Kraków

Archeion, Św. Filipa 23/6, Kraków, Polska, 30-636

Sale szkoleniowe znajdują się przy ul. Św. Filipa 23/6 w Krakowie, zaledwie 3 minuty od dworca PKP, w s...

Tarnów

Hotel Tarnovia, Kościuszki 10, Tarnów, Polska, 33-100

Sala szkoleniowa NobleProg jest usytuowana w hotelu Tarnovia przy ulicy Kościuszki 10 w Ta...

Zakopane

Dafne, Jagiellońska 30, Zakopane, Polska, 34-500

Sala szkoleniowa jest zlokalizowana zaledwie 350 metrów od dworców PKP i PKS oraz 700 metrów od Krupów...

Subcategories (3)

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Apache Spark MLlib
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PySpark

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Python, Spark, and Hadoop for Big Data

21 godzin
Python is a scalable, flexible, and widely used programming language for data science and machine learning. Spark is a data processing engine used in querying, analyzing, and transforming big data, while Hadoop is a software library framework for large-scale data storage and processing. This instructor-led, live training (online or onsite) is aimed at developers who wish to use and integrate Spark, Hadoop, and Python to process, analyze, and transform large and complex data sets. By the end of this training, participants will be able to:
  • Set up the necessary environment to start processing big data with Spark, Hadoop, and Python.
  • Understand the features, core components, and architecture of Spark and Hadoop.
  • Learn how to integrate Spark, Hadoop, and Python for big data processing.
  • Explore the tools in the Spark ecosystem (Spark MlLib, Spark Streaming, Kafka, Sqoop, Kafka, and Flume).
  • Build collaborative filtering recommendation systems similar to Netflix, YouTube, Amazon, Spotify, and Google.
  • Use Apache Mahout to scale machine learning algorithms.
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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Administration of Apache Spark

35 godzin
Apache Spark is an open-source, unified analytics engine for large-scale data processing.This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level system administrators who wish to deploy, maintain, and optimize Spark clusters.By the end of this training, participants will be able to:
  • Install and configure Apache Spark in various environments.
  • Manage cluster resources and monitor Spark applications.
  • Optimize the performance of Spark clusters.
  • Implement security measures and ensure high availability.
  • Debug and troubleshoot common Spark issues.
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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Python and Spark for Big Data (PySpark)

21 godzin
Python is a high-level programming language famous for its clear syntax and code readibility. Spark is a data processing engine used in querying, analyzing, and transforming big data. PySpark allows users to interface Spark with Python. In this instructor-led, live training, participants will learn how to use Python and Spark together to analyze big data as they work on hands-on exercises. By the end of this training, participants will be able to:
  • Learn how to use Spark with Python to analyze Big Data.
  • Work on exercises that mimic real world cases.
  • Use different tools and techniques for big data analysis using PySpark.
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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Big Data Analytics in Health

21 godzin
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.
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Hadoop and Spark for Administrators

35 godzin
Apache Hadoop is a popular data processing framework for processing large data sets across many computers. This instructor-led, live training (online or onsite) is aimed at system administrators who wish to learn how to set up, deploy and manage Hadoop clusters within their organization. By the end of this training, participants will be able to:
  • Install and configure Apache Hadoop.
  • Understand the four major components in the Hadoop ecoystem: HDFS, MapReduce, YARN, and Hadoop Common.
  • Use Hadoop Distributed File System (HDFS) to scale a cluster to hundreds or thousands of nodes.  
  • Set up HDFS to operate as storage engine for on-premise Spark deployments.
  • Set up Spark to access alternative storage solutions such as Amazon S3 and NoSQL database systems such as Redis, Elasticsearch, Couchbase, Aerospike, etc.
  • Carry out administrative tasks such as provisioning, management, monitoring and securing an Apache Hadoop cluster.
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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Hortonworks Data Platform (HDP) for Administrators

21 godzin
Hortonworks Data Platform (HDP) is an open-source Apache Hadoop support platform that provides a stable foundation for developing big data solutions on the Apache Hadoop ecosystem. This instructor-led, live training (online or onsite) introduces Hortonworks Data Platform (HDP) and walks participants through the deployment of Spark + Hadoop solution. By the end of this training, participants will be able to:
  • Use Hortonworks to reliably run Hadoop at a large scale.
  • Unify Hadoop's security, governance, and operations capabilities with Spark's agile analytic workflows.
  • Use Hortonworks to investigate, validate, certify and support each of the components in a Spark project.
  • Process different types of data, including structured, unstructured, in-motion, and at-rest.
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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A Practical Introduction to Stream Processing

21 godzin
Stream Processing refers to the real-time processing of "data in motion", that is, performing computations on data as it is being received. Such data is read as continuous streams from data sources such as sensor events, website user activity, financial trades, credit card swipes, click streams, etc. Stream Processing frameworks are able to read large volumes of incoming data and provide valuable insights almost instantaneously. In this instructor-led, live training (onsite or remote), participants will learn how to set up and integrate different Stream Processing frameworks with existing big data storage systems and related software applications and microservices. By the end of this training, participants will be able to:
  • Install and configure different Stream Processing frameworks, such as Spark Streaming and Kafka Streaming.
  • Understand and select the most appropriate framework for the job.
  • Process of data continuously, concurrently, and in a record-by-record fashion.
  • Integrate Stream Processing solutions with existing databases, data warehouses, data lakes, etc.
  • Integrate the most appropriate stream processing library with enterprise applications and microservices.
Audience
  • Developers
  • Software architects
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.
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Magellan: Geospatial Analytics on Spark

14 godzin
Magellan is an open-source distributed execution engine for geospatial analytics on big data. Implemented on top of Apache Spark, it extends Spark SQL and provides a relational abstraction for geospatial analytics. This instructor-led, live training introduces the concepts and approaches for implementing geospacial analytics and walks participants through the creation of a predictive analysis application using Magellan on Spark. By the end of this training, participants will be able to:
  • Efficiently query, parse and join geospatial datasets at scale
  • Implement geospatial data in business intelligence and predictive analytics applications
  • Use spatial context to extend the capabilities of mobile devices, sensors, logs, and wearables
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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Apache Spark for .NET Developers

21 godzin
Apache Spark is a distributed processing engine for analyzing very large data sets. It can process data in batches and real-time, as well as carry out machine learning, ad-hoc queries, and graph processing. .NET for Apache Spark is a free, open-source, and cross-platform big data analytics framework that supports applications written in C# or F#. This instructor-led, live training (online or onsite) is aimed at developers who wish to carry out big data analysis using Apache Spark in their .NET applications. By the end of this training, participants will be able to:
  • Install and configure Apache Spark.
  • Understand how .NET implements Spark APIs so that they can be accessed from a .NET application.
  • Develop data processing applications using C# or F#, capable of handling data sets whose size is measured in terabytes and pedabytes.
  • Develop machine learning features for a .NET application using Apache Spark capabilities.
  • Carry out exploratory analysis using SQL queries on big data sets.
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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SMACK Stack for Data Science

14 godzin
SMACK is a collection of data platform softwares, namely Apache Spark, Apache Mesos, Apache Akka, Apache Cassandra, and Apache Kafka. Using the SMACK stack, users can create and scale data processing platforms. This instructor-led, live training (online or onsite) is aimed at data scientists who wish to use the SMACK stack to build data processing platforms for big data solutions. By the end of this training, participants will be able to:
  • Implement a data pipeline architecture for processing big data.
  • Develop a cluster infrastructure with Apache Mesos and Docker.
  • Analyze data with Spark and Scala.
  • Manage unstructured data with Apache Cassandra.
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.
Więcej...

Apache Spark Fundamentals

21 godzin
Apache Spark is an analytics engine designed to distribute data across a cluster in order to process it in parallel. It contains modules for streaming, SQL, machine learning and graph processing. This instructor-led, live training (online or onsite) is aimed at engineers who wish to deploy Apache Spark system for processing very large amounts of data. By the end of this training, participants will be able to:
  • Install and configure Apache Spark.
  • Understand the difference between Apache Spark and Hadoop MapReduce and when to use which.
  • Quickly read in and analyze very large data sets.
  • Integrate Apache Spark with other machine learning tools.
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.
Więcej...

Apache Spark in the Cloud

21 godzin
Apache Spark's learning curve is slowly increasing at the begining, it needs a lot of effort to get the first return. This course aims to jump through the first tough part. After taking this course the participants will understand the basics of Apache Spark , they will clearly differentiate RDD from DataFrame, they will learn Python and Scala API, they will understand executors and tasks, etc.  Also following the best practices, this course strongly focuses on cloud deployment, Databricks and AWS. The students will also understand the differences between AWS EMR and AWS Glue, one of the lastest Spark service of AWS.     AUDIENCE: Data Engineer, DevOps, Data Scientist
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Spark for Developers

21 godzin
OBJECTIVE: This course will introduce Apache Spark. The students will learn how  Spark fits  into the Big Data ecosystem, and how to use Spark for data analysis.  The course covers Spark shell for interactive data analysis, Spark internals, Spark APIs, Spark SQL, Spark streaming, and machine learning and graphX. AUDIENCE : Developers / Data Analysts
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Scaling Data Pipelines with Spark NLP

14 godzin
Spark NLP is an open source library, built on Apache Spark, for natural language processing with Python, Java, and Scala. It is widely used for enterprise and industry verticals, such as healthcare, finance, life science, and recruiting. This instructor-led, live training (online or onsite) is aimed at data scientists and developers who wish to use Spark NLP, built on top of Apache Spark, to develop, implement, and scale natural language text processing models and pipelines. By the end of this training, participants will be able to:
  • Set up the necessary development environment to start building NLP pipelines with Spark NLP.
  • Understand the features, architecture, and benefits of using Spark NLP.
  • Use the pre-trained models available in Spark NLP to implement text processing.
  • Learn how to build, train, and scale Spark NLP models for production-grade projects.
  • Apply classification, inference, and sentiment analysis on real-world use cases (clinical data, customer behavior insights, etc.).
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.
Więcej...

Apache Spark Streaming with Scala

21 godzin
Scala is a condensed version of Java for large scale functional and object-oriented programming. Apache Spark Streaming is an extended component of the Spark API for processing big data sets as real-time streams. Together, Spark Streaming and Scala enable the streaming of big data. This instructor-led, live training (online or onsite) is aimed at software engineers who wish to stream big data with Spark Streaming and Scala. By the end of this training, participants will be able to:
  • Create Spark applications with the Scala programming language.
  • Use Spark Streaming to process continuous streams of data.
  • Process streams of real-time data with Spark Streaming.
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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Apache Spark SQL

7 godzin
Spark SQL is Apache Spark's module for working with structured and unstructured data. Spark SQL provides information about the structure of the data as well as the computation being performed. This information can be used to perform optimizations. Two common uses for Spark SQL are:
- to execute SQL queries.
- to read data from an existing Hive installation. In this instructor-led, live training (onsite or remote), participants will learn how to analyze various types of data sets using Spark SQL. By the end of this training, participants will be able to:
  • Install and configure Spark SQL.
  • Perform data analysis using Spark SQL.
  • Query data sets in different formats.
  • Visualize data and query results.
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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Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP

21 godzin
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.
Więcej...

Apache Spark MLlib

35 godzin
MLlib is Spark’s machine learning (ML) library. Its goal is to make practical machine learning scalable and easy. It consists of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, as well as lower-level optimization primitives and higher-level pipeline APIs. It divides into two packages:
  • spark.mllib contains the original API built on top of RDDs.
  • spark.ml provides higher-level API built on top of DataFrames for constructing ML pipelines.
  Audience This course is directed at engineers and developers seeking to utilize a built in Machine Library for Apache Spark
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Introduction to Graph Computing

28 godzin
Many real world problems can be described in terms of graphs. For example, the Web graph, the social network graph, the train network graph and the language graph. These graphs tend to be extremely large; processing them requires a specialized set of tools and processes -- these tools and processes can be referred to as Graph Computing (also known as Graph Analytics). In this instructor-led, live training, participants will learn about the technology offerings and implementation approaches for processing graph data. The aim is to identify real-world objects, their characteristics and relationships, then model these relationships and process them as data using a Graph Computing (also known as Graph Analytics and Distributed Graph Processing) approach. We start with a broad overview and narrow in on specific tools as we step through a series of case studies, hands-on exercises and live deployments. By the end of this training, participants will be able to:
  • Understand how graph data is persisted and traversed.
  • Select the best framework for a given task (from graph databases to batch processing frameworks.)
  • Implement Hadoop, Spark, GraphX and Pregel to carry out graph computing across many machines in parallel.
  • View real-world big data problems in terms of graphs, processes and traversals.
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
Więcej...

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Opinie uczestników (22)

The VM I liked very much The Teacher was very knowledgeable regarding the topic as well as other topics, he was very nice and friendly I liked the facility in Dubai.

Safar Alqahtani - Elm Information Security
Szkolenie - Big Data Analytics in Health

Sufficient hands on, trainer is knowledgable

Chris Tan
Szkolenie - A Practical Introduction to Stream Processing

very interactive...

Richard Langford
Szkolenie - SMACK Stack for Data Science

Zaangażowanie i chęć wyjaśnienia tematów pobocznych.

Marek - Krajowy Rejestr Długów Biuro Informacji Gospodarczej S.A.
Szkolenie - Apache Spark Fundamentals

Doświadczenie praktyczne trenera, nie koloryzowanie omawianego rozwiązania ale też nie wprowadzanie negatywnego nacechowania. Mam poczucie, że trener przygotowuje mnie do realnego i praktycznego wykorzystania narzędzia - tych cennych szczegółów nie ma zazwyczaj w książkach.

Krzysztof Miodek - Krajowy Rejestr Długów Biuro Informacji Gospodarczej S.A.
Szkolenie - Apache Spark Fundamentals

Having hands on session / assignments

Poornima Chenthamarakshan - Intelligent Medical Objects
Szkolenie - Apache Spark in the Cloud

1. Right balance between high level concepts and technical details. 2. Andras is very knowledgeable about his teaching. 3. Exercise

Steven Wu - Intelligent Medical Objects
Szkolenie - Apache Spark in the Cloud

Wszystko ok.

Marek Siódmiak - Santander Bank Polska
Szkolenie - Spark for Developers

Doing similar exercises different ways really help understanding what each component (Hadoop/Spark, standalone/cluster) can do on its own and together. It gave me ideas on how I should test my application on my local machine when I develop vs when it is deployed on a cluster.

Thomas Carcaud - IT Frankfurt GmbH
Szkolenie - Spark for Developers

Ajay was very friendly, helpful and also knowledgable about the topic he was discussing.

Biniam Guulay - ICE International Copyright Enterprise Germany GmbH
Szkolenie - Spark for Developers

Ernesto did a great job explaining the high level concepts of using Spark and it's various modules.

Michael Nemerouf
Szkolenie - Spark for Developers

Exercises and exchanges during questions/answers

Antoine - Physiobotic
Szkolenie - Scaling Data Pipelines with Spark NLP

The good humor, support and skills of the trainer.

Oumayma - Physiobotic
Szkolenie - Scaling Data Pipelines with Spark NLP

The fact that we were able to take with us most of the information/course/presentation/exercises done, so that we can look over them and perhaps redo what we didint understand first time or improve what we already did.

Raul Mihail Rat - Accenture Industrial SS
Szkolenie - Python, Spark, and Hadoop for Big Data

I liked that it managed to lay the foundations of the topic and go to some quite advanced exercises. Also provided easy ways to write/test the code.

Ionut Goga - Accenture Industrial SS
Szkolenie - Python, Spark, and Hadoop for Big Data

This is one of the best hands-on with exercises programming courses I have ever taken.

Laura Kahn
Szkolenie - Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP

A lot of practical examples, different ways to approach the same problem, and sometimes not so obvious tricks how to improve the current solution

Rafał - Nordea
Szkolenie - Apache Spark MLlib

I liked that it was practical. Loved to apply the theoretical knowledge with practical examples.

Aurelia-Adriana - Allianz Services Romania
Szkolenie - Python and Spark for Big Data (PySpark)

Łatwość komunikacji i materiały.

Michał - summ-it s.a.
Szkolenie - Python and Spark for Big Data (PySpark)

Kontakt z prowadzącą, wiedza prowadzącej

Jakub - summ-it s.a.
Szkolenie - Python and Spark for Big Data (PySpark)

dużo praktycznych przykładów, na rzeczywistych danych

Tomasz Bronk-Zdunowski - ZF Automotive Systems Poland sp. z o.o.
Szkolenie - Python and Spark for Big Data (PySpark)

The course was about a series of very complex related topics & Pablo has in-depth expertise of each of them. Sometimes nuances were lost in communication and/or due to time pressures and possibly expectations were not quite met due to this. Also there were some UHG/Azure Databricks setup issues however Pablo / UHG resolved these quickly once they became apparent - this to me showed a high level of understanding and professionalism between UHG & Pablo,

Michael Monks - Tech NorthWest Skillnet
Szkolenie - Python and Spark for Big Data (PySpark)

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Apache Spark Konsultacje
Szkolenie Apache Spark małopolskie, szkolenie wieczorowe Spark małopolskie, szkolenie weekendowe Apache Spark małopolskie, Apache Spark boot camp małopolskie, kurs zdalny Apache Spark małopolskie, wykładowca Spark małopolskie, nauka przez internet Apache Spark małopolskie, nauczanie wirtualne Spark małopolskie, kurs online Spark małopolskie, instruktor Apache Spark małopolskie, lekcje Spark małopolskie, Kursy Spark małopolskie, edukacja zdalna Apache Spark małopolskie, Kurs Spark małopolskie, Trener Apache Spark małopolskie
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