Szkolenia Big Data

BigData to termin używany w odniesieniu do rozwiązań przeznaczonych do przechowywania i przetwarzania dużych zbiorów danych. Rozwiązania typu BigData zostały zainicjowane przez firmę Google, jakkolwiek obecnie dostępnych jest wiele rozwiązań typu open-source takich jak Apache Hadoop, Cassandra czy Cloudera Impala. Zgodnie z raportami publikowanymi przez firmę Gartner BigData jest kolejnym wielkim krokiem w branży IT, zaraz po rozwiązaniach opartych na chmurze obliczeniowej, i będzie wiodącym trendem przez kilka najbliższych lat.

Opinie uczestników

★★★★★

Podkategorie

Apache ActiveMQ

Apache Drill

Apache Spark

Apache ZooKeeper

Avro

Dremio

Graph Computing

Hadoop

PySpark

Plany Kursów

Kod	Nazwa	Czas trwania	Charakterystyka kursu
mdlmrah	Model MapReduce w implementacji oprogramowania Apache Hadoop	14 godz.	Szkolenie skierowane jest do organizacji chcących wdrożyć rozwiązania pozwalające na przetwarzanie dużych zbiorów danych za pomocą klastrów.
pjfs	Programowanie w języku F#	7 godz.	Szkolenie skierowane jest do programistów, analityków oraz osób chcących poznać podstawy i możliwości języka F# w oparciu o platformę .NET.
solrdev	Solr for Developers	21 godz.	This course introduces students to the Solr platform. Through a combination of lecture, discussion and labs students will gain hands on experience configuring effective search and indexing. The class begins with basic Solr installation and configuration then teaches the attendees the search features of Solr. Students will gain experience with faceting, indexing and search relevance among other features central to the Solr platform. The course wraps up with a number of advanced topics including spell checking, suggestions, Multicore and SolrCloud. Duration: 3 days Audience: Developers, business users, administrators
dmmlr	Data Mining & Machine Learning 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.
TalendDI	Talend Open Studio for Data Integration	28 godz.	Talend Open Studio for Data Integration is an open-source data integration product used to combine, convert and update data in various locations across a business. In this instructor-led, live training, participants will learn how to use the Talend ETL tool to carry out data transformation, data extraction, and connectivity with Hadoop, Hive, and Pig. By the end of this training, participants will be able to Explain the concepts behind ETL (Extract, Transform, Load) and propagation Define ETL methods and ETL tools to connect with Hadoop Efficiently amass, retrieve, digest, consume, transform and shape big data in accordance to business requirements Upload to and extract large records from Hadoop (optional), Hive (optional), and NoSQL databases Audience Business intelligence professionals Project managers Database professionals SQL Developers ETL Developers Solution architects Data architects Data warehousing professionals System administrators and integrators 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.
hypertable	Hypertable: Deploy a BigTable like database	14 godz.	Hypertable is an open-source software database management system based on the design of Google's Bigtable. In this instructor-led, live training, participants will learn how to set up and manage a Hypertable database system. By the end of this training, participants will be able to: Install, configure and upgrade a Hypertable instance Set up and administer a Hypertable cluster Monitor and optimize the performance of the database Design a Hypertable schema Work with Hypertable's API Troubleshoot operational issues Audience Developers Operations engineers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Part lecture, part discussion, exercises and heavy hands-on practice
beam	Unified Batch and Stream Processing with Apache Beam	14 godz.	Apache Beam is an open source, unified programming model for defining and executing parallel data processing pipelines. It's power lies in its ability to run both batch and streaming pipelines, with execution being carried out by one of Beam's supported distributed processing back-ends: Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow. Apache Beam is useful for ETL (Extract, Transform, and Load) tasks such as moving data between different storage media and data sources, transforming data into a more desirable format, and loading data onto a new system. In this instructor-led, live training (onsite or remote), participants will learn how to implement the Apache Beam SDKs in a Java or Python application that defines a data processing pipeline for decomposing a big data set into smaller chunks for independent, parallel processing. By the end of this training, participants will be able to: Install and configure Apache Beam. Use a single programming model to carry out both batch and stream processing from withing their Java or Python application. Execute pipelines across multiple environments. Audience Developers Format of the Course Part lecture, part discussion, exercises and heavy hands-on practice Note This course will be available Scala in the future. Please contact us to arrange.
bdbitcsp	Big Data Business Intelligence for Telecom & Communication Service Providers	35 godz.	Overview Communications service providers (CSP) are facing pressure to reduce costs and maximize average revenue per user (ARPU), while ensuring an excellent customer experience, but data volumes keep growing. Global mobile data traffic will grow at a compound annual growth rate (CAGR) of 78 percent to 2016, reaching 10.8 exabytes per month. Meanwhile, CSPs are generating large volumes of data, including call detail records (CDR), network data and customer data. Companies that fully exploit this data gain a competitive edge. According to a recent survey by The Economist Intelligence Unit, companies that use data-directed decision-making enjoy a 5-6% boost in productivity. Yet 53% of companies leverage only half of their valuable data, and one-fourth of respondents noted that vast quantities of useful data go untapped. The data volumes are so high that manual analysis is impossible, and most legacy software systems can’t keep up, resulting in valuable data being discarded or ignored. With Big Data & Analytics’ high-speed, scalable big data software, CSPs can mine all their data for better decision making in less time. Different Big Data products and techniques provide an end-to-end software platform for collecting, preparing, analyzing and presenting insights from big data. Application areas include network performance monitoring, fraud detection, customer churn detection and credit risk analysis. Big Data & Analytics products scale to handle terabytes of data but implementation of such tools need new kind of cloud based database system like Hadoop or massive scale parallel computing processor ( KPU etc.) This course work on Big Data BI for Telco covers all the emerging new areas in which CSPs are investing for productivity gain and opening up new business revenue stream. The course will provide a complete 360 degree over view of Big Data BI in Telco so that decision makers and managers can have a very wide and comprehensive overview of possibilities of Big Data BI in Telco for productivity and revenue gain. Course objectives Main objective of the course is to introduce new Big Data business intelligence techniques in 4 sectors of Telecom Business (Marketing/Sales, Network Operation, Financial operation and Customer Relation Management). Students will be introduced to following: Introduction to Big Data-what is 4Vs (volume, velocity, variety and veracity) in Big Data- Generation, extraction and management from Telco perspective How Big Data analytic differs from legacy data analytic In-house justification of Big Data -Telco perspective Introduction to Hadoop Ecosystem- familiarity with all Hadoop tools like Hive, Pig, SPARC –when and how they are used to solve Big Data problem How Big Data is extracted to analyze for analytics tool-how Business Analysis’s can reduce their pain points of collection and analysis of data through integrated Hadoop dashboard approach Basic introduction of Insight analytics, visualization analytics and predictive analytics for Telco Customer Churn analytic and Big Data-how Big Data analytic can reduce customer churn and customer dissatisfaction in Telco-case studies Network failure and service failure analytics from Network meta-data and IPDR Financial analysis-fraud, wastage and ROI estimation from sales and operational data Customer acquisition problem-Target marketing, customer segmentation and cross-sale from sales data Introduction and summary of all Big Data analytic products and where they fit into Telco analytic space Conclusion-how to take step-by-step approach to introduce Big Data Business Intelligence in your organization Target Audience Network operation, Financial Managers, CRM managers and top IT managers in Telco CIO office. Business Analysts in Telco CFO office managers/analysts Operational managers QA managers
datamin	Data Mining	21 godz.	Course can be provided with any tools, including free open-source data mining software and applications
sparkdev	Spark for Developers	21 godz.	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
rprogda	R Programming for Data Analysis	14 godz.	This course is part of the Data Scientist skill set (Domain: Data and Technology)
pythonmultipurpose	Advanced Python	28 godz.	In this instructor-led training, 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. Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Notes If you wish to add, remove or customize any section or topic within this course, please contact us to arrange.
nifi	Apache NiFi for Administrators	21 godz.	Apache NiFi (Hortonworks DataFlow) is a real-time integrated data logistics and simple event processing platform that enables the moving, tracking and automation of data between systems. It is written using flow-based programming and provides a web-based user interface to manage dataflows in real time. In this instructor-led, live training, participants will learn how to deploy and manage Apache NiFi in a live lab environment. By the end of this training, participants will be able to: Install and configure Apachi NiFi Source, transform and manage data from disparate, distributed data sources, including databases and big data lakes Automate dataflows Enable streaming analytics Apply various approaches for data ingestion Transform Big Data and into business insights Audience System administrators Data engineers Developers DevOps Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
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.
bdbiga	Big Data Business Intelligence for Govt. Agencies	35 godz.	Advances in technologies and the increasing amount of information are transforming how business is conducted in many industries, including government. Government data generation and digital archiving rates are on the rise due to the rapid growth of mobile devices and applications, smart sensors and devices, cloud computing solutions, and citizen-facing portals. As digital information expands and becomes more complex, information management, processing, storage, security, and disposition become more complex as well. New capture, search, discovery, and analysis tools are helping organizations gain insights from their unstructured data. The government market is at a tipping point, realizing that information is a strategic asset, and government needs to protect, leverage, and analyze both structured and unstructured information to better serve and meet mission requirements. As government leaders strive to evolve data-driven organizations to successfully accomplish mission, they are laying the groundwork to correlate dependencies across events, people, processes, and information. High-value government solutions will be created from a mashup of the most disruptive technologies: Mobile devices and applications Cloud services Social business technologies and networking Big Data and analytics IDC predicts that by 2020, the IT industry will reach $5 trillion, approximately $1.7 trillion larger than today, and that 80% of the industry's growth will be driven by these 3rd Platform technologies. In the long term, these technologies will be key tools for dealing with the complexity of increased digital information. Big Data is one of the intelligent industry solutions and allows government to make better decisions by taking action based on patterns revealed by analyzing large volumes of data — related and unrelated, structured and unstructured. But accomplishing these feats takes far more than simply accumulating massive quantities of data.“Making sense of these volumes of Big Data requires cutting-edge tools and technologies that can analyze and extract useful knowledge from vast and diverse streams of information,” Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy wrote in a post on the OSTP Blog. The White House took a step toward helping agencies find these technologies when it established the National Big Data Research and Development Initiative in 2012. The initiative included more than $200 million to make the most of the explosion of Big Data and the tools needed to analyze it. The challenges that Big Data poses are nearly as daunting as its promise is encouraging. Storing data efficiently is one of these challenges. As always, budgets are tight, so agencies must minimize the per-megabyte price of storage and keep the data within easy access so that users can get it when they want it and how they need it. Backing up massive quantities of data heightens the challenge. Analyzing the data effectively is another major challenge. Many agencies employ commercial tools that enable them to sift through the mountains of data, spotting trends that can help them operate more efficiently. (A recent study by MeriTalk found that federal IT executives think Big Data could help agencies save more than $500 billio while also fulfilling mission objectives.). Custom-developed Big Data tools also are allowing agencies to address the need to analyze their data. For example, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. The system has helped medical researchers find a link that can alert doctors to aortic aneurysms before they strike. It’s also used for more mundane tasks, such as sifting through résumés to connect job candidates with hiring managers.
smtwebint	Semantic Web Overview	7 godz.	The Semantic Web is a collaborative movement led by the World Wide Web Consortium (W3C) that promotes common formats for data on the World Wide Web. The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries.
hbasedev	HBase for Developers	21 godz.	This course introduces HBase – a NoSQL store on top of Hadoop. The course is intended for developers who will be using HBase to develop applications, and administrators who will manage HBase clusters. We will walk a developer through HBase architecture and data modelling and application development on HBase. It will also discuss using MapReduce with HBase, and some administration topics, related to performance optimization. The course is very hands-on with lots of lab exercises. Duration : 3 days Audience : Developers & Administrators
bigddbsysfun	Big Data & Database Systems Fundamentals	14 godz.	The course is part of the Data Scientist skill set (Domain: Data and Technology).
PentahoDI	Pentaho Data Integration Fundamentals	21 godz.	Pentaho Data Integration is an open-source data integration tool for defining jobs and data transformations. In this instructor-led, live training, participants will learn how to use Pentaho Data Integration's powerful ETL capabilities and rich GUI to manage an entire big data lifecycle, maximizing the value of data to the organization. By the end of this training, participants will be able to: Create, preview, and run basic data transformations containing steps and hops Configure and secure the Pentaho Enterprise Repository Harness disparate sources of data and generate a single, unified version of the truth in an analytics-ready format. Provide results to third-part applications for further processing Audience Data Analyst ETL developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
nifidev	Apache NiFi for Developers	7 godz.	Apache NiFi (Hortonworks DataFlow) is a real-time integrated data logistics and simple event processing platform that enables the moving, tracking and automation of data between systems. It is written using flow-based programming and provides a web-based user interface to manage dataflows in real time. In this instructor-led, live training, participants will learn the fundamentals of flow-based programming as they develop a number of demo extensions, components and processors using Apache NiFi. By the end of this training, participants will be able to: Understand NiFi's architecture and dataflow concepts Develop extensions using NiFi and third-party APIs Custom develop their own Apache Nifi processor Ingest and process real-time data from disparate and uncommon file formats and data sources Audience Developers Data engineers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
apachejena	Apache Jena: Creating a Semantic Web Application	21 godz.	Apache Jena is an open source Java framework for building Semantic Web and Linked Data applications. In this instructor-led, live training, participants will learn how to use Apache Jena to build and deploy a Semantic Web Application. By the end of this training, participants will be able to: Install and configure Apache Jena Convert and store data in RDF format Query RDF data using SPARQL Test and deploy a semantic web application Audience Developers Data Engineers 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.
iotemi	IoT (Internet of Things) for Entrepreneurs, Managers and Investors	21 godz.	Estimates for Internet of Things or IoT market value are massive, since by definition the IoT is an integrated and diffused layer of devices, sensors, and computing power that overlays entire consumer, business-to-business, and government industries. The IoT will account for an increasingly huge number of connections: 1.9 billion devices today, and 9 billion by 2018. That year, it will be roughly equal to the number of smartphones, smart TVs, tablets, wearable computers, and PCs combined. In the consumer space, many products and services have already crossed over into the IoT, including kitchen and home appliances, parking, RFID, lighting and heating products, and a number of applications in Industrial Internet. However the underlying technologies of IoT are nothing new as M2M communication existed since the birth of Internet. However what changed in last couple of years is the emergence of number of inexpensive wireless technologies added by overwhelming adaptation of smart phones and Tablet in every home. Explosive growth of mobile devices led to present demand of IoT. Due to unbounded opportunities in IoT business, a large number of small and medium sized entrepreneurs jumped into bandwagon of IoT gold rush. Also due to emergence of open source electronics and IoT platform, cost of development of IoT system and further managing its sizeable production is increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their device with Internet or Mobile app. This training is intended for a technology and business review of an emerging industry so that IoT enthusiasts/entrepreneurs can grasp the basics of IoT technology and business. Course objectives Main objective of the course is to introduce emerging technological options, platforms and case studies of IoT implementation in home & city automation (smart homes and cities), Industrial Internet, healthcare, Govt., Mobile Cellular and other areas. Basic introduction of all the elements of IoT-Mechanical, Electronics/sensor platform, Wireless and wireline protocols, Mobile to Electronics integration, Mobile to enterprise integration, Data-analytics and Total control plane. M2M Wireless protocols for IoT- WiFi, Zigbee/Zwave, Bluetooth, ANT+ : When and where to use which one? Mobile/Desktop/Web app- for registration, data acquisition and control –Available M2M data acquisition platform for IoT-–Xively, Omega and NovoTech, etc. Security issues and security solutions for IoT Open source/commercial electronics platform for IoT-Rasberry Pi, Adruino , ArmMbedLPC etc Open source /commercial enterprise cloud platform for IoT-Ayla, iO Bridge, Libellium, Axeda, Cisco frog cloud Studies of business and technology of some of the common IoT devices like Home automation, Smoke alarm, vehicles, military, home health etc. Target Audience Investors and IoT entrepreneurs Managers and Engineers whose company is venturing into IoT space Business Analysts & Investors
wdneo4j	Wprowadzenie do Neo4j - grafowej bazy danych	7 godz.
bdhat	Big Data Hadoop Analyst Training	28 godz.	Big Data Analyst Training to praktyczny kurs, który polecany jest każdemu, kto chce w przyszłości zostać ekspertem Data Scientist. Kurs skupia sie na aspektach potrzebnych do pracy nowoczesnego analityka w technologii Big Data. W trakcie kursu prezentowane są narzędzia pozwalające na uzyskanie dostępu, zmianę, transformację i analizę skomplikowanych struktur danych umieszczonych w klastrze Hadoop. W trakcie kursu będą poruszane tematy w ramach technologii Hadoop Ecosystem (Pig, Hive, Impala, ELK i inne). Funkcjonaloność narzędzi Pig, Hive, Impala, ELK, pozwalające na zbieranie danych, zapisywanie wyników i analitykę. Jak Pig, Hive i Impala mogą podnieść wydajność typowych i codziennych zadań analitycznych. Wykonywanie w czasie rzeczywistym interaktywnych analiz ogromnych zbiorów danych aby uzyskać cenne i wartościowe elementy dla biznesu oraz jak interpretować wnioski. Wykonywanie złożonych zapytań na bardzo dużych wolumenach danych.
rintrob	Introductory R for Biologists	28 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 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.
hdp	Hortonworks Data Platform (HDP) for administrators	21 godz.	Hortonworks Data Platform 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 introduces Hortonworks 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. Audience Hadoop administrators Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
graphcomputing	Introduction to Graph Computing	28 godz.	A large number of 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 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 Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
rneuralnet	Sieci Neuronowe w R	14 godz.	Szkolenie jest wprowadzeniem do wdrożenia sieci neuronowych w życiu codziennym wykorzystując oprogramowanie R-project.
datashrinkgov	Data Shrinkage for Government	14 godz.	The objective of the course is to enable participants to gain a mastery of the fundamentals of data shrinkage for government.
hivehiveql	Data Analysis with Hive/HiveQL	7 godz.	This course covers how to use Hive SQL language (AKA: Hive HQL, SQL on Hive, HiveQL) for people who extract data from Hive

Upcoming Courses

Szkolenie	Data Kursu	Cena szkolenia [Zdalne / Stacjonarne]
Datameer for Data Analysts - Kielce, ul. Warszawska 19	pon., 2018-07-09 09:00	1990PLN / 2740PLN
Data Vault: Building a Scalable Data Warehouse - Zielona Góra, ul. Reja 6	pon., 2018-07-09 09:00	6650PLN / 7900PLN
Hadoop Administration on MapR - Opole, Władysława Reymonta 29	pon., 2018-07-09 09:00	3990PLN / 5240PLN
R Programming for Data Analysis - Wrocław, ul.Ludwika Rydygiera 2a/22	czw., 2018-07-12 09:00	3330PLN / 4080PLN
Big Data Business Intelligence for Govt. Agencies - Kraków, ul. Rzemieślnicza 1	pon., 2018-07-16 09:00	8320PLN / 9820PLN

Szkolenie Big Data, Big Data boot camp, Szkolenia Zdalne Big Data, szkolenie wieczorowe Big Data, szkolenie weekendowe Big Data, Kurs Big Data,Kursy Big Data, Trener Big Data, instruktor Big Data, kurs zdalny Big Data, edukacja zdalna Big Data, nauczanie wirtualne Big Data, lekcje UML, nauka przez internet Big Data, e-learning Big Data, kurs online Big Data, wykładowca Big Data

Kursy w promocyjnej cenie

Szkolenie	Miejscowość	Data Kursu	Cena szkolenia [Zdalne / Stacjonarne]
Basic Network Troubleshooting Using Wireshark	Poznań, Garbary 100/63	pon., 2018-06-25 09:00	2960PLN / 3960PLN
Oracle SQL dla początkujących	Warszawa, ul. Złota 3/11	pon., 2018-06-25 09:00	2960PLN / 3960PLN
Docker, Kubernetes and OpenShift for Administrators	Warszawa, ul. Złota 3/11	pon., 2018-06-25 09:00	4930PLN / 6430PLN
Tableau for Developers	Warszawa, ul. Złota 3/11	pon., 2018-06-25 09:00	2960PLN / 3960PLN
WebServices with SOAP and WSDL Basics	Warszawa, ul. Złota 3/11	czw., 2018-06-28 09:00	1970PLN / 2720PLN
Efektywne wykorzystanie Social Media - Facebook, Twitter, Youtube, Google+, blogi	Wrocław, ul.Ludwika Rydygiera 2a/22	pon., 2018-07-02 09:00	720PLN / 1220PLN
Język SQL w bazie danych MSSQL	Poznań, Garbary 100/63	wt., 2018-07-03 09:00	1970PLN / 2720PLN
Systems Modeling with SysML	Wrocław, ul.Ludwika Rydygiera 2a/22	śr., 2018-07-11 09:00	4940PLN / 5940PLN
Six Sigma Green Belt - Fast Track	Gdańsk, ul. Grodzka 19	pon., 2018-07-16 09:00	N/A / 5200PLN
Data Science for Big Data Analytics	Poznań, Garbary 100/63	śr., 2018-07-25 09:00	8230PLN / 9730PLN
Programowanie w języku C++	Rzeszów, Plac Wolności 13	pon., 2018-08-06 09:00	3610PLN / 5110PLN
Data analysis with Tableau	Warszawa, ul. Złota 3/11	wt., 2018-08-07 09:00	1970PLN / 2720PLN
FreeRTOS: Programming for Real Time Operating Systems	Warszawa, ul. Złota 3/11	pon., 2018-08-13 09:00	990PLN / 1490PLN

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Szkolenia Big Data

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