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 Swindon or in NobleProg corporate training centers in Swindon. Remote live training is carried out by way of an interactive, remote desktop. NobleProg -- Your Local Training Provider
Located on the western side of Swindon and located only 300yds from junction 16 of the M4 providing easy access to both the south west and south east.
By train London Paddington is only 1 hour away and Bristol temple meads 45 minutes from Swindon’s mainline station.
Swindon town centre is only a 5 min drive away and offers all modern restaurant and shopping facilities, for those who prefer a slower pace areas such as Lydiard Country Park are located within 1 mile of the...
I am a hands-on learner and this was something that he did a lot of.
Lisa Comfort
Course: Data Visualization
Overall the Content was good.
Sameer Rohadia
Course: A practical introduction to Data Analysis and Big Data
I generally was benefit from the presentation of technologies.
Continental AG / Abteilung: CF IT Finance
Course: A practical introduction to Data Analysis and Big Data
He was very personable and worked hard to provide a relevant experience. It was the course content that was the issue.
TECTERRA
Course: IoT (Internet of Things) for Entrepreneurs, Managers and Investors
Ernesto did a great job explaining the high level concepts of using Spark and its various modules.
Michael Nemerouf
Course: Spark for Developers
I generally liked all.
Marjorie Pepito
Course: Data Protection
We know a lot more about the whole environment.
John Kidd
Course: Spark for Developers
The trainer made the class interesting and entertaining which helps quite a bit with all day training.
Ryan Speelman
Course: Spark for Developers
I think the trainer had an excellent style of combining humor and real life stories to make the subjects at hand very approachable. I would highly recommend this professor in the future.
Course: Spark for Developers
I liked the examples.
Peter Coleman
Course: Data Visualization
The hands-on exercises are good for us to appreciate the capability and features of Talent.
Iverson Associates Sdn Bhd
Course: Talend Open Studio for Data Integration
Trainer was enthusiastic.
Diane Lucas
Course: Data Visualization
Learning about all the chart types and what they are used for. Learning the value of cluttering. Learning about the methods to show time data.
Susan Williams
Course: Data Visualization
Richard's training style kept it interesting, the real world examples used helped to drive the concepts home.
Jamie Martin-Royle - NBrown Group
Course: From Data to Decision with Big Data and Predictive Analytics
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
The content, as I found it very interesting and think it would help me in my final year at University.
Krishan Mistry - NBrown Group
Course: From Data to Decision with Big Data and Predictive Analytics
I was benefit from some new and interesting ideas. Meeting and interacting with other attendees.
TECTERRA
Course: IoT (Internet of Things) for Entrepreneurs, Managers and Investors
I generally enjoyed the Hardtop Eco system.
Adnan Rafiq
Course: Big Data Business Intelligence for Govt. Agencies
I really liked the content / Instructor.
Craig Roberson
Course: Data Visualization
The subject matter and the pace were perfect.
Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
I generally was benefit from the examples.
peter coleman
Course: Data Visualization
It covered a broad range of information.
Continental AG / Abteilung: CF IT Finance
Course: A practical introduction to Data Analysis and Big Data
I enjoyed the interaction and facts gained / learn.
Monna Liza Mengullo
Course: Data Protection
Michael the trainer is very knowledgeable and skillful about the subject of Big Data and R. He is very flexible and quickly customize 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
I enjoyed the good real world examples, reviews of existing reports.
Ronald Parrish
Course: Data Visualization
I was benefit from the discussion and exchange of ideas.
RAYMOND JACKSON PAJARILLO
Course: Data Protection
The example and training material were sufficient and made it easy to understand what you are doing.
Teboho Makenete
Course: Data Science for Big Data Analytics
The tutor, Mr. Michael An, interacted with the audience very well, the instruction was clear. The tutor also go extent to add more information based on the requests from the students during the training.
Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course: Programming with Big Data in R
It was very hands-on, we spent half the time actually doing things in Clouded/Hardtop, running different commands, checking the system, and so on. The extra materials (books, websites, etc. .) were really appreciated, we will have to continue to learn. The installations were quite fun, and very handy, the cluster setup from scratch was really good.
Ericsson
Course: Administrator Training for Apache Hadoop
I really was benefit from the willingness of the trainer to share more.
Balaram Chandra Paul
Course: A practical introduction to Data Analysis and Big Data
| Code | Name | Venue | Duration | Course Date | Course Price [Remote / Classroom] |
|---|---|---|---|---|---|
| matlabpredanalytics | Matlab for Predictive Analytics | Swindon | 21 hours | Wed, 2018-09-05 09:30 | £3900 / £4425 |
| teraintro | Teradata Fundamentals | Swindon | 21 hours | Wed, 2018-09-05 09:30 | £3300 / £3825 |
| amazonredshift | Amazon Redshift | Swindon | 21 hours | Wed, 2018-09-05 09:30 | £3300 / £3825 |
| magellan | Magellan: Geospatial Analytics on Spark | Swindon | 14 hours | Thu, 2018-09-06 09:30 | £2600 / £2950 |
| IntroToAvro | Apache Avro: Data Serialization for Distributed Applications | Swindon | 14 hours | Mon, 2018-09-10 09:30 | £2200 / £2550 |
| bigdatabicriminal | Big Data Business Intelligence for Criminal Intelligence Analysis | Swindon | 35 hours | Mon, 2018-09-10 09:30 | £6500 / £7375 |
| dmmlr | Data Mining & Machine Learning with R | Swindon | 14 hours | Tue, 2018-09-11 09:30 | £2600 / £2950 |
| hadoopdeva | Advanced Hadoop for Developers | Swindon | 21 hours | Tue, 2018-09-11 09:30 | £3300 / £3825 |
| hadoopadm1 | Hadoop For Administrators | Swindon | 21 hours | Tue, 2018-09-11 09:30 | £3300 / £3825 |
| sparkpython | Python and Spark for Big Data (PySpark) | Swindon | 21 hours | Wed, 2018-09-12 09:30 | £3900 / £4425 |
| vespa | Vespa: Serving Large-Scale Data in Real-Time | Swindon | 14 hours | Thu, 2018-09-13 09:30 | £2200 / £2550 |
| hadooppython | Hadoop with Python | Swindon | 28 hours | Tue, 2018-09-18 09:30 | £4400 / £5100 |
| tigon | Tigon: Real-time Streaming for the Real World | Swindon | 14 hours | Tue, 2018-09-18 09:30 | £2200 / £2550 |
| TalendDI | Talend Open Studio for Data Integration | Swindon | 28 hours | Tue, 2018-09-18 09:30 | N/A / £5100 |
| hadoopba | Hadoop for Business Analysts | Swindon | 21 hours | Tue, 2018-09-18 09:30 | £3300 / £3825 |
| bigdataM | Big Data and its Management Process | Swindon | 14 hours | Tue, 2018-09-18 09:30 | £2200 / £2550 |
| accumulo | Apache Accumulo: Building Highly Scalable Big Data Applications | Swindon | 21 hours | Wed, 2018-09-19 09:30 | £3300 / £3825 |
| ApacheIgnite | Apache Ignite: Improve Speed, Scale and Availability with In-memory Computing | Swindon | 14 hours | Wed, 2018-09-19 09:30 | £2200 / £2550 |
| bigd_LBG | Big Data - Data Science | Swindon | 14 hours | Wed, 2018-09-19 09:30 | £2600 / £2950 |
| sparkdev | Spark for Developers | Swindon | 21 hours | Wed, 2018-09-19 09:30 | £3300 / £3825 |
| dremio | Dremio for Self-Service Data Analysis | Swindon | 21 hours | Wed, 2018-09-19 09:30 | £3300 / £3825 |
| hivehiveql | Data Analysis with Hive/HiveQL | Swindon | 7 hours | Thu, 2018-09-20 09:30 | £1100 / £1275 |
| sparksql | Apache Spark SQL | Swindon | 7 hours | Fri, 2018-09-21 09:30 | £1100 / £1275 |
| hadoopdev | Hadoop for Developers (4 days) | Swindon | 28 hours | Mon, 2018-09-24 09:30 | £4400 / £5100 |
| bigdatar | Programming with Big Data in R | Swindon | 21 hours | Mon, 2018-09-24 09:30 | £3900 / £4425 |
| bdbitcsp | Big Data Business Intelligence for Telecom and Communication Service Providers | Swindon | 35 hours | Mon, 2018-09-24 09:30 | £6500 / £7375 |
| zookeeper | Apache Zookeeper | Swindon | 14 hours | Tue, 2018-09-25 09:30 | £2200 / £2550 |
| osqlide | Oracle SQL Intermediate - Data Extraction | Swindon | 14 hours | Tue, 2018-09-25 09:30 | £2200 / £2550 |
| apex | Apache Apex: Processing Big Data-in-Motion | Swindon | 21 hours | Tue, 2018-09-25 09:30 | £3300 / £3825 |
| datavault | Data Vault: Building a Scalable Data Warehouse | Swindon | 28 hours | Tue, 2018-09-25 09:30 | £4400 / £5100 |
| Code | Name | Duration | Overview |
|---|---|---|---|
| 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 - An advanced training program covering the current state of the art in Internet of Things - Cuts across multiple technology domains to develop awareness of an IoT system and its components and how it can help businesses and organizations. - Live demo of model IoT applications to showcase practical IoT deployments across different industry domains, such as Industrial IoT, Smart Cities, Retail, Travel & Transportation and use cases around connected devices & things Target Audience - Managers responsible for business and operational processes within their respective organizations and want to know how to harness IoT to make their systems and processes more efficient. - Entrepreneurs and Investors who are looking to build new ventures and want to develop a better understanding of the IoT technology landscape to see how they can leverage it in an effective manner. 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. - 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-Raspberry Pi, Arduino , ArmMbedLPC etc - Open source /commercial enterprise cloud platform for AWS-IoT apps, Azure -IOT, Watson-IOT cloud in addition to other minor IoT clouds - Studies of business and technology of some of the common IoT devices like Home automation, Smoke alarm, vehicles, military, home health etc. |
| datavault | Data Vault: Building a Scalable Data Warehouse | 28 hours | Data vault modeling is a database modeling technique that provides long-term historical storage of data that originates from multiple sources. A data vault stores a single version of the facts, or "all the data, all of the time". Its flexible, scalable, consistent and adaptable design encompasses the best aspects of 3rd normal form (3NF) and star schema. In this instructor-led, live training, participants will learn how to build a Data Vault. By the end of this training, participants will be able to: - Understand the architecture and design concepts behind Data Vault 2.0, and its interaction with Big Data, NoSQL and AI. - Use data vaulting techniques to enable auditing, tracing, and inspection of historical data in a data warehouse - Develop a consistent and repeatable ETL (Extract, Transform, Load) process - Build and deploy highly scalable and repeatable warehouses Audience - Data modelers - Data warehousing specialist - Business Intelligence specialists - Data engineers - Database administrators Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| 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 |
| 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. |
| 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. |
| 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 |
| 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. |
| 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. |
| 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. |
| 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 |
| 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 |
| 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 |
| matlabpredanalytics | Matlab for Predictive Analytics | 21 hours | Predictive analytics is the process of using data analytics to make predictions about the future. This process uses data along with data mining, statistics, and machine learning techniques to create a predictive model for forecasting future events. In this instructor-led, live training, participants will learn how to use Matlab to build predictive models and apply them to large sample data sets to predict future events based on the data. By the end of this training, participants will be able to: - Create predictive models to analyze patterns in historical and transactional data - Use predictive modeling to identify risks and opportunities - Build mathematical models that capture important trends - Use data from devices and business systems to reduce waste, save time, or cut costs Audience - Developers - Engineers - Domain experts Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| vespa | Vespa: Serving Large-Scale Data in Real-Time | 14 hours | Vespa is an open-source big data processing and serving engine created by Yahoo. It is used to respond to user queries, make recommendations, and provide personalized content and advertisements in real-time. This instructor-led, live training introduces the challenges of serving large-scale data and walks participants through the creation of an application that can compute responses to user requests, over large datasets in real-time. By the end of this training, participants will be able to: - Use Vespa to quickly compute data (store, search, rank, organize) at serving time while a user waits - Implement Vespa into existing applications involving feature search, recommendations, and personalization - Integrate and deploy Vespa with existing big data systems such as Hadoop and Storm. Audience - Developers Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| 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. |
| PentahoDI | Pentaho Data Integration Fundamentals | 21 hours | 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 |
| TalendDI | Talend Open Studio for Data Integration | 28 hours | 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. |
| 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'. |
| 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. |
| 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. |
| altdomexp | Analytics Domain Expertise | 7 hours | This course is part of the Data Scientist skill set (Domain: Analytics Domain Expertise). |
| bigddbsysfun | Big Data & Database Systems Fundamentals | 14 hours | The course is part of the Data Scientist skill set (Domain: Data and Technology). |
| 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. |
| 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. |
| 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. |
| 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. |
| 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. |
| 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 |
| 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. |
| Course | Venue | Course Date | Course Price [Remote / Classroom] |
|---|---|---|---|
| Excel VBA Introduction | Belfast City Centre | Mon, 2018-09-03 09:30 | £2178 / £2678 |
| Introduction to Selenium | York - Priory Street Centre | Tue, 2018-09-04 09:30 | £1089 / £1239 |
| Minitab for Statistical Data Analysis | Cambridge | Mon, 2018-09-10 09:30 | £2574 / £3024 |
| AWS: A Hands-on Introduction to Cloud Computing | Edinburgh Training and Conference Venue | Tue, 2018-09-11 09:30 | £1287 / £1487 |
| JMeter Fundamentals and JMeter Advanced | Birmingham | Tue, 2018-09-18 09:30 | £2178 / £2828 |
| Test Automation with Selenium | St Helier, Jersey, Channel Isles | Tue, 2018-09-18 09:30 | £2970 / £4395 |
| Jenkins: Continuous Integration for Agile Development | Manchester, King Street | Thu, 2018-10-18 09:30 | £2574 / £3224 |
| CakePHP: Rapid Web Application Development | Birmingham | Tue, 2018-11-06 09:30 | £4356 / £5656 |
