Online or onsite, instructor-led live Telecom training courses demonstrate through interactive hands-on practice the fundamentals and advanced topics of Telecom.

Telecom 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 Telecom trainings in the US can be carried out locally on customer premises or in NobleProg corporate training centers.

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Testimonials

★★★★★

The Colab Notebooks with the training and examples notes.

Felix Navarro, Motorola Solutions

Course: Deep Learning for Telecom (with Python)

The exercises were very good and interactive. Instructors were always answering all questions and providing their insight on all topics

Felix Navarro, Motorola Solutions

Course: Deep Learning for Telecom (with Python)

Trainer knows very well the subject. He try to give a lot of examples in order that we understand "how" it is working. He answer to all questions raised. Very available.

christel salve - BICS

Course: Blockchain for Telecom

lots of information, all questions ansered, interesting examples

A1 Telekom Austria AG

Course: Deep Learning for Telecom (with Python)

The paste, all the information I got.

Tele 2 Sverige AB

Course: OpenStack for Telecom

I like that we before the training had some meetings to discuss what parts we should focus on, and what is interesting for us at Tele2.

Tele 2 Sverige AB

Course: OpenStack for Telecom

The varied topics

Daniel Lindh - Tele 2 Sverige AB

Course: OpenStack for Telecom

Telecom Course Outlines

Course Name

Duration

Overview

Course Name

Duration

Overview

Deep Learning for Telecom (with Python)

28 hours

In this instructor-led, live training in the US, participants will learn how to implement deep learning models for telecom using Python as they step through the creation of a deep learning credit risk model. By the end of this training, participants will be able to:

Understand the fundamental concepts of deep learning.
Learn the applications and uses of deep learning in telecom.
Use Python, Keras, and TensorFlow to create deep learning models for telecom.
Build their own deep learning customer churn prediction model using Python.

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

Blockchain for Telecom

7 hours

In this instructor-led, live training in the US, we examine the core principles behind Blockchain technology and gain an understanding of its overall architecture and functionality. Throughout the course, we examine Blockchain technology's specific applications within the Telecom industry. Scenarios include security, payment systems, and user verification.

BSS (BUSINESS SUPPORT SYSTEM) for Telecom

21 hours

BSS Course Contents :
This course is primarily aimed at managers in Telecom operation who need to have 360
view of a) legacy BSS in eTOM b) emerging BSS in NGOSS c) Billing system including
mediation, rating and CDR in details. This course also introduces in new topics like
advanced big data based CRM, Churn management and Fraud Management.

Digital Identity for Telecom

21 hours

This instructor-led, live training in the US is aimed at engineers in telecommunication companies who wish to set up an end-to-end digital identity management system. By the end of this training, participants will be able to:

Understand, evaluate and adopt different approaches to managing usernames and passwords.
Setup a single login system that works across all applications used in a telecom environment.
Use identity technology to get a clear understanding of their customers and their needs.
Implement an authentication system that works across different platforms (laptop, mobile, etc.).

OpenStack for Telecom

14 hours

This instructor-led, live training in the US (online or onsite) is aimed at engineers, architects and managers who wish to deploy an OpenStack cloud to manage their Telecom infrastructure. By the end of this training, participants will be able to:

Plan, deploy, and administer OpenStack as a private cloud.
Understand IaaS architecture and its implementation under OpenStack.
Replace physical routers and servers with virtual machines running in a private cloud.
Reduce infrastructure and maintenance costs through virtualization and cloud computing.
Expedite the rollout of new services to customers.

OSS ( Operation Support System ) for Telecom

21 hours

Introduction: OSS/BSS is at the heart of operation of any Telecom operator. Given growth of Big Data in recent time,
area of OSS/BSS has undergone disruptive changes specially with virtualization of the OSS/BSS and given
the fact, many of the new OTT ( Over the top) services are newly developed web/mobile based services
that do not fit into legacy OSS. In this current course, which consists of 4 days, first 3 days are spent
extensively to develop background in legacy OSS/BSS, while last 5 modules, are dedicated to explain
emerging Big Data analytics application in OSS/BSS layer Target Audience:

Telecom/Cellular Operation People
Telecom Sales professionals
Telecom Operation vendors/contractors
CXO, VP, Director level managers in TELECOM

Wireless Network and Telecom Network Security

35 hours

This instructor-led, live training in the US (online or onsite) is aimed at technical persons who wish to apply the most suitable tools and techniques to secure both telecom as well as wireless networks.

Last Updated: 2023-11-15