Explore Our Courses

Data Analytics with Tableau, Python, R, and SQL

35 Hours
Analitik data adalah ilmu menganalisis data mentah untuk mendapatkan wawasan dan tren. Tableau adalah alat intelijen bisnis dan visualisasi data terkemuka, sedangkan SQL adalah bahasa yang paling umum digunakan untuk kueri basis data. Bersama dengan dua bahasa pemrograman paling populer untuk ilmu data, Python dan R, Tableau dan SQL memberikan solusi end-to-end yang kuat yang dapat membantu memvisualisasikan dan menganalisis data secara efektif.Pelatihan langsung yang dipandu instruktur ini (online atau onsite) ditujukan untuk analis data dan siapa saja yang tertarik untuk mempelajari cara menggunakan dan mengintegrasikan Tableau, Python, R, dan SQL untuk visualisasi dan analisis data.Pada akhir pelatihan ini, peserta akan dapat:
    Lakukan analisis data menggunakan Python, R, dan SQL. Buat wawasan melalui visualisasi data dengan Tableau. Buat keputusan berdasarkan data untuk operasi bisnis.
Format Kursus
    Kuliah dan diskusi interaktif. Banyak latihan dan latihan. Implementasi langsung di lingkungan lab langsung.
Opsi Penyesuaian Kursus
    Untuk meminta pelatihan khusus untuk kursus ini, silakan hubungi kami untuk mengaturnya.
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Data Analytics With R

21 Hours
R 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
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Data and Analytics - from the ground up

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 over a period of weeks if preferred. We can work with you to deliver the course to best suit your needs.
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NLP: Natural Language Processing with R

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
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R Programming for Excel

21 Hours
R is a programming language and software environment for statistical computing. Together with R and Excel, users are able to implement R Tidyverse standards and more powerful R features for improving data analytics in Excel. This instructor-led, live training (online or onsite) is aimed at data analysts who wish to program in R for Excel. By the end of this training, participants will be able to:
  • Toggle and move data between Excel and R.
  • Use R Tidyverse and R features for data analytic solutions in Excel.
  • Update their data science skills by learning R.
Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
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R Programming for Finance

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.
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Advanced R

7 Hours
This course covers advanced topics in R programming.
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Algorithmic Trading with Python and R

14 Hours
Algorithmic trading is the practice of implementing pre-programmed instructions for placing trades. In theory, with algorithmic trading users will be able to achieve profits at a frequency not possible for a human trader. This instructor-led, live training (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.
Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
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Anomaly Detection with Python and R

14 Hours
Anomaly detection is the identification of extreme values that deviate from an overall pattern on a data set. Using Python and R in SAS, users can implement anomaly detection algorithms for identifying anomalies in big data. This instructor-led, live training (online or onsite) is aimed at data scientists and data analysts who wish to program in R and Python in SAS to carry out anomaly detection. By the end of this training, participants will be able to:
  • Identify whether data is an anomaly or is an expected value.
  • Implement algorithms for anomaly detection.
  • Use various techniques and methods to detect anomalies.
Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
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Programming with Big Data in R

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.
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R Fundamentals

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.
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Cluster Analysis with R and SAS

14 Hours
R is a programming language and software environment for statistical computing. SAS is a statistical software platform for predictive analysis, data management, advanced analytics, and more. With R in SAS, users can find natural groups of data for cluster analysis that are essential to data mining. This instructor-led, live training (online or onsite) is aimed at data analysts who wish to program with R in SAS for cluster analysis. By the end of this training, participants will be able to:
  • Use cluster analysis for data mining
  • Master R syntax for clustering solutions.
  • Implement hierarchical and non-hierarchical clustering.
  • Make data-driven decisions to help to improve business operations.
Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
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Data Mining with R

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.
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Deep Learning for Finance (with R)

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
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Deep Learning for Banking (with R)

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
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Data Mining & Machine Learning with R

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.
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Foundation R

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.
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Introduction to R with Time Series Analysis

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.
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KNIME with Python and R for Machine Learning

14 Hours
KNIME is an open source data analytical software for integrating machine learning and data mining through data pipelines. With Python and R, users are able to extend KNIME in its capabilities for data analytics and machine learning. This instructor-led, live training (online or onsite) is aimed at data scientists who wish to program in Python and R for KNIME. By the end of this training, participants will be able to:
  • Plan, build, and deploy machine learning models in KNIME.
  • Implement end to end data science projects.
  • Make data driven decisions for operations.
Format of the Course
  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.
Course Customization Options
  • To request a customized training for this course, please contact us to arrange.
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Machine Learning for Banking (with R)

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
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Machine Learning for Finance (with R)

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
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Marketing Analytics using R

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.
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Predictive Modelling with R

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.
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Advanced Machine Learning with R

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.
Audience
  • Developers
  • Analysts
  • Data scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Introductory R for Biologists

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.
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Introduction to R for Finance

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
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R

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.
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Neural Network in R

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

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
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R Programming for Data Analysis

14 Hours
This course is part of the Data Scientist skill set (Domain: Data and Technology)
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Testimonials(31)

The flexible and friendly style. Learning exactly what was useful and relevant for me

Jenny
Course - Advanced 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

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 to meet 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

That Haytham started with the basics and gave us enough time to do the examples and ensure that we were at the same page before we moved on to the next topic.

Jaco Dreyer - Africa Health Research Institute
Course - R Fundamentals

I enjoyed that it was very hands-on, so we were constantly having the chance to try things on, rather than just sitting listening to a lecture (for example). I felt like I am now able to go away and start using R, which I haven't been able to do before

Kathy Baisley - Africa Health Research Institute
Course - R Fundamentals

real life practical examples

Wioleta
Course - Data and Analytics - from the ground up

The patience of Kamil.

Laszlo Maros
Course - Data and Analytics - from the ground up

Kamil is very knowledgeable and nice person, I have learned from him a lot.

Aleksandra Szubert
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

The way the trainer made complex subjects easy to understand.

Adam Drewry
Course - Data and Analytics - from the ground up

the clarity with which he explained the entire course, as well as the willingness to return to the syllabus when necessary

Carlos Eloy - AMERICAN EXPRESS COMPANY MEXICO
Course - Data Analytics With R

I liked that the trainer made sure we all understood and were following the lectures. if we had a problem, he stopped and helped us fix it.

Cesar - AMERICAN EXPRESS COMPANY MEXICO
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

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

I get answers on all my questions.

Natalia Gladii
Course - Data Analytics With R

very tailored to needs

Yashan Wang
Course - Data Mining with R

The trainer was so knowledgeable and included areas I was interested in

Mohamed Salama
Course - Data Mining & Machine Learning with 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 - Birmingham City University
Course - Foundation R

Well thought out and high grade planning materials.

Andrew - Office of Projects Victoria - Department of Treasury & Finance
Course - Forecasting with R

he is patient

Abdul De kock - Vodacom
Course - Forecasting with R

his knowlede and practical exemples

Irina Tulgara
Course - Forecasting with R

A lot of knowldege - theoretical and practical

Anna Alechno
Course - Forecasting with R

Good detail on what R is used for and how to start using it right away

Hoss Shenassa - Trimac Management Services LP
Course - Introduction to R with Time Series Analysis

the matter was well presented and in an orderly manner.

Marylin Houle - Ivanhoe Cambridge
Course - Introduction to R with Time Series Analysis

The exercises.

Elena Velkova - CEED Bulgaria
Course - Predictive Modelling with R

He was very informative and helpful.

Pratheep Ravy
Course - Predictive Modelling with R

At the end of the class, we had a great overview of the language, we were provided tools to continue learning and were provided suggestions on how to continue learning. We covered AI/ML information.

Victor Prado - Global Knowledge Network Training Ltd
Course - R

The R-programming overview training is quite intensive but Tomasz is always helpful, energetic and up to date. On top of it, he is passionate about R. I would highly recommend his R sessions to anyone interested in R.

Luiza Panoschi - Global Knowledge Network Training Ltd
Course - R

Wasn't boring, the trainer could keep the attention, the topics were covered in depth.

Marta - Ministerstwo Zdrowia
Course - Advanced R Programming

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

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

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