Local, instructor-led live Big Data training courses start with an introduction to elemental concepts of Big Data, then progress into the programmeming languages and methodologies used to perform Data Analysis. Tools and infrastructure for enabling Big Data storage, Distributed Processing, and Scalability are discussed, compared and implemented in demo practice sessions. Big Data training is available as "onsite live training" or "remote live training". Onsite live Big Data training can be carried out locally on customer premises in Birmingham or in NobleProg corporate training centres in Birmingham. Remote live training is carried out by way of an interactive, remote desktop. NobleProg -- Your Local Training Provider
From Moor Street Station
Exiting via the main ticket hall, travel up the escalator to the Pallasades Shopping centre. At the top turn left and follow the shops first to the left and then to the right leading to the exit from the Pallasades and on to Corporation Street. Walking down the ramp past McDonalds continue up Corporation Street for 200m passing Gap Clothes, House of Fraser and Wetherspoons pub. Continue across Old...
Read moreI generally enjoyed the Hardtop Eco system.
Adnan Rafiq
Course:Big Data Business Intelligence for Govt. Agencies
I really enjoyed the introduction of new packages.
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course:Programming with Big Data in R
Michael the trainer is very knowledgeable and skillful about the subject of Big Data and R. He is very flexible and quickly customise the training meeting clients' need. He is also very capable to solve technical and subject matter problems on the go. Fantastic and professional training!.
Xiaoyuan Geng - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course:Programming with Big Data in R
the scope of material
Maciej Jonczyk
Course:From Data to Decision with Big Data and Predictive Analytics
Translated by
systematizing knowledge in the field of ML
Orange Polska
Course:From Data to Decision with Big Data and Predictive Analytics
Translated by
entirety
Szymon Bodak - Bridgestone Stargard Sp. z o.o.
Course:Talend Open Studio for Data Integration
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| Code | Name | Venue | Duration | Course Date | Course Price [Remote / Classroom] |
|---|---|---|---|---|---|
| foundr | Foundation R | Birmingham | 7 hours | Mon, 2018-11-26 09:30 | £1300 / £1625 |
| dremio | Dremio for Self-Service Data Analysis | Birmingham | 21 hours | Wed, 2018-11-28 09:30 | £3300 / £4275 |
| druid | Druid: Build a Fast, Real-Time Data Analysis System | Birmingham | 21 hours | Tue, 2018-11-27 09:30 | £3300 / £4275 |
| apachedrillqueryoptim | Apache Drill Query Optimization | Birmingham | 7 hours | Tue, 2018-11-27 09:30 | £1100 / £1425 |
| datamin | Data Mining | Birmingham | 21 hours | Wed, 2018-11-28 09:30 | £3900 / £4875 |
| hadoopdev | Hadoop for Developers (4 days) | Birmingham | 28 hours | Tue, 2018-11-27 09:30 | £4400 / £5700 |
| samza | Samza for Stream Processing | Birmingham | 14 hours | Wed, 2018-11-28 09:30 | £2200 / £2850 |
| tigon | Tigon: Real-time Streaming for the Real World | Birmingham | 14 hours | Wed, 2018-12-05 09:30 | £2200 / £2850 |
| hadoopmapr | Hadoop Administration on MapR | Birmingham | 28 hours | Mon, 2018-12-03 09:30 | £4400 / £5700 |
| dataminr | Data Mining with R | Birmingham | 14 hours | Thu, 2018-12-06 09:30 | £2600 / £3250 |
| apacheignite | Apache Ignite: Improve Speed, Scale and Availability with In-Memory Computing | Birmingham | 14 hours | Mon, 2018-12-03 09:30 | £2200 / £2850 |
| sparkdev | Spark for Developers | Birmingham | 21 hours | Wed, 2018-12-05 09:30 | £3300 / £4275 |
| bigdatar | Programming with Big Data in R | Birmingham | 21 hours | Wed, 2018-11-28 09:30 | £3900 / £4875 |
| kdd | Knowledge Discovery in Databases (KDD) | Birmingham | 21 hours | Mon, 2018-12-03 09:30 | £3300 / £4275 |
| introtoavro | Apache Avro: Data Serialization for Distributed Applications | Birmingham | 14 hours | Wed, 2018-12-05 09:30 | £2200 / £2850 |
| processmining | Process Mining | Birmingham | 21 hours | Wed, 2018-12-05 09:30 | £3900 / £4875 |
| hadoopba | Hadoop for Business Analysts | Birmingham | 21 hours | Wed, 2018-12-05 09:30 | £3300 / £4275 |
| kylin | Apache Kylin: From Classic OLAP to Real-Time Data Warehouse | Birmingham | 14 hours | Tue, 2018-11-27 09:30 | £2200 / £2850 |
| monetdb | MonetDB | Birmingham | 28 hours | Mon, 2018-12-03 09:30 | £4400 / £5700 |
| vespa | Vespa: Serving Large-Scale Data in Real-Time | Birmingham | 14 hours | Thu, 2018-12-06 09:30 | £2200 / £2850 |
| hadoopdeva | Advanced Hadoop for Developers | Birmingham | 21 hours | Tue, 2018-12-11 09:30 | £3300 / £4275 |
| datavault | Data Vault: Building a Scalable Data Warehouse | Birmingham | 28 hours | Mon, 2018-12-10 09:30 | £4400 / £5700 |
| sparksql | Apache Spark SQL | Birmingham | 7 hours | Tue, 2018-12-11 09:30 | £1100 / £1425 |
| bdbiga | Big Data Business Intelligence for Govt. Agencies | Birmingham | 35 hours | Mon, 2018-12-10 09:30 | £6500 / £8125 |
| pmml | Predictive Models with PMML | Birmingham | 7 hours | Thu, 2018-12-13 09:30 | £1300 / £1625 |
| beam | Unified Batch and Stream Processing with Apache Beam | Birmingham | 14 hours | Tue, 2018-12-11 09:30 | £2200 / £2850 |
| apex | Apache Apex: Processing Big Data-in-Motion | Birmingham | 21 hours | Mon, 2018-12-10 09:30 | £3300 / £4275 |
| spmllib | Apache Spark MLlib | Birmingham | 35 hours | Mon, 2018-12-10 09:30 | £6500 / £8125 |
| bigdatam | Big Data and its Management Process | Birmingham | 14 hours | Thu, 2018-12-06 09:30 | £2200 / £2850 |
| hadooppython | Hadoop with Python | Birmingham | 28 hours | Tue, 2018-12-11 09:30 | £4400 / £5700 |
| Code | Name | Duration | Overview |
|---|---|---|---|
| aifortelecom | AI Awareness for Telecom | 14 hours | 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 |
| d2dbdpa | From Data to Decision with Big Data and Predictive Analytics | 21 hours | Audience If you try to make sense out of the data you have access to or want to analyse unstructured data available on the net (like Twitter, Linked in, etc...) this course is for you. It is mostly aimed at decision makers and people who need to choose what data is worth collecting and what is worth analyzing. It is not aimed at people configuring the solution, those people will benefit from the big picture though. Delivery Mode During the course delegates will be presented with working examples of mostly open source technologies. Short lectures will be followed by presentation and simple exercises by the participants Content and Software used All software used is updated each time the course is run, so we check the newest versions possible. It covers the process from obtaining, formatting, processing and analysing the data, to explain how to automate decision making process with machine learning. |
| hbasedev | HBase for Developers | 21 hours | 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 |
| hadoopmapr | Hadoop Administration on MapR | 28 hours | Audience: This course is intended to demystify big data/hadoop technology and to show it is not difficult to understand. |
| hadoopforprojectmgrs | Hadoop for Project Managers | 14 hours | As more and more software and IT projects migrate from local processing and data management to distributed processing and big data storage, Project Managers are finding the need to upgrade their knowledge and skills to grasp the concepts and practices relevant to Big Data projects and opportunities. This course introduces Project Managers to the most popular Big Data processing framework: Hadoop. In this instructor-led training, participants will learn the core components of the Hadoop ecosystem and how these technologies can be used to solve large-scale problems. In learning these foundations, participants will also improve their ability to communicate with the developers and implementers of these systems as well as the data scientists and analysts that many IT projects involve. Audience - Project Managers wishing to implement Hadoop into their existing development or IT infrastructure - Project Managers needing to communicate with cross-functional teams that include big data engineers, data scientists and business analysts Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| HadoopDevAd | Hadoop for Developers and Administrators | 21 hours | Hadoop is the most popular Big Data processing framework. |
| hadoopdeva | Advanced Hadoop for Developers | 21 hours | Apache Hadoop is one of the most popular frameworks for processing Big Data on clusters of servers. This course delves into data management in HDFS, advanced Pig, Hive, and HBase. These advanced programming techniques will be beneficial to experienced Hadoop developers. Audience: developers Duration: three days Format: lectures (50%) and hands-on labs (50%). |
| hadoopdev | Hadoop for Developers (4 days) | 28 hours | Apache Hadoop is the most popular framework for processing Big Data on clusters of servers. This course will introduce a developer to various components (HDFS, MapReduce, Pig, Hive and HBase) Hadoop ecosystem. |
| hadoopba | Hadoop for Business Analysts | 21 hours | Apache Hadoop is the most popular framework for processing Big Data. Hadoop provides rich and deep analytics capability, and it is making in-roads in to tradional BI analytics world. This course will introduce an analyst to the core components of Hadoop eco system and its analytics Audience Business Analysts Duration three days Format Lectures and hands on labs. |
| hadoopadm1 | Hadoop For Administrators | 21 hours | Apache Hadoop is the most popular framework for processing Big Data on clusters of servers. In this three (optionally, four) days course, attendees will learn about the business benefits and use cases for Hadoop and its ecosystem, how to plan cluster deployment and growth, how to install, maintain, monitor, troubleshoot and optimize Hadoop. They will also practice cluster bulk data load, get familiar with various Hadoop distributions, and practice installing and managing Hadoop ecosystem tools. The course finishes off with discussion of securing cluster with Kerberos. “…The materials were very well prepared and covered thoroughly. The Lab was very helpful and well organized” — Andrew Nguyen, Principal Integration DW Engineer, Microsoft Online Advertising Audience Hadoop administrators Format Lectures and hands-on labs, approximate balance 60% lectures, 40% labs. |
| hadoopadm | Hadoop Administration | 21 hours | The course is dedicated to IT specialists that are looking for a solution to store and process large data sets in distributed system environment Course goal: Getting knowledge regarding Hadoop cluster administration |
| dsbda | Data Science for Big Data Analytics | 35 hours | Big data is data sets that are so voluminous and complex that traditional data processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy. |
| DatSci7 | Data Science Programme | 245 hours | The explosion of information and data in today’s world is un-paralleled, our ability to innovate and push the boundaries of the possible is growing faster than it ever has. The role of Data Scientist is one of the highest in-demand skills across industry today. We offer much more than learning through theory; we deliver practical, marketable skills that bridge the gap between the world of academia and the demands of industry. This 7 week curriculum can be tailored to your specific Industry requirements, please contact us for further information or visit the Nobleprog Institute website [www.inobleprog.co.uk](http://www.inobleprog.co.uk/) Audience: This programme is aimed post level graduates as well as anyone with the required pre-requisite skills which will be determined by an assessment and interview. Delivery: Delivery of the course will be a mixture of Instructor Led Classroom and Instructor Led Online; typically the 1st week will be 'classroom led', weeks 2 - 6 'virtual classroom' and week 7 back to 'classroom led'. |
| datameer | Datameer for Data Analysts | 14 hours | 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 |
| bigd_LBG | Big Data - Data Science | 14 hours | This classroom based training session will explore Big Data. Delegates will have computer based examples and case study exercises to undertake with relevant big data tools |
| alluxio | Alluxio: Unifying Disparate Storage Systems | 7 hours | Alluxio is an open-source virtual distributed storage system that unifies disparate storage systems and enables applications to interact with data at memory speed. It is used by companies such as Intel, Baidu and Alibaba. In this instructor-led, live training, participants will learn how to use Alluxio to bridge different computation frameworks with storage systems and efficiently manage multi-petabyte scale data as they step through the creation of an application with Alluxio. By the end of this training, participants will be able to: - Develop an application with Alluxio - Connect big data systems and applications while preserving one namespace - Efficiently extract value from big data in any storage format - Improve workload performance - Deploy and manage Alluxio standalone or clustered Audience - Data scientist - Developer - System administrator Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| bigddbsysfun | Big Data & Database Systems Fundamentals | 14 hours | The course is part of the Data Scientist skill set (Domain: Data and Technology). |
| BigData_ | A Practical Introduction to Data Analysis and Big Data | 35 hours | Participants who complete this training 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. Audience - Developers / programmers - IT consultants Format of the course - Part lecture, part discussion, hands-on practice and implementation, occasional quizing to measure progress. |
| bigdatastore | Big Data Storage Solution - NoSQL | 14 hours | When traditional storage technologies don't handle the amount of data you need to store there are hundereds of alternatives. This course try to guide the participants what are alternatives for storing and analyzing Big Data and what are theirs pros and cons. This course is mostly focused on discussion and presentation of solutions, though hands-on exercises are available on demand. |
| bigdatar | Programming with Big Data in R | 21 hours | Big Data is a term that refers to solutions destined for storing and processing large data sets. Developed by Google initially, these Big Data solutions have evolved and inspired other similar projects, many of which are available as open-source. R is a popular programming language in the financial industry. |
| bigdataM | Big Data and its Management Process | 14 hours | Objective : This training course aims at helping attendees understand why Big Data is changing our lives and how it is altering the way businesses see us as consumers. Indeed, users of big data in businesses find that big data unleashes a wealth of information and insights which translate to higher profits, reduced costs, and less risk. However, the downside was frustration sometimes when putting too much emphasis on individual technologies and not enough focus on the pillars of big data management. Attendees will learn during this course how to manage the big data using its three pillars of data integration, data governance and data security in order to turn big data into real business value. Different exercices conducted on a case study of customer management will help attendees to better understand the underlying processes. |
| bigdatabicriminal | Big Data Business Intelligence for Criminal Intelligence Analysis | 35 hours | Advances in technologies and the increasing amount of information are transforming how law enforcement is conducted. The challenges that Big Data pose are nearly as daunting as Big Data's promise. Storing data efficiently is one of these challenges; effectively analyzing it is another. In this instructor-led, live training, participants will learn the mindset with which to approach Big Data technologies, assess their impact on existing processes and policies, and implement these technologies for the purpose of identifying criminal activity and preventing crime. Case studies from law enforcement organizations around the world will be examined to gain insights on their adoption approaches, challenges and results. By the end of this training, participants will be able to: - Combine Big Data technology with traditional data gathering processes to piece together a story during an investigation - Implement industrial big data storage and processing solutions for data analysis - Prepare a proposal for the adoption of the most adequate tools and processes for enabling a data-driven approach to criminal investigation Audience - Law Enforcement specialists with a technical background Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| bigdataanahealth | Big Data Analytics in Health | 21 hours | 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. |
| bdbitcsp | Big Data Business Intelligence for Telecom and Communication Service Providers | 35 hours | 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 |
| bdbiga | Big Data Business Intelligence for Govt. Agencies | 35 hours | 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 thesevolumes of Big Datarequires 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 billion 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. |
| BDATR | Big Data Analytics for Telecom Regulators | 16 hours | To meet compliance of the regulators, CSPs (Communication service providers) can tap into Big Data Analytics which not only help them to meet compliance but within the scope of same project they can increase customer satisfaction and thus reduce the churn. In fact since compliance is related to Quality of service tied to a contract, any initiative towards meeting the compliance, will improve the “competitive edge” of the CSPs. Therefore, it is important that Regulators should be able to advise/guide a set of Big Data analytic practice for CSPs that will be of mutual benefit between the regulators and CSPs. 2 days of course : 8 modules, 2 hours each = 16 hours |
| ApHadm1 | Apache Hadoop: Manipulation and Transformation of Data Performance | 21 hours | This course is intended for developers, architects, data scientists or any profile that requires access to data either intensively or on a regular basis. The major focus of the course is data manipulation and transformation. Among the tools in the Hadoop ecosystem this course includes the use of Pig and Hive both of which are heavily used for data transformation and manipulation. This training also addresses performance metrics and performance optimisation. The course is entirely hands on and is punctuated by presentations of the theoretical aspects. |
| apacheh | Administrator Training for Apache Hadoop | 35 hours | Audience: The course is intended for IT specialists looking for a solution to store and process large data sets in a distributed system environment Goal: Deep knowledge on Hadoop cluster administration. |
| ambari | Apache Ambari: Efficiently Manage Hadoop Clusters | 21 hours | Apache Ambari is an open-source management platform for provisioning, managing, monitoring and securing Apache Hadoop clusters. In this instructor-led live training participants will learn the management tools and practices provided by Ambari to successfully manage Hadoop clusters. By the end of this training, participants will be able to: - Set up a live Big Data cluster using Ambari - Apply Ambari's advanced features and functionalities to various use cases - Seamlessly add and remove nodes as needed - Improve a Hadoop cluster's performance through tuning and tweaking Audience - DevOps - System Administrators - DBAs - Hadoop testing professionals Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| hdp | Hortonworks Data Platform (HDP) for Administrators | 21 hours | 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 |
| Course | Venue | Course Date | Course Price [Remote / Classroom] |
|---|---|---|---|
| Android Development | Glasgow | Mon, 2018-11-19 09:30 | £4356 / £5756 |
| Selenium WebDriver in C#: Introduction to Web Testing Automation in C# | Edinburgh Training and Conference Venue | Tue, 2018-11-20 09:30 | £2178 / £2578 |
| F#: Introduction to Functional Programming | Portsmouth | Mon, 2018-11-26 09:30 | £2178 / £2478 |
| Python: Automate the Boring Stuff | Swindon | Wed, 2018-11-28 09:30 | £2178 / £2528 |
| JMeter Fundamentals and JMeter Advanced | Edinburgh Training and Conference Venue | Mon, 2018-12-03 09:30 | £2178 / £2578 |
| HAProxy Administration | London, Hatton Garden | Mon, 2018-12-03 09:30 | £2178 / £2928 |
| From Data to Decision with Big Data and Predictive Analytics | Birmingham | Tue, 2018-12-11 09:30 | £3861 / £4836 |
| Test Automation with Selenium | Manchester, King Street | Wed, 2018-12-12 09:30 | £3267 / £4242 |
| Artificial Intelligence Overview | London, Hatton Garden | Thu, 2018-12-27 09:30 | £1287 / £1662 |
| RPA: Implementing Robotic Process Automation | London, Hatton Garden | Tue, 2019-01-29 09:30 | £3861 / £4986 |
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