Online or onsite, instructor-led live Predictive Analytics training courses demonstrate through hands-on practice how to use different tools to build predictive models and apply them to large sample data sets to predict future events based on the data.
Predictive Analytics training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Predictive Analytics trainings in Dublin can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Dublin Ballsbridge
Regus Dublin Ballsbridge, Alexandra House, Ballsbridge, Dublin, Ireland, D04 C7H2
The modern, marble-fronted Ballsbridge building stands in the commercial centre of Dublin. It is close to the city's banking ...
The modern, marble-fronted Ballsbridge building stands in the commercial centre of Dublin. It is close to the city's banking and financial institutions as well as foreign embassies. The Dublin 4 area covers businesses literally from A to Z and almost any support or service is just a few minutes' walk away. These enterprises range from the micro to multinational, with the sectors covered stretching from traditional professional and financial services to cutting-edge IT and support. Dublin has energy and passion for doing business. New opportunities abound and there is a growing number of outlets, such as business networking groups, to help support growing firms reach their full potential.
Pembroke House is home to a thoroughly modern business centre within an impressive, historic Georgian building. The address l...
Pembroke House is home to a thoroughly modern business centre within an impressive, historic Georgian building. The address lies within the commercial district of the capital and means it offers excellent business connections to the diverse enterprises of Dublin. With many financial and IT enterprises already operating successfully, the area around this location puts occupiers at the very heart of business life. This proximity of the centre to other firms opens up numerous networking and business development opportunities often literally on the doorstep. When it comes to selecting advisers and support services there are plenty of options available for any size of organisation. All this comes with excellent transport links and other amenities.
The Crescent Building is located in a prestigious business park just 5 minutes from Dublin airport. With its own dedicated gr...
The Crescent Building is located in a prestigious business park just 5 minutes from Dublin airport. With its own dedicated ground floor entrance this striking, crescent-shaped building features floor to ceiling tinted-glass windows on every level. The stylish, business centre is perfectly situated between Dublin city centre and the airport and also has easy access to both the M1 and M50 motorways. A large number of global pharmaceutical, information and telecommunication companies have bases in Dublin, which is the economic heart of Ireland. Hotels, cafes, restaurants and other amenities are nearby.
Our Dublin, The Chase, business centre provides the best possible working environment thanks to its innovative design, qualit...
Our Dublin, The Chase, business centre provides the best possible working environment thanks to its innovative design, quality construction and stunning architecture. The exceptionally high spec, mixed-use location provides a clean, efficient space to work in alongside a number of international blue-chip corporations in the highly sought after Sandyford Industrial Estate. If you are networking or meeting with clients, there are excellent transport links with close connections to the Luas tram network, M50, the airport, N11 and a quality bus link. If you want to conduct business in a more social setting, not only are there on-site dining facilities, but also a host of options a little further afield. And with the famous Leopardstown racecourse on the doorstep, client entertainment couldn’t be easier. With easy accessibility, a wide variety of essential amenities such as banks, supermarkets, hotels and corporate lettings, Sandyford is one of the most popular business locations in Ireland.
Dublin Jury Inn
Dublin - Jury's Inn, Moore Street Plaza, Parnell Street, Dublin 1, ireland
Directions:
From Airport by Car (8 km): Follow the signs for the city cen...
Directions:
From Airport by Car (8 km): Follow the signs for the city centre to the M1 motorway city bound.
Leaving the motorway continue straight onto Drumcondra Road. This road leads into Lower Dorset Street.
Turn left onto Hardwicke Street. Continue straight ahead onto Hardwicke Place. Bear left onto George's Place. Bear right onto Temple Street. Turn right onto Denmark Street. Continue straight ahead onto Gardiner Row.
Turn left onto Parnell Square East. Continue straight ahead onto Cavendish Row.
Bear right onto Parnell Street. Jurys Inn Dublin Parnell Street is on the left.
Connelly Station (1.6 km): Leave the station and cross Matt Talbot Bridge. Turn right onto George's Quay. Continue straight on Burgh Quay and then onto Aston Quay. Turn right onto O'Connell Street and at the end of that street take a left onto Parnell Street. Jurys Inn Dublin Parnell Street is on your left.
Heuston Station (3.2 km): Leave the station and take a left towards the city centre. Follow the quays along the river. Turn left onto O'Connell Street. Continue straight and turn left onto Parnell Street. Jurys are on the left.
Dun Laoghaire Ferry Port (8 km): Leave the station and cross Matt Talbot Bridge. Turn right onto George's Quay. Continue straight on Burgh Quay and then onto Aston Quay. Turn right onto O'Connell Street and at the end of that street take a left onto Parnell Street. Jurys Inn Dublin Parnell Street is on your left.Turn left onto George's Street Upper. Turn right onto Marine Road. Turn left onto Eblana Avenue. Turn left onto Sussex Street. Turn right onto George's Street Lower. Continue straight on Cumberland Street. Continue straight on Dun Laoighre Road. Continue straight on Longford Place. Continue straight on Monkstown Crescent. Turn Left onto Carrickbrennan Road. Bear left onto Monkstown Road. Bear right onto Temple Hill. Continue straight on Temple Road. Continue straight on Frascati Road. Continue straight on Rock Road. Continue straight on Merrion Road. Continue straight on Pembroke Road. Continue straight on Northumberland Road. Continue straight on Mount Street Lower. Bear right onto Grattan Court East. Bear right onto Grattan Street. Turn left onto Hogan Place. Continue straight on Fenian Street. Bear right onto Sandwith Street Upper. Bear left onto Pearse Street. Turn right onto Tara Street. Continue straight over Butt Bridge. Continue straight on Beresford Place. Continue straight on Abbey Street Lower. Bear right onto Beresford Place. Turn Left onto Gardiner Street Lower. Turn left onto Sean MacDermott Street Lower. Turn right onto Cumberland Street. Bear left onto Britain Place. Bear left onto Parnell Street. Jurys located on the left.
Car Parking: Parking is available only 5 min walk from hotel at Clerys Q-Park Multi Storey Car Park located at Marlborough St. Jurys Inn Hotel Guests can avail of discount rates as follows: evening parking for €4.00 (6pm - midnight) and €10.00 for 24 hour. Ensure to get your ticket validated at the hotel reception and pay for your parking at the QPark Car Park Office located at the pedestrian entrance on Marlborough Street.
Opening times and prices may change at the car park operator’s discretion and as such the information is a guideline only. Please check at the entrance to the car park to obtain exact prices, opening times and closing times. Tel: (01) 8748902 | Web: www.q-park.ie
This instructor-led, live training in Dublin (online or onsite) is aimed at technical persons who wish to build machine learning models using algorithms such as GLM, Deep Learning and Random Forests.
By the end of this training, participants will be able to:
Install and configure H2O.
Create machine learning models using different popular algorithms.
Evaluate models based on the type of data and business requirements.
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.
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
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.
This instructor-led, live training in Dublin (online or onsite) is aimed at data scientists and data analysts who wish to automate, evaluate, and manage predictive models using DataRobot's machine learning capabilities.
By the end of this training, participants will be able to:
Load datasets in DataRobot to analyze, assess, and quality check data.
Build and train models to identify important variables and meet prediction targets.
Interpret models to create valuable insights that are useful in making business decisions.
Monitor and manage models to maintain an optimized prediction performance.
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.
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
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.
RapidMiner is an open source data science software platform for rapid application prototyping and development. It includes an integrated environment for data preparation, machine learning, deep learning, text mining, and predictive analytics.
In this instructor-led, live training, participants will learn how to use RapidMiner Studio for data preparation, machine learning, and predictive model deployment.
By the end of this training, participants will be able to:
Install and configure RapidMiner
Prepare and visualize data with RapidMiner
Validate machine learning models
Mashup data and create predictive models
Operationalize predictive analytics within a business process
Troubleshoot and optimize RapidMiner
Audience
Data scientists
Engineers
Developers
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.
This classroom based training session will contain presentations and computer based examples and case study exercises to undertake.
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Testimonials (4)
All the examples used and the lecturing style was on point even for a begginer i was able to understand and the training was so patient and always willing to go extra mile when in need of assistance.
Mathipa Chepape - Vodacom
Course - Big Data Business Intelligence for Telecom and Communication Service Providers
The exercises.
Elena Velkova - CEED Bulgaria
Course - Predictive Modelling with R
Good detail on what R is used for and how to start using it right away
Hoss Shenassa - Trimac Management Services LP
Course - Introduction to R with Time Series Analysis
The content, as I found it very interesting and think it would help me in my final year at University.
Krishan - NBrown Group
Course - From Data to Decision with Big Data and Predictive Analytics
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