Praktyczne szkolenia na żywo z Data Analysis pokazuje jak poprzez praktyczne ćwiczenia opanować podstawy i zaawansowane koncepcje. Na szkoleniu Data Analysis poznasz proces przetwarzania danych, które będziesz mógł następnie wykorzystać do różnych celów m.in jak tworzyć różne raporty na podstawie użytecznych informacji i wniosków. W zależności od rodzaju danych i stawianych problemów, może to oznaczać użycie metod statystycznych, eksploracyjnych i innych.
Szkolenia Data Analysis są dostępne jako "szkolenie na miejscu" lub "szkolenie na żywo". Szkolenie stacjonarne może odbywać się lokalnie w siedzibie klienta w Polsce lub w ośrodkach szkoleniowych NobleProg w Polsce. Zdalne szkolenie online odbywa się za pomocą interaktywnego, zdalnego pulpitu DaDesktop .
NobleProg -- Twój lokalny dostawca szkoleń.
Opinie uczestników
Sposób kontaktu prowadzący - szkolony. Podejście dobre zarówno dla grupy jak i do indywidualnej osoby.
Marcin Szcześniak - Credit Agricole Bank P
Szkolenie: BPMN 2.0 dla Analityków Biznesowych
świczenia
Piotr Kubiński
Szkolenie: BPMN 2.0 dla Analityków Biznesowych
Test końcowy symulujący pytania z egzaminu, gdzie próbowaliśmy jako grupa rozwiązać zadania w oparciu o zdobytą na szkoleniu wiedzę.
Dominik Łubiński
Szkolenie: Business Analysis, BABOK V3.0 and IIBA Certification Preparation
Wszechstronna wiedza prowadzącego - na wszystkie nasze pytania dawał odpowiedzi przerastające moje oczekiwania... Wykładowca świetnie prowadzi dyskusje... Nie brakuje mu cierpliwości...
Łukasz Matulewicz
Szkolenie: Programowanie w języku Python
Duża wiedzą prowadzącego, różnorodność narzędzi i praktyczne podejście do tematu
Magdalena Stupak
Szkolenie: Programowanie w języku Python
duza wiedza trenera, sposob tlumaczenia
Renata Cylejowska
Szkolenie: Programowanie w języku Python
Wszystko
Grześ
Szkolenie: BPMN 2.0 dla Analityków Biznesowych
Praktyczne przykłady.
Przemysław Domański
Szkolenie: BPMN 2.0 dla Analityków Biznesowych
Profesjonalizm, elokwencja, humor i duża wiedza.
Michał Zych
Szkolenie: Podstawy inżynierii wymagań i analizy
Fakt, że dostaliśmy gotowe rozwiązania na zadane problemy + pokazanie szerokiego spektrum zastosowań + przekazane kompendium wiedzy.
Wojciech Michalak
Szkolenie: Power BI
Trener posiada bardzo szeroką wiedzę, potrafi ją przekazać. Angażuje uczestników do interakcji i wspólnego rozwiązywania napotkanych problemów.
Nina Rokita
Szkolenie: Power BI
Trener był w stałym kontakcie z odbiorcami szkolenia, dostosowywał tempo do naszych potrzeb i na bieżąco rozwiązywał nasze problemy i odpowiadał na nasze pytania
Dominika Jaworska
Szkolenie: Power BI
Szkolenie było bardzo spójne, dowiedziałam się o wielu ciekawych funkcjonalnościach programu.
Anna Klimczak
Szkolenie: Power BI
Dobrze przygotowane, przemyslane cwiczenia oraz wiedza prowadzacego
Sandra Przewdzing
Szkolenie: Power BI
Wykorzystanie data-integration
Waldemar Wisniewski
Szkolenie: Pentaho Business Intelligence (PBI) - moduły raportowe
wiedza trenera, dostępny sprzęt
Mariusz Moskal
Szkolenie: Pentaho Business Intelligence (PBI) - moduły raportowe
Przykłady wzbogacane danymi rzeczywistymi i scenariuszami przydatnymi w codziennej praktyce
Krzysztof Świątczak
Szkolenie: Pentaho Business Intelligence (PBI) - moduły raportowe
Trener ma duzo anegdot i potrafi pokazywac tresc na prostych zyciowych wykladach
Katarzyna Gołda
Szkolenie: Business Analysis
Pan Bogdan jest świetnym specjalistą i umie przekazać wiedzę w przystępny sposób. Rozumie i zauważa kiedy publiczność się "wyłącza".
Unit4 Polska sp. z o.o; ALTEN Polska Sp. z o.o.; UBS; Zerochaos Sp. z o.o.
Szkolenie: Business Analysis
Podejscie trenera, humor i intereaktywny sposob prowadzenia szkolen oraz nawiazywanie do wlasnych doswiadczen.
Zbigniew Grzeskow
Szkolenie: Business Analysis
Otwartość, łatwość prowadzenia rozmowy, atmosfera.
Lucyna Kowalczyk
Szkolenie: Business Analysis
"gawędziarski" styl prowadzenia
Tomasz Niziołek
Szkolenie: Business Analysis
Podstawowe informacje pozwalajae na samodzielne rozpoczęcie pracy i uwagi dot. optymalizacji podejścia
Robert Kaźmierczak
Szkolenie: Microsoft Office Excel - moduł Business Intelligence
Duża ilość praktycznych przykładów, które pozwalają zapamiętać przerabiany materiał
Talex S.A.
Szkolenie: BPMN 2.0 dla Analityków Biznesowych
Życiowe i proste przykłady
Justyna Krzewińska
Szkolenie: BPMN 2.0 dla Analityków Biznesowych
poziom skomplikowania zadań - był wyższy niż podczas zadań z uml i wymagał większego zaangażowania, było to bardzo pozytywne.
Talex S.A.
Szkolenie: BPMN 2.0 dla Analityków Biznesowych
zadania
Talex S.A.
Szkolenie: BPMN 2.0 dla Analityków Biznesowych
forma z ćwiczeniami, przygotowanie narzędzi profesjonalne
Kinga
Szkolenie: BPMN 2.0 dla Analityków Biznesowych
Sposób prowadzenia zajęć, treść szkolenia, ćwiczenia
Talex S.A.
Szkolenie: BPMN 2.0 dla Analityków Biznesowych
Zrozumiałe dla wszystkich przykłady i praca w aplikacji, gdzie na żywo można było od razu zamodelować dany aspekt zagadnienia.
Euro Bank S.A.
Szkolenie: Analiza biznesowa i systemowa z użyciem notacji UML - warsztat praktyczny dla PO w metodyce Scrum
przekrojowe podejście do tematu
Łukasz Zięba
Szkolenie: Efficient Requirement Management using Agile Methods and Agile UML Modeling
Duza wiedza ogolna trenra i doswiadczenie
Nokia Solutions and Networks Sp. z o.o.
Szkolenie: Efficient Requirement Management using Agile Methods and Agile UML Modeling
Zywy sposob prowadzenia
Nokia Solutions and Networks Sp. z o.o.
Szkolenie: Efficient Requirement Management using Agile Methods and Agile UML Modeling
dobra interakcja z trenerem, dynamiczna wymiana wiedzy
NIIT Limited
Szkolenie: Data Analytics With R
trener zerkał i pomagał każdej osobie indywidualnie
Szymon Wolny
Szkolenie: Programowanie w języku Python
Zestaw ćwiczeń idealnie dopasowany do tematyki. Ćwiczenia łatwe i "z gwiazdką"
Motorola Solutions Systems Polska Sp. z o.o
Szkolenie: Programowanie w języku Python
Dobry balans teoria/ćwiczenia, dostosowanie poziomu wykładów do słuchaczy mniej i bardziej doświadczonych, bardzo duży plus za użycie Jupiter Notebooka i pokazywanie na bieżąco teorii w praktyce. Podobało mi się również zebranie anonimowego feedbacku po pierwszej części szkolenia - następnego dnia wszystko było przygotowane zgodnie z naszymi sugestiami i pomimo że wcześniej było już bardzo dobrze, to później było jeszcze lepiej :)
Motorola Solutions Systems Polska Sp. z o.o
Szkolenie: Programowanie w języku Python
zaangażowanie prowadzącego, przygotowanie, podejście do słuchaczy, chęć wytłumaczenia wszystkich niejasności
Małgorzata Konior
Szkolenie: Programowanie w języku Python
To, ze prowadzący podchodzi do każdego, nawet gdy nie woła o pomoc i sprawdza poziom wykonanego ćwiczenia.
Agnieszka Bielak
Szkolenie: Programowanie w języku Python
Trener przedstawiał bardzo krótką teorie na temat danego zagadnienia i od razu przechodziliśmy do praktyki. Fajny sposób z rozwieszaniem kartek, co daje informacje trenerowi ile czasu ma poświęcić na dane zadanie, oraz kto jeszcze ma problemy z rozwiązaniem.
Motorola Solutions Systems Polska Sp. z o.o
Szkolenie: Programowanie w języku Python
Że nawet jak ktoś nie prosił to, ale widać było że nie idzie do przodu z zadaniem to Krzysztof podchodził i potrafił umiejętnie doradzić
Motorola Solutions Systems Polska Sp. z o.o
Szkolenie: Programowanie w języku Python
Sposób prowadzenia, ćwiczenia, w sumie to wszystko podobało się, bardzo jestem zadowolony z tego ze trafiłem do takiego trenera
Maksym Kolodiy
Szkolenie: Programowanie w języku Python
Realne przykłady ćwiczeń
Motorola Solutions Systems Polska Sp. z o.o
Szkolenie: Programowanie w języku Python
Dostępność materiałów szkoleniowych (Jupyter), tworzone na bieżąco - aktualizowanie notebooka w zależności od pytań, które padły w czasie zajęć. Rozwiewanie wątpliwości, odpowiedzi na wszelkie pytania.
Motorola Solutions Systems Polska Sp. z o.o
Szkolenie: Programowanie w języku Python
Dostępność i ciekawy sposób dostarczania materiałów dydaktycznych.
Motorola Solutions Systems Polska Sp. z o.o
Szkolenie: Programowanie w języku Python
Ćwiczenia na funkcjach!
WIktor Paprzycki
Szkolenie: SQL Advanced level for Analysts
Plany szkoleń z technologii Data Analysis
Nazwa kursu
Czas trwania
Opis
Nazwa kursu
Czas trwania
Opis
28 godzin
Kurs przeznaczony jest dla osób pragnących nauczyć się języka programowania Python . Nacisk kładziony jest na język Python , podstawowe biblioteki, a także na wybór najlepszych i najbardziej przydatnych bibliotek opracowanych przez społeczność Python . Python napędza firmy i jest używany przez naukowców na całym świecie - jest to jeden z najpopularniejszych języków programowania.
Kurs może być prowadzony w Python 2.7.x lub 3.x, z praktycznymi ćwiczeniami wykorzystującymi pełną moc obu wersji języka. Ten kurs może być dostarczony w dowolnym systemie operacyjnym (wszystkie wersje UNIX, w tym Linux i Mac OS X, a także Microsoft Windows).
Ćwiczenia praktyczne stanowią około 70% czasu kursu, a około 30% to pokazy i prezentacje. W trakcie kursu można zadawać dyskusje i pytania.
Uwaga: szkolenie może być dostosowane do konkretnych potrzeb na wcześniejsze żądanie przed proponowaną datą kursu.
Kurs może być prowadzony w Python 2.7.x lub 3.x, z praktycznymi ćwiczeniami wykorzystującymi pełną moc obu wersji języka. Ten kurs może być dostarczony w dowolnym systemie operacyjnym (wszystkie wersje UNIX, w tym Linux i Mac OS X, a także Microsoft Windows).
Ćwiczenia praktyczne stanowią około 70% czasu kursu, a około 30% to pokazy i prezentacje. W trakcie kursu można zadawać dyskusje i pytania.
Uwaga: szkolenie może być dostosowane do konkretnych potrzeb na wcześniejsze żądanie przed proponowaną datą kursu.
28 godzin
In this instructor-led, live training in w Polsce, participants will learn advanced Python programming techniques, including how to apply this versatile language to solve problems in areas such as distributed applications, data analysis and visualization, UI programming and maintenance scripting.
14 godzin
Szkolenie jest wprowadzeniem do nauki programowania w języku Python. Nacisk został położony na strukturę języka, główne biblioteki jak również na najciekwsze i najbardziej przydatne, opracowane przez Python community. Python zarówno napędza biznes oraz używany przez naukowców na całym świecie. Dzięki bogatemu zapleczu gotowych bibliotek Python jest jednym z najpopularniejszych języków do analizy danych. Python jest też bardzo prosty w nauce, dzięki czemu pisanie własnych, dedykowanych narzędzi nie stanowi problemu nawet dla początkujących programistów.
14 godzin
Kurs jes przeznaczony dla analityków, badaczy naukowych, statystyków, osób na co dzien wykorzystujących MS Excel w pracy oraz wszystkich tych którzy chcieliby poznać jakie możliwości daje analiza statystyczna w Excel.
Kurs poprawia znajomość programu Excel, statystyki, analizy statystycznej oraz zwiększa efektywności i skuteczność pracy czy też prowadzonych badań. Szkolenie opisuje jak używać Analysis ToolPack w programie Microsoft Excel, funkcji statystycznych oraz jak wykonywać procedury statystyczne. Szkolenie pokazuje ograniczenia Excela i wyjaśnia jak je przezwyciężyć.
Kurs poprawia znajomość programu Excel, statystyki, analizy statystycznej oraz zwiększa efektywności i skuteczność pracy czy też prowadzonych badań. Szkolenie opisuje jak używać Analysis ToolPack w programie Microsoft Excel, funkcji statystycznych oraz jak wykonywać procedury statystyczne. Szkolenie pokazuje ograniczenia Excela i wyjaśnia jak je przezwyciężyć.
7 godzin
This instructor-led, live training in w Polsce (online or onsite) is aimed at data analysts who wish to learn techniques for preparing data in Excel, then visualizing it in Power BI.
By the end of this training, participants will be able to:
- Understand the principles of data analysis, objectives of data analysis, and approaches for data analysis.
- Use DAX formulas in Power BI for complex calculations.
- Create and use visualizations and charts for particular analysis cases.
- Import with Power View to move from Excel based Power BI to independent Power BI.
By the end of this training, participants will be able to:
- Understand the principles of data analysis, objectives of data analysis, and approaches for data analysis.
- Use DAX formulas in Power BI for complex calculations.
- Create and use visualizations and charts for particular analysis cases.
- Import with Power View to move from Excel based Power BI to independent Power BI.
14 godzin
Pandas is a Python package that provides data structures for working with structured (tabular, multidimensional, potentially heterogeneous) and time series data.
21 godzin
A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data. The acronym GIS is sometimes used for geographic information science (GIScience) to refer to the academic discipline that studies geographic information systems and is a large domain within the broader academic discipline of geoinformatics.
The use of Python with GIS has substantially increased over the last two decades, particularly with the introduction of Python 2.0 series in 2000, which included many new programming features that made the language much easier to deploy. Since that time, Python has not only been utilized within commercial GIS such as products by Esri but also open source platforms, including as part of QGIS and GRASS. In fact, Python today is by far the most widely used language by GIS users and programmers.
This program covers the usage of Python and its advance libraries like geopandas, pysal, bokeh and osmnx to implement your own GIS features. The program also covers introductory modules around ArcGIS API, and QGIS toolboox.
The use of Python with GIS has substantially increased over the last two decades, particularly with the introduction of Python 2.0 series in 2000, which included many new programming features that made the language much easier to deploy. Since that time, Python has not only been utilized within commercial GIS such as products by Esri but also open source platforms, including as part of QGIS and GRASS. In fact, Python today is by far the most widely used language by GIS users and programmers.
This program covers the usage of Python and its advance libraries like geopandas, pysal, bokeh and osmnx to implement your own GIS features. The program also covers introductory modules around ArcGIS API, and QGIS toolboox.
14 godzin
In this instructor-led, live training in w Polsce (onsite or remote), participants will learn how to combine the capabilities of Python and Excel.
By the end of this training, participants will be able to:
- Install and configure packages for integrating Python and Excel.
- Read, write, and manipulate Excel files using Python.
- Call Python functions from Excel.
By the end of this training, participants will be able to:
- Install and configure packages for integrating Python and Excel.
- Read, write, and manipulate Excel files using Python.
- Call Python functions from Excel.
14 godzin
In this instructor-led, live training in w Polsce, participants will learn three different approaches for accessing, analyzing and visualizing data. We start with an introduction to RDMS databases; the focus will be on accessing and querying an Oracle database using the SQL language. Then we look at strategies for accessing an RDMS database programmatically using the Python language. Finally, we look at how to visualize and present data graphically using TIBCO Spotfire.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
28 godzin
This instructor-led, live training in w Polsce (online or onsite) is aimed at persons who wish to learn just enough Python to begin crunching numbers from sales data, traffic analytics, customer interactions, etc..
By the end of this training, participants will be able to:
- Install and configure the necessary software, libraries and development environment to begin writing Python code for data analysis.
- Analyze data from sources such as Excel, CSV, JSON files and databases.
- Clean data to improve its usefulness before analyzing it.
- Perform simple statistical analysis.
- Generate reports that present the desired data in just the right format, from straight numbers to data visualizations.
- Gain valuable insight from data, including trends in performance, problematic areas.
By the end of this training, participants will be able to:
- Install and configure the necessary software, libraries and development environment to begin writing Python code for data analysis.
- Analyze data from sources such as Excel, CSV, JSON files and databases.
- Clean data to improve its usefulness before analyzing it.
- Perform simple statistical analysis.
- Generate reports that present the desired data in just the right format, from straight numbers to data visualizations.
- Gain valuable insight from data, including trends in performance, problematic areas.
21 godzin
This course has been created for business analysts who want to use BPMN 2.0 extensively in their projects.
It focuses on practical aspects of all BPMN 2.0 specification as well as implementations of common patterns.
It is a series of short lectures followed by exercises: the delegates will have a problem described in English, and will have to create a proper diagram for each problem. After that, the diagrams will be discussed and assessed by the group and the trainer.
This course doesn't cover execution part of BPMN, it focuses on analysis and process design aspects of BPMN 2.0.
It focuses on practical aspects of all BPMN 2.0 specification as well as implementations of common patterns.
It is a series of short lectures followed by exercises: the delegates will have a problem described in English, and will have to create a proper diagram for each problem. After that, the diagrams will be discussed and assessed by the group and the trainer.
This course doesn't cover execution part of BPMN, it focuses on analysis and process design aspects of BPMN 2.0.
21 godzin
[R](https://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
7 godzin
This course covers how to use Hive SQL language (AKA: Hive HQL, SQL on Hive, HiveQL) for people who extract data from Hive
21 godzin
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 instructor-led, live 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.
In this instructor-led, live 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.
21 godzin
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
35 godzin
Participants who complete this instructor-led, live training in w Polsce will gain a practical, real-world understanding of Big Data and its related technologies, methodologies and tools.
Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class.
The course starts with an introduction to elemental concepts of Big Data, then progresses into the programming languages and methodologies used to perform Data Analysis. Finally, we discuss the tools and infrastructure that enable Big Data storage, Distributed Processing, and Scalability.
Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class.
The course starts with an introduction to elemental concepts of Big Data, then progresses into the programming languages and methodologies used to perform Data Analysis. Finally, we discuss the tools and infrastructure that enable Big Data storage, Distributed Processing, and Scalability.
14 godzin
This instructor-led, live training in w Polsce is aimed at software developers who wish to build search and analytics solutions using Elasticsearch.
The training starts with a discussion of the Elasticsearch architecture, including its distributed model and search API. This is followed by an explanation of Elasticsearch's functionality and how to best integrate it into an existing application.
Hands-on exercises make up an important part of the training, and give participants a chance to put into practice their knowledge while receiving feedback on their implementation and progress.
The training starts with a discussion of the Elasticsearch architecture, including its distributed model and search API. This is followed by an explanation of Elasticsearch's functionality and how to best integrate it into an existing application.
Hands-on exercises make up an important part of the training, and give participants a chance to put into practice their knowledge while receiving feedback on their implementation and progress.
42 godzin
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 godzin
The aim of this course is to provide a clear understanding of the use of SQL for different
databases (Oracle, SQL Server, MS Access...). Understanding of analytic functions and the
way how to join different tables in a database will help delegates to move data analysis
operations to the database side, instead of doing this in MS Excel application. This can also
help in creating any IT system, which uses any relational database.
databases (Oracle, SQL Server, MS Access...). Understanding of analytic functions and the
way how to join different tables in a database will help delegates to move data analysis
operations to the database side, instead of doing this in MS Excel application. This can also
help in creating any IT system, which uses any relational database.
14 godzin
Apache Kylin is an extreme, distributed analytics engine for big data.
In this instructor-led live training, participants will learn how to use Apache Kylin to set up a real-time data warehouse.
By the end of this training, participants will be able to:
- Consume real-time streaming data using Kylin
- Utilize Apache Kylin's powerful features, rich SQL interface, spark cubing and subsecond query latency
Note
- We use the latest version of Kylin (as of this writing, Apache Kylin v2.0)
Audience
- Big data engineers
- Big Data analysts
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 use Apache Kylin to set up a real-time data warehouse.
By the end of this training, participants will be able to:
- Consume real-time streaming data using Kylin
- Utilize Apache Kylin's powerful features, rich SQL interface, spark cubing and subsecond query latency
Note
- We use the latest version of Kylin (as of this writing, Apache Kylin v2.0)
Audience
- Big data engineers
- Big Data analysts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
14 godzin
Datameer is a business intelligence and analytics platform built on Hadoop. It allows end-users to access, explore and correlate large-scale, structured, semi-structured and unstructured data in an easy-to-use fashion.
In this instructor-led, live training, participants will learn how to use Datameer to overcome Hadoop's steep learning curve as they step through the setup and analysis of a series of big data sources.
By the end of this training, participants will be able to:
- Create, curate, and interactively explore an enterprise data lake
- Access business intelligence data warehouses, transactional databases and other analytic stores
- Use a spreadsheet user-interface to design end-to-end data processing pipelines
- Access pre-built functions to explore complex data relationships
- Use drag-and-drop wizards to visualize data and create dashboards
- Use tables, charts, graphs, and maps to analyze query results
Audience
- Data analysts
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 use Datameer to overcome Hadoop's steep learning curve as they step through the setup and analysis of a series of big data sources.
By the end of this training, participants will be able to:
- Create, curate, and interactively explore an enterprise data lake
- Access business intelligence data warehouses, transactional databases and other analytic stores
- Use a spreadsheet user-interface to design end-to-end data processing pipelines
- Access pre-built functions to explore complex data relationships
- Use drag-and-drop wizards to visualize data and create dashboards
- Use tables, charts, graphs, and maps to analyze query results
Audience
- Data analysts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
14 godzin
Embedding Projector is an open-source web application for visualizing the data used to train machine learning systems. Created by Google, it is part of TensorFlow.
This instructor-led, live training introduces the concepts behind Embedding Projector and walks participants through the setup of a demo project.
By the end of this training, participants will be able to:
- Explore how data is being interpreted by machine learning models
- Navigate through 3D and 2D views of data to understand how a machine learning algorithm interprets it
- Understand the concepts behind Embeddings and their role in representing mathematical vectors for images, words and numerals.
- Explore the properties of a specific embedding to understand the behavior of a model
- Apply Embedding Project to real-world use cases such building a song recommendation system for music lovers
Audience
- Developers
- Data scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
This instructor-led, live training introduces the concepts behind Embedding Projector and walks participants through the setup of a demo project.
By the end of this training, participants will be able to:
- Explore how data is being interpreted by machine learning models
- Navigate through 3D and 2D views of data to understand how a machine learning algorithm interprets it
- Understand the concepts behind Embeddings and their role in representing mathematical vectors for images, words and numerals.
- Explore the properties of a specific embedding to understand the behavior of a model
- Apply Embedding Project to real-world use cases such building a song recommendation system for music lovers
Audience
- Developers
- Data scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
21 godzin
kdb+ is an in-memory, column-oriented database and q is its built-in, interpreted vector-based language. In kdb+, tables are columns of vectors and q is used to perform operations on the table data as if it was a list. kdb+ and q are commonly used in high frequency trading and are popular with the major financial institutions, including Goldman Sachs, Morgan Stanley, Merrill Lynch, JP Morgan, etc.
In this instructor-led, live training, participants will learn how to create a time series data application using kdb+ and q.
By the end of this training, participants will be able to:
- Understand the difference between a row-oriented database and a column-oriented database
- Select data, write scripts and create functions to carry out advanced analytics
- Analyze time series data such as stock and commodity exchange data
- Use kdb+'s in-memory capabilities to store, analyze, process and retrieve large data sets at high speed
- Think of functions and data at a higher level than the standard function(arguments) approach common in non-vector languages
- Explore other time-sensitive applications for kdb+, including energy trading, telecommunications, sensor data, log data, and machine and network usage monitoring
Audience
- Developers
- Database engineers
- Data scientists
- Data analysts
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 create a time series data application using kdb+ and q.
By the end of this training, participants will be able to:
- Understand the difference between a row-oriented database and a column-oriented database
- Select data, write scripts and create functions to carry out advanced analytics
- Analyze time series data such as stock and commodity exchange data
- Use kdb+'s in-memory capabilities to store, analyze, process and retrieve large data sets at high speed
- Think of functions and data at a higher level than the standard function(arguments) approach common in non-vector languages
- Explore other time-sensitive applications for kdb+, including energy trading, telecommunications, sensor data, log data, and machine and network usage monitoring
Audience
- Developers
- Database engineers
- Data scientists
- Data analysts
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
21 godzin
Data science is the application of statistical analysis, machine learning, data visualization and programming for the purpose of understanding and interpreting real-world data. F# is a well suited programming language for data science as it combines efficient execution, REPL-scripting, powerful libraries and scalable data integration.
In this instructor-led, live training, participants will learn how to use F# to solve a series of real-world data science problems.
By the end of this training, participants will be able to:
- Use F#'s integrated data science packages
- Use F# to interoperate with other languages and platforms, including Excel, R, Matlab, and Python
- Use the Deedle package to solve time series problems
- Carry out advanced analysis with minimal lines of production-quality code
- Understand how functional programming is a natural fit for scientific and big data computations
- Access and visualize data with F#
- Apply F# for machine learning
Explore solutions for problems in domains such as business intelligence and social gaming
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 use F# to solve a series of real-world data science problems.
By the end of this training, participants will be able to:
- Use F#'s integrated data science packages
- Use F# to interoperate with other languages and platforms, including Excel, R, Matlab, and Python
- Use the Deedle package to solve time series problems
- Carry out advanced analysis with minimal lines of production-quality code
- Understand how functional programming is a natural fit for scientific and big data computations
- Access and visualize data with F#
- Apply F# for machine learning
Explore solutions for problems in domains such as business intelligence and social gaming
Audience
- Developers
- Data scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
28 godzin
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 godzin
Apache Drill is a schema-free, distributed, in-memory columnar SQL query engine for Hadoop, NoSQL and other Cloud and file storage systems. The power of Apache Drill lies in its ability to join data from multiple data stores using a single query. Apache Drill supports numerous NoSQL databases and file systems, including HBase, MongoDB, MapR-DB, HDFS, MapR-FS, Amazon S3, Azure Blob Storage, Google Cloud Storage, Swift, NAS and local files. Apache Drill is the open source version of Google's Dremel system which is available as an infrastructure service called Google BigQuery.
In this instructor-led, live training, participants will learn the fundamentals of Apache Drill, then leverage the power and convenience of SQL to interactively query big data across multiple data sources, without writing code. Participants will also learn how to optimize their Drill queries for distributed SQL execution.
By the end of this training, participants will be able to:
- Perform "self-service" exploration on structured and semi-structured data on Hadoop
- Query known as well as unknown data using SQL queries
- Understand how Apache Drills receives and executes queries
- Write SQL queries to analyze different types of data, including structured data in Hive, semi-structured data in HBase or MapR-DB tables, and data saved in files such as Parquet and JSON.
- Use Apache Drill to perform on-the-fly schema discovery, bypassing the need for complex ETL and schema operations
- Integrate Apache Drill with BI (Business Intelligence) tools such as Tableau, Qlikview, MicroStrategy and Excel
Audience
- Data analysts
- Data scientists
- SQL programmers
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 Apache Drill, then leverage the power and convenience of SQL to interactively query big data across multiple data sources, without writing code. Participants will also learn how to optimize their Drill queries for distributed SQL execution.
By the end of this training, participants will be able to:
- Perform "self-service" exploration on structured and semi-structured data on Hadoop
- Query known as well as unknown data using SQL queries
- Understand how Apache Drills receives and executes queries
- Write SQL queries to analyze different types of data, including structured data in Hive, semi-structured data in HBase or MapR-DB tables, and data saved in files such as Parquet and JSON.
- Use Apache Drill to perform on-the-fly schema discovery, bypassing the need for complex ETL and schema operations
- Integrate Apache Drill with BI (Business Intelligence) tools such as Tableau, Qlikview, MicroStrategy and Excel
Audience
- Data analysts
- Data scientists
- SQL programmers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
14 godzin
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
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
21 godzin
Dremio is an open-source "self-service data platform" that accelerates the querying of different types of data sources. Dremio integrates with relational databases, Apache Hadoop, MongoDB, Amazon S3, ElasticSearch, and other data sources. It supports SQL and provides a web UI for building queries.
In this instructor-led, live training, participants will learn how to install, configure and use Dremio as a unifying layer for data analysis tools and the underlying data repositories.
By the end of this training, participants will be able to:
- Install and configure Dremio
- Execute queries against multiple data sources, regardless of location, size, or structure
- Integrate Dremio with BI and data sources such as Tableau and Elasticsearch
Audience
- Data scientists
- Business analysts
- Data engineers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Notes
- To request a customized training for this course, please contact us to arrange.
In this instructor-led, live training, participants will learn how to install, configure and use Dremio as a unifying layer for data analysis tools and the underlying data repositories.
By the end of this training, participants will be able to:
- Install and configure Dremio
- Execute queries against multiple data sources, regardless of location, size, or structure
- Integrate Dremio with BI and data sources such as Tableau and Elasticsearch
Audience
- Data scientists
- Business analysts
- Data engineers
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Notes
- To request a customized training for this course, please contact us to arrange.
14 godzin
A business' marketing strategy is one of its most essential tools to ensure success. The rise in technology and advances in data gathering and analysis has led to a continuous transformation of marketing. Data analysis is now considered to be a crucial skill for marketers to learn. Likewise, applying data science to marketing principles is also important in helping data science professionals maximize their contributions.
In this instructor-led, live training, participants will learn how to gain valuable insights from large data sets and how to use these for marketing strategies.
By the end of this training, participants will be able to:
- Install and configure tools for data-driven marketing tools (Tableau, Google Analytics, Zarget, etc)
- Measure, test, and optimize the performance of their marketing strategies using data
- Use data to segment their customers and prospects
- Use predictive modeling to improve response rates
- Implement step-by-step data analytics to drive better marketing decisions
Audience
- Marketers
- 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.
In this instructor-led, live training, participants will learn how to gain valuable insights from large data sets and how to use these for marketing strategies.
By the end of this training, participants will be able to:
- Install and configure tools for data-driven marketing tools (Tableau, Google Analytics, Zarget, etc)
- Measure, test, and optimize the performance of their marketing strategies using data
- Use data to segment their customers and prospects
- Use predictive modeling to improve response rates
- Implement step-by-step data analytics to drive better marketing decisions
Audience
- Marketers
- 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.
35 godzin
Participants who complete this training will gain a practical, real-world understanding of Data Science and its related technologies, methodologies and tools.
Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class.
The course starts with an introduction to elemental concepts of Data Science, then progresses into the tools and methodologies used in Data Science.
Audience
- Developers
- Technical analysts
- IT consultants
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.
Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class.
The course starts with an introduction to elemental concepts of Data Science, then progresses into the tools and methodologies used in Data Science.
Audience
- Developers
- Technical analysts
- IT consultants
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.
Last Updated:
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Konsultacje
Szkolenie Data Analysis, Data Analysis boot camp, Szkolenia Zdalne Data Analysis, szkolenie wieczorowe Data Analysis, szkolenie weekendowe Data Analysis, Kurs Data Analysis,Kursy Data Analysis, Trener Data Analysis, instruktor Data Analysis, kurs zdalny Data Analysis, edukacja zdalna Data Analysis, nauczanie wirtualne Data Analysis, lekcje UML, nauka przez internet Data Analysis, e-learning Data Analysis, kurs online Data Analysis, wykładowca Data Analysis
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