Szkolenia Predictive Analytics
Lokalne, instruktażowe kursy szkoleniowe na żywo Predictive Analytics demonstrują poprzez praktyczną praktykę używania różnych narzędzi do budowy modeli predykcyjnych i stosowania ich do dużych zestawów danych próbek w celu przewidywania przyszłych zdarzeń na podstawie danych Przewidywanie szkoleń Analytics jest dostępne jako "szkolenie na miejscu" lub "szkolenie na żywo" Szkolenie na żywo w siedzibie klienta może odbywać się lokalnie w siedzibie klienta w Polsce lub w centrach szkoleniowych korporacji NobleProg w Polsce Zdalne szkolenie na żywo odbywa się za pomocą interaktywnego, zdalnego pulpitu NobleProg Twój lokalny dostawca szkoleń.
Opinie uczestników
zakres materialu
Maciej Jonczyk
Nazwa kursu: From Data to Decision with Big Data and Predictive Analytics
usystematyzowanie wiedzy z dziedziny ML
Orange Polska
Nazwa kursu: From Data to Decision with Big Data and Predictive Analytics
ref materiał do wykorzystania później był bardzo dobry.
PAUL BEALES- Seagate Technology.
Nazwa kursu: Applied Machine Learning
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Co najbardziej podobało Ci się w treningu ?: Dałem mi dobrą praktykę z użyciem R do budowania systemów uczenia maszynowego w rzeczywistych sytuacjach. Mogę użyć tego w mojej pracy od razu. What d
Nazwa kursu: Applied Machine Learning
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Był bardzo dobrze poinformowany i pomocny.
Pratheep Ravy
Nazwa kursu: Predictive Modelling with R
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ref materiał do wykorzystania później był bardzo dobry
PAUL BEALES
Nazwa kursu: Applied Machine Learning
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Trener Michael jest bardzo kompetentny i zręczny w temacie Big Data i R. Jest bardzo elastyczny i szybko dostosowuje szkolenie do potrzeb klientów. Jest także bardzo zdolny do rozwiązywania problemów technicznych i tematycznych w drodze. Fantastyczne i profesjonalne szkolenie!X
Xiaoyuan Geng - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Nazwa kursu: Programming with Big Data in R
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wprowadzenie nowych pakietów
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Nazwa kursu: Programming with Big Data in R
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Nauczyciel, pan Michael Yan, bardzo dobrze wchodził w interakcję z publicznością, instrukcje były jasne. Nauczyciel może również poszerzyć zakres informacji, w oparciu o prośby uczniów podczas szkoleniaOttawa
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Nazwa kursu: Programming with Big Data in R
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Tematyka i tempo były idealne
Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Nazwa kursu: Programming with Big Data in R
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Styl treningowy Richarda był interesujący, przykłady z prawdziwego świata pomogły wprowadzić koncepcje do domu ...
Jamie Martin-Royle - NBrown Group
Nazwa kursu: From Data to Decision with Big Data and Predictive Analytics
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Treść, ponieważ uważam ją za bardzo interesującą i myślę, że pomogłaby mi w ostatnim roku studiów na uniwersytecie.
Krishan Mistry - NBrown Group
Nazwa kursu: From Data to Decision with Big Data and Predictive Analytics
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Plany Kursów
| Kod | Nazwa | Czas trwania | Charakterystyka kursu |
|---|---|---|---|
| bigdatar | Programming with Big Data in R | 21 godz. | 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. |
| appliedml | Applied Machine Learning | 14 godz. | This training course is for people that would like to apply Machine Learning in practical applications. Audience This course is for data scientists and statisticians that have some familiarity with statistics and know how to program R (or Python or other chosen language). The emphasis of this course is on the practical aspects of data/model preparation, execution, post hoc analysis and visualization. The purpose is to give practical applications to Machine Learning to participants interested in applying the methods at work. Sector specific examples are used to make the training relevant to the audience. |
| apachemdev | Apache Mahout for Developers | 14 godz. | Audience Developers involved in projects that use machine learning with Apache Mahout. Format Hands on introduction to machine learning. The course is delivered in a lab format based on real world practical use cases. |
| d2dbdpa | From Data to Decision with Big Data and Predictive Analytics | 21 godz. | Audience If you try to make sense out of the data you have access to or want to analyse unstructured data available on the net (like Twitter, Linked in, etc...) this course is for you. It is mostly aimed at decision makers and people who need to choose what data is worth collecting and what is worth analyzing. It is not aimed at people configuring the solution, those people will benefit from the big picture though. Delivery Mode During the course delegates will be presented with working examples of mostly open source technologies. Short lectures will be followed by presentation and simple exercises by the participants Content and Software used All software used is updated each time the course is run so we check the newest versions possible. It covers the process from obtaining, formatting, processing and analysing the data, to explain how to automate decision making process with machine learning. |
| Piwik | Getting started with Piwik | 21 godz. | Audience Web analysist Data analysists Market researchers Marketing and sales professionals System administrators Format of course Part lecture, part discussion, heavy hands-on practice |
| datamodeling | Pattern Recognition | 35 godz. | This course provides an introduction into the field of pattern recognition and machine learning. It touches on practical applications in statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. The course is interactive and includes plenty of hands-on exercises, instructor feedback, and testing of knowledge and skills acquired. Audience Data analysts PhD students, researchers and practitioners |
| kdd | Knowledge Discover in Databases (KDD) | 21 godz. | Knowledge discovery in databases (KDD) is the process of discovering useful knowledge from a collection of data. Real-life applications for this data mining technique include marketing, fraud detection, telecommunication and manufacturing. In this course, we introduce the processes involved in KDD and carry out a series of exercises to practice the implementation of those processes. Audience Data analysts or anyone interested in learning how to interpret data to solve problems Format of the course After a theoretical discussion of KDD, the instructor will present real-life cases which call for the application of KDD to solve a problem. Participants will prepare, select and cleanse sample data sets and use their prior knowledge about the data to propose solutions based on the results of their observations. |
| intror | Introduction to R with Time Series Analysis | 21 godz. | 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. |
| predmodr | Predictive Modelling with R | 14 godz. | 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. |
| bigdatabicriminal | Big Data Business Intelligence for Criminal Intelligence Analysis | 35 godz. | Advances in technologies and the increasing amount of information are transforming how law enforcement is conducted. The challenges that Big Data pose are nearly as daunting as Big Data's promise. Storing data efficiently is one of these challenges; effectively analyzing it is another. In this instructor-led, live training, participants will learn the mindset with which to approach Big Data technologies, assess their impact on existing processes and policies, and implement these technologies for the purpose of identifying criminal activity and preventing crime. Case studies from law enforcement organizations around the world will be examined to gain insights on their adoption approaches, challenges and results. By the end of this training, participants will be able to: Combine Big Data technology with traditional data gathering processes to piece together a story during an investigation Implement industrial big data storage and processing solutions for data analysis Prepare a proposal for the adoption of the most adequate tools and processes for enabling a data-driven approach to criminal investigation Audience Law Enforcement specialists with a technical background Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| aifortelecom | AI Awareness for Telecom | 14 godz. | AI is a collection of technologies for building intelligent systems capable of understanding data and the activities surrounding the data to make "intelligent decisions". For Telecom providers, building applications and services that make use of AI could open the door for improved operations and servicing in areas such as maintenance and network optimization. In this course we examine the various technologies that make up AI and the skill sets required to put them to use. Throughout the course, we examine AI's specific applications within the Telecom industry. Audience Network engineers Network operations personnel Telecom technical managers Format of the course Part lecture, part discussion, hands-on exercises |
| bigdataanahealth | Big Data Analytics in Health | 21 godz. | Big data analytics involves the process of examining large amounts of varied data sets in order to uncover correlations, hidden patterns, and other useful insights. The health industry has massive amounts of complex heterogeneous medical and clinical data. Applying big data analytics on health data presents huge potential in deriving insights for improving delivery of healthcare. However, the enormity of these datasets poses great challenges in analyses and practical applications to a clinical environment. In this instructor-led, live training (remote), participants will learn how to perform big data analytics in health as they step through a series of hands-on live-lab exercises. By the end of this training, participants will be able to: Install and configure big data analytics tools such as Hadoop MapReduce and Spark Understand the characteristics of medical data Apply big data techniques to deal with medical data Study big data systems and algorithms in the context of health applications Audience Developers Data Scientists Format of the Course Part lecture, part discussion, exercises and heavy hands-on practice. Note To request a customized training for this course, please contact us to arrange. |
Upcoming Courses
| Szkolenie | Data Kursu | Cena szkolenia [Zdalne / Stacjonarne] |
|---|---|---|
| AI Awareness for Telecom - Częstochowa, ul. Wały Dwernickiego 117/121 | śr., 2018-07-04 09:00 | 1990PLN / 2740PLN |
| Knowledge Discover in Databases (KDD) - Łódź, ul. Tatrzańska 11 | śr., 2018-07-04 09:00 | 4990PLN / 5990PLN |
| Applied Machine Learning - Katowice ul. Opolska 22 | czw., 2018-07-05 09:00 | 3330PLN / 4080PLN |
| Predictive Modelling with R - Zakopane, ul. Jagiellońska 30 | czw., 2018-07-05 09:00 | 3330PLN / 4080PLN |
| Pattern Recognition - Kielce, ul. Warszawska 19 | pon., 2018-07-09 09:00 | 8320PLN / 9820PLN |