5G and IoT Training Course

This instructor-led, live training in South Africa (online or onsite) is designed for intermediate-level telecom professionals, AI engineers, and IoT specialists keen on exploring how 5G networks accelerate Edge AI applications.

Upon completion of this training, participants will be able to:

• Grasp the fundamentals of 5G technology and its influence on Edge AI.
• Deploy AI models optimized for low-latency applications within 5G environments.
• Implement real-time decision-making systems leveraging Edge AI and 5G connectivity.
• Optimize AI workloads to ensure efficient performance on edge devices.

This instructor-led, live training in South Africa (online or on-site) is aimed at business managers who wish to learn only the critical information needed to make important decisions about the adoption of 5G. This course is not a technical course but rather a course on the strategic thinking needed to prepare for the arrival of 5G. The technical coverage and industry coverage will be adapted to the audience.

By the end of this training, participants will be able to:

• Identify the opportunities that 5G brings to the organisation.
• Identify the risks that 5G poses to business and industry.
• Understand and distinguish the different technologies and standards underlying 5G.
• Understand the role that 5G will play in the further development of AI and IoT.
• Head up 5G initiatives that lead to improvements in customer service and operational efficiency.
• Initiate a strategy for adopting 5G products and services within the organisation as well as across external partner organisations.

This instructor-led, live training in South Africa (online or onsite) is designed for intermediate-level professionals seeking to comprehend and assess the dynamics, scope, and deployment of 5G networks within technical settings.

Upon completion of this training, participants will be equipped to:

• Analyse how 5G networks behave within clustered environments.
• Gain insight into the RF environment unique to 5G technology.
• Evaluate real-world 5G implementation examples from various countries.
• Assess the coverage capabilities and constraints of 5G.
• Interpret and analyse technical 5G network quality parameters.

5G represents the fifth generation of mobile network technology, facilitating faster data speeds, reduced latency, and more dependable connectivity across a diverse array of applications.

This instructor-led live training, available either online or at your premises, is designed for IT professionals and technical managers at an intermediate level who wish to grasp the fundamentals, architectural framework, and business impact of 5G networks.

Upon completing this training, participants will acquire the knowledge and skills to:

• Comprehend the core concepts and evolution of 5G technology.
• Identify the principal components and architecture of 5G networks.
• Differentiate between 4G LTE and 5G regarding performance and design.
• Evaluate 5G use cases and applications across various industries.
• Assess 5G deployment strategies and regulatory aspects.

Course Format

• Interactive lectures and group discussions.
• Case studies and scenario-based exercises.
• Practical exploration of 5G network architecture through live demonstrations.

Course Customisation Options

• This course can be tailored to focus on specific industry applications or regional 5G deployment contexts, upon request.

6G represents the forthcoming generation of wireless communication standards, poised to revolutionise IoT ecosystems through ultra-fast connectivity, advanced sensing, and integrated AI capabilities.

This instructor-led live training (available online or onsite) is designed for advanced-level participants who wish to understand and leverage the emerging intersection of 6G technologies and IoT applications.

Upon completing this course, learners will be able to:

• Explain the core technical concepts behind 6G.
• Assess how 6G will reshape IoT device communication and architecture.
• Evaluate 6G-enabled IoT use cases across industries.
• Prepare strategies for integrating 6G capabilities into existing IoT solutions.

Format of the Course

• Concept-focused lectures combined with expert discussion.
• Applied exercises designed to reinforce key engineering principles.
• Case-based exploration and scenario analysis in a guided environment.

Course Customization Options

• For tailored versions of this training aligned with your organisational technology roadmap, please contact us to arrange.

Technological advancements and the exponential growth of information are reshaping business operations across numerous sectors, including government. The volume of government data generation and digital archiving is surging, driven by the proliferation of mobile devices and applications, smart sensors and IoT devices, cloud computing solutions, and citizen-facing portals. As digital information becomes more expansive and complex, the management, processing, storage, security, and disposition of this data grow increasingly challenging. New tools for capture, search, discovery, and analysis are enabling organisations to extract valuable insights from unstructured data. The government sector is at a critical juncture, recognising information as a strategic asset. Governments must protect, leverage, and analyse both structured and unstructured data to enhance service delivery and meet mission requirements. As government leaders strive to evolve into data-driven organisations, they are laying the groundwork to correlate dependencies across events, people, processes, and information.

High-value government solutions will emerge from the integration of the most disruptive technologies:

• Mobile devices and applications
• Cloud services
• Social business technologies and networking
• Big Data and analytics

Big Data represents an intelligent industry solution that enables government bodies to make better decisions by acting on patterns revealed through the analysis of large volumes of data—both related and unrelated, structured and unstructured.

However, achieving these feats requires far more than simply accumulating massive quantities of data. "Making sense of these volumes of Big Data requires cutting-edge tools and technologies that can analyse and extract useful knowledge from vast and diverse streams of information," wrote Tom Kalil and Fen Zhao of the White House Office of Science and Technology Policy in a post on the OSTP Blog.

The White House took a significant step toward helping agencies identify these technologies by establishing the National Big Data Research and Development Initiative in 2012. This initiative allocated over $200 million to maximise the potential of the Big Data explosion and the tools required to analyse it.

The challenges posed by Big Data are nearly as daunting as its promise is encouraging. Efficient data storage is one such challenge. With budgets always tight, agencies must minimise the per-megabyte cost of storage while ensuring data remains easily accessible so users can retrieve it when and how they need it. Backing up massive quantities of data further intensifies this challenge.

Effective data analysis presents another major hurdle. Many agencies utilise commercial tools that allow them to sift through mountains of data, identifying trends that enhance operational efficiency. (A recent MeriTalk study found that federal IT executives believe Big Data could help agencies save over $500 billion while also fulfilling mission objectives.)

Custom-developed Big Data tools are also enabling agencies to address their data analysis needs. For instance, the Oak Ridge National Laboratory’s Computational Data Analytics Group has made its Piranha data analytics system available to other agencies. This system has helped medical researchers identify links that can alert doctors to aortic aneurysms before they occur. It is also employed for more routine tasks, such as sifting through resumes to connect job candidates with hiring managers.

This instructor-led, live training in South Africa (online or onsite) is aimed at intermediate-level IT professionals and business managers who wish to understand the potential of IoT and edge computing for enabling efficiency, real-time processing, and innovation in various industries.

By the end of this training, participants will be able to:

• Understand the principles of IoT and edge computing and their role in digital transformation.
• Identify use cases for IoT and edge computing in manufacturing, logistics, and energy sectors.
• Differentiate between edge and cloud computing architectures and deployment scenarios.
• Implement edge computing solutions for predictive maintenance and real-time decision-making.

This instructor-led, live training in South Africa (online or onsite) is aimed at intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI for enhancing IoT applications with intelligent data processing and analytics capabilities.

By the end of this training, participants will be able to:

• Understand the fundamentals of Edge AI and its application in IoT.
• Set up and configure Edge AI environments for IoT devices.
• Develop and deploy AI models on edge devices for IoT applications.
• Implement real-time data processing and decision-making in IoT systems.
• Integrate Edge AI with various IoT protocols and platforms.
• Address ethical considerations and best practices in Edge AI for IoT.

This instructor-led, live training in South Africa (online or onsite) is aimed at product managers and developers who wish to use Edge Computing to decentralize data management for faster performance, leveraging smart devices located on the source network.

By the end of this training, participants will be able to:

• Understand the basic concepts and advantages of Edge Computing.
• Identify the use cases and examples where Edge Computing can be applied.
• Design and build Edge Computing solutions for faster data processing and reduced operational costs.

Embedded systems are dedicated computing architectures engineered to execute specific tasks within broader ecosystems. The Internet of Things (IoT) refers to a network of physical devices equipped with sensors and software, enabling them to communicate and share data via the internet.

This instructor-led live training, available both online and onsite, is tailored for technical professionals at a beginner level who wish to grasp and apply embedded systems and IoT principles using C programming and microcontroller architectures.

Upon completion of this training, participants will be able to:

• Comprehend the architecture and constituent parts of embedded systems.
• Write and compile C code to facilitate interaction with embedded hardware.
• Operate microcontroller peripherals, including timers and ADCs.
• Appreciate the role of embedded systems within IoT architectures.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live laboratory environment.

Customisation Options

• For tailored training needs, please contact us to arrange a bespoke session.

This instructor-led live training in South Africa (online or onsite) is aimed at intermediate-level professionals who wish to apply Federated Learning to optimise IoT and edge computing solutions.

By the end of this training, participants will be able to:

• Grasp the principles and advantages of Federated Learning in IoT and edge computing.
• Deploy Federated Learning models on IoT devices for decentralized AI processing.
• Minimise latency and enhance real-time decision-making in edge computing environments.
• Address challenges concerning data privacy and network constraints in IoT systems.

The Internet of Things (IoT) refers to a network infrastructure that wirelessly connects physical objects and software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. C is a general-purpose programming language often recommended for IoT development due to its widespread use and low-level programming advantages.

In this instructor-led live training, participants will learn how to programme IoT solutions using C.

By the end of this training, participants will be able to:

• Install and configure NetBeans for programming IoT systems with C
• Understand the fundamentals of IoT architecture
• Learn the benefits of using C in programming IoT systems
• Build, test, deploy, and troubleshoot an IoT system using C

Audience

• Developers
• Engineers

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

• To request a customised training for this course, please contact us to arrange.

Unlike other technologies, the Internet of Things (IoT) is significantly more complex, spanning almost every branch of core engineering including Mechanical, Electronics, Firmware, Middleware, Cloud, Analytics, and Mobile. For each of its engineering layers, there are critical aspects of economics, standards, regulations, and the evolving state of the art. For the first time, this modest course is offered to cover all of these critical aspects of IoT Engineering.

Summary

An advanced training programme covering the current state of the art in the Internet of Things

Cuts across multiple technology domains to develop awareness of an IoT system, its components, and how it can help businesses and organizations.

Live demos 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 who wish to understand 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 effectively.

Estimates for the Internet of Things or IoT market value are massive. By definition, 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 solutions, RFID, lighting and heating products, and a number of applications in the Industrial Internet.

However, the underlying technologies of IoT are nothing new as Machine-to-Machine (M2M) communication existed since the birth of the Internet. What changed in the last couple of years is the emergence of numerous inexpensive wireless technologies added by the overwhelming adoption of smartphones and tablets in every home. The explosive growth of mobile devices led to the current demand for IoT.

Due to unbounded opportunities in IoT business, a large number of small and medium-sized entrepreneurs jumped on the bandwagon of the IoT gold rush. Also, due to the emergence of open-source electronics and IoT platforms, the cost of developing IoT systems and further managing their sizable production is increasingly affordable. Existing electronic product owners are experiencing pressure to integrate their devices with the Internet or mobile apps.

This training is intended for a technology and business review of this emerging industry so that IoT enthusiasts and entrepreneurs can grasp the basics of IoT technology and business.

Course Objective

The 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, Government, Mobile Cellular, and other areas.

Basic introduction to 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 apps for registration, data acquisition, and control – Available M2M data acquisition platforms for IoT such as Xively, Omega, and NovoTech, etc.

Security issues and security solutions for IoT

Open source/commercial electronics platforms for IoT: Raspberry Pi, Arduino, ArmMbedLPC, etc.

Open source/commercial enterprise cloud platforms for AWS-IoT apps, Azure-IoT, Watson-IoT cloud in addition to other minor IoT clouds

Studies of the business and technology of some common IoT devices like home automation, smoke alarms, vehicles, military applications, home health, etc.

In this instructor-led, live training in South Africa, participants will explore the various aspects of NB-IoT (also known as LTE Cat NB1) while developing and deploying a sample NB-IoT-based application.

By the end of this training, participants will be able to:

• Identify the different components of NB-IoT and understand how they fit together to form an ecosystem.
• Understand and explain the security features built into NB-IoT devices.
• Develop a simple application to track NB-IoT devices.

This instructor-led, live training (online or onsite) is aimed at beginner-level and intermediate-level telecom engineers and field professionals who wish to use structured deployment methodologies and industry best practices to successfully install, supervise, integrate, and manage multi-vendor wireless networks from 2G to 5G across operator and enterprise environments.

By the end of this training, participants will be able to:

• Install and configure multi-vendor BTS systems (Huawei, ZTE, Ericsson) from 2G to 5G.
• Supervise site deployment activities and coordinate RF, transmission, power, civil, and core network teams during integration.
• Prepare telecom sites for ATP (Acceptance Test Procedure) and manage operator handover processes.
• Monitor wireless KPIs and manage cluster-based and region-based network operations within commercial and technical reporting structures.