

14 hours

Overview

Tableau helps people see and understand data.

Introduction to Data Visualization with Tidyverse and R

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

NLP: Natural Language Processing with R

21 hours

Overview

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

Minitab for Statistical Data Analysis

14 hours

Overview

The course is aimed at anyone interested in statistical analysis. It provides familiarity with Minitab and will increase the effectiveness and efficiency of your data analysis and improve your knowledge of statistics.

Market Forecasting

14 hours

Overview

Audience

This course has been created for analysts, forecasters wanting to introduce or improve forecasting which can be related to sale forecasting, economic forecasting, technology forecasting, supply chain management and demand or supply forecasting.

Description

This course guides delegates through series of methodologies, frameworks and algorithms which are useful when choosing how to predict the future based on historical data.

It uses standard tools like Microsoft Excel or some Open Source programs (notably R project).

The principles covered in this course can be implemented by any software (e.g. SAS, SPSS, Statistica, MINITAB ...)

Analysing Financial Data in Excel

14 hours

Overview

Audience

Financial or market analysts, managers, accountants

Course Objectives

Facilitate and automate all kinds of financial analysis with Microsoft Excel

Upcoming Statistics Courses

Intermediate R for Finance

2019-09-02 09:30:00

Pune, JM Road - Classroom

Remote

152,191INR

Classroom

176,691INR

Intermediate R for Finance

2019-09-02 09:30:00

Mumbai, Andheri (East) - Classroom

Remote

152,191INR

Classroom

208,191INR

Intermediate R for Finance

2019-09-02 09:30:00

Mumbai, Andheri East - Classroom

Remote

152,191INR

Classroom

172,191INR

Intermediate R for Finance

2019-09-02 09:30:00

Delhi, Mayur Vihar - Classroom

Remote

152,191INR

Classroom

172,191INR

Intermediate R for Finance

2019-09-02 09:30:00

Delhi, Mohan Estate - Classroom

Remote

152,191INR

Classroom

176,691INR

Other countries

These courses are also available in other countries ››

Consulting

Statistics Consulting

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