Big Data Training Courses
Local, instructor-led live Big Data training courses start with an introduction to elemental concepts of Big Data, then progress into the programming 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 training can be carried out locally on customer premises in the UK or in NobleProg corporate training centers in the UK. Remote live training is carried out by way of an interactive, remote desktop. NobleProg -- Your Local Training Provider
Client Testimonials
Course Outlines
| Code | Name | Duration | Overview |
|---|---|---|---|
| smtwebint | Semantic Web Overview | 7 hours | 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. |
| psr | Introduction to Recommendation Systems | 7 hours | AudienceMarketing department employees, IT strategists and other people involved in decisions related to the design and implementation of recommender systems. FormatShort theoretical background follow by analysing working examples and short, simple exercises. |
| mdlmrah | Model MapReduce and Apache Hadoop | 14 hours | The course is intended for IT specialist that works with the distributed processing of large data sets across clusters of computers. |
| sspsspas | Statistics with SPSS Predictive Analytics Software | 14 hours | Goal:Learning to work with SPSS at the level of independence The addressees:Analysts, researchers, scientists, students and all those who want to acquire the ability to use SPSS package and learn popular data mining techniques. |
| iotemi | IoT ( Internet of Things) for Entrepreneurs, Managers and Investors | 21 hours | Unlike other technologies, IoT is far more complex encompassing almost every branch of core Engineering-Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics and Mobile. For each of its engineering layers, there are aspects of economics, standards, regulations and evolving state of the art. This is for the firs time, a modest course is offered to cover all of these critical aspects of IoT Engineering. Summary
Target Audience
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 on a 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 sizable 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 Objective 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.
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| 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 |
| 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:
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. |
| bdbitcsp | Big Data Business Intelligence for Telecom and Communication Service Providers | 35 hours | OverviewCommunications 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 objectivesMain 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:
Target Audience
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| 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. |
| datamin | Data Mining | 21 hours | Course can be provided with any tools, including free open-source data mining software and applications |
| dataminr | Data Mining with R | 14 hours | 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. |
| pmml | Predictive Models with PMML | 7 hours | The course is created to scientific, developers, analysts or any other people who want to standardize or exchange their models with Predictive Model Markup Language (PMML) file format. |
| 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. |
| 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. |
| datashrinkgov | Data Shrinkage for Government | 14 hours | The objective of the course is to enable participants to gain a mastery of the fundamentals of data shrinkage for government. |
| d2dbdpa | From Data to Decision with Big Data and Predictive Analytics | 21 hours | AudienceIf 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 ModeDuring 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 usedAll 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. |
| bigdarch | Big Data Architect | 35 hours | Day 1 - provides a high-level overview of essential Big Data topic areas. The module is divided into a series of sections, each of which is accompanied by a hands-on exercise. Day 2 - explores a range of topics that relate analysis practices and tools for Big Data environments. It does not get into implementation or programming details, but instead keeps coverage at a conceptual level, focusing on topics that enable participants to develop a comprehensive understanding of the common analysis functions and features offered by Big Data solutions. Day 3 - provides an overview of the fundamental and essential topic areas relating to Big Data solution platform architecture. It covers Big Data mechanisms required for the development of a Big Data solution platform and architectural options for assembling a data processing platform. Common scenarios are also presented to provide a basic understanding of how a Big Data solution platform is generally used. Day 4 - builds upon Day 3 by exploring advanced topics relatng to Big Data solution platform architecture. In particular, different architectural layers that make up the Big Data solution platform are introduced and discussed, including data sources, data ingress, data storage, data processing and security. Day 5 - covers a number of exercises and problems designed to test the delegates ability to apply knowledge of topics covered Day 3 and 4. |
| osqlide | Oracle SQL Intermediate - Data Extraction | 14 hours | The objective of the course is to enable participants to gain a mastery of how to work with the SQL language in Oracle database for data extraction at intermediate level. |
| datama | Data Mining and Analysis | 28 hours | Objective:Delegates be able to analyse big data sets, extract patterns, choose the right variable impacting the results so that a new model is forecasted with predictive results. |
| rintrob | Introductory R for Biologists | 28 hours | 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. |
| 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. |
| bigddbsysfun | Big Data & Database Systems Fundamentals | 14 hours | The course is part of the Data Scientist skill set (Domain: Data and Technology). |
| dmmlr | Data Mining & Machine Learning with R | 14 hours | 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. |
| altdomexp | Analytics Domain Expertise | 7 hours | This course is part of the Data Scientist skill set (Domain: Analytics Domain Expertise). |
| hivehiveql | Data Analysis with Hive/HiveQL | 7 hours | This course covers how to use Hive SQL language (AKA: Hive HQL, SQL on Hive, HiveQL) for people who extract data from Hive |
| datapro | Data Protection | 35 hours | This is an Instructor led course, and is the non-certification version of the "CDP - Certificate in Data Protection" course Those experienced in data protection issues, as well as those new to the subject, need to be trained so that their organisations are confident that legal compliance is continually addressed. It is necessary to identify issues requiring expert data protection advice in good time in order that organisational reputation and credibility are enhanced through relevant data protection policies and procedures. Objectives:The aim of the syllabus is to promote an understanding of how the data protection principles work rather than simply focusing on the mechanics of regulation. The syllabus places the Act in the context of human rights and promotes good practice within organisations. On completion you will have:
Course Synopsis:The syllabus comprises three main parts, each sub-sections.
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| 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. |
| sparkdev | Spark for Developers | 21 hours | 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 |
| datavis1 | Data Visualization | 28 hours | This course is intended for engineers and decision makers working in data mining and knoweldge discovery. You will learn how to create effective plots and ways to present and represent your data in a way that will appeal to the decision makers and help them to understand hidden information. |
| HadoopDevAd | Hadoop for Developers and Administrators | 21 hours | Hadoop is the most popular Big Data processing framework. |
Upcoming Courses
| Course | Course Date | Course Price [Remote / Classroom] |
|---|---|---|
| Apache Spark - Brighton | Wed, 2018-08-01 09:30 | £2200 / £2600 |
| Big Data - Data Science - Birmingham | Wed, 2018-08-01 09:30 | £2600 / £3250 |
| Big Data & Database Systems Fundamentals - Edinburgh | Wed, 2018-08-01 09:30 | £2200 / £3200 |
| A Practical Introduction to Data Analysis and Big Data - London, Hatton Garden | Mon, 2018-08-06 09:30 | £6500 / £8375 |
| Vespa: Serving Large-Scale Data in Real-Time - Swansea- Princess House | Mon, 2018-08-06 09:30 | £2200 / £2500 |
Other regions
Other countries
Consulting
Course Discounts
| Course | Venue | Course Date | Course Price [Remote / Classroom] |
|---|---|---|---|
| OCUP2 UML 2.5 Certification - Advanced Exam Preparation | St Helier, Jersey, Channel Isles | Mon, 2018-07-23 09:30 | £1980 / £2930 |
| Introduction to R | Glasgow | Wed, 2018-08-01 09:30 | £3861 / £4911 |
| Subversion for Users | Newcastle | Fri, 2018-08-03 09:30 | £1089 / £1289 |
| OCUP2 UML 2.5 Certification - Intermediate Exam Preparation | St Helier, Jersey, Channel Isles | Tue, 2018-08-07 09:30 | £2340 / £3290 |
| jQuery | Swansea- Princess House | Wed, 2018-08-15 09:30 | £1980 / £2280 |
| AWS: A Hands-on Introduction to Cloud Computing | Edinburgh Training and Conference Venue | Tue, 2018-09-11 09:30 | £1287 / £1487 |
| Test Automation with Selenium | St Helier, Jersey, Channel Isles | Tue, 2018-09-18 09:30 | £2970 / £4395 |
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