6G and IoT Training Course

The primary goal of this training is to clarify what the 5G network entails and its influence on smart technologies. The focus is on illustrating both the benefits and drawbacks of this technological synergy (5G / IoT), while also highlighting the developmental trajectory of a network inherently designed for the smart ecosystem from its inception.

"6G and the Intelligent Edge" is a forward-looking course that explores the integration of 6G wireless technologies with edge computing, IoT ecosystems, and AI-driven data processing to support intelligent, low-latency, and adaptive infrastructures.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT architects who wish to understand and design next-generation distributed architectures leveraging the synergy of 6G connectivity and intelligent edge systems.

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

• Understand how 6G will transform edge computing and IoT architectures.
• Design distributed systems for ultra-low latency, high bandwidth, and autonomous operations.
• Integrate AI and data analytics at the edge for intelligent decision-making.
• Plan scalable, secure, and resilient 6G-ready edge infrastructures.
• Evaluate business and operational models enabled by 6G-edge convergence.

Format of the Course

• Interactive lectures and discussions.
• Case studies and applied architecture design exercises.
• Hands-on simulation with optional edge or container tools.

Course Customization Options

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

The 'Preparing Infrastructure for 6G: Network Design Essentials' programme is a targeted training initiative designed to equip existing telecom and enterprise networks for the upcoming era of wireless connectivity. It achieves this through advanced architectural frameworks and engineering methodologies. Key areas of focus include the evolution of transport and fronthaul networks, cloud-native and open RAN architectures, edge and distributed computing, precise timing and synchronization, spectrum and RF preparedness, automation and AI-driven operations, and practical migration pathways for operators and enterprises.

This live, instructor-led training (available online or onsite) caters to intermediate-level telecom engineers and network architects aiming to design, optimise, and evolve their current 4G/5G infrastructure to satisfy the performance, scalability, and reliability demands of 6G.

Upon completing this course, participants will be able to:

• Evaluate current network infrastructure gaps and assess readiness for 6G evolution.
• Design transport and fronthaul/backhaul architectures tailored for ultra-low latency and high throughput.
• Implement cloud-native principles, integrate vRAN/O-RAN solutions, and optimise edge compute placement for 6G applications.
• Plan timing, synchronization, and RF upgrades necessary for mmWave/THz and dense network deployments.
• Establish testing, validation, and operational monitoring strategies to guarantee performance and reliability.
• Develop a phased migration and investment roadmap aligned with business objectives and risk management protocols.

Course Format

• Technical lectures and in-depth architecture discussions.
• Case studies and design workshops.
• Practical labs utilising simulation and verification tools.

Customisation Options

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

This live, instructor-led training, available online or onsite, is designed for executive-level professionals seeking to grasp the global 6G landscape, evaluate its commercial potential, and prepare for early strategic investments.

Upon completing this course, participants will acquire the necessary insights to:

• Recognise emerging market trends and global initiatives that are shaping the 6G ecosystem.
• Comprehend the regulatory frameworks and spectrum allocation schedules associated with IMT-2030.
• Assess the changing vendor landscape and the current levels of technology readiness.
• Formulate a strategic roadmap for early investment, research collaborations, and pilot projects.

AI and Digital Twins in 6G Networks is an advanced, specialised course that explores how digital twin technology and AI-native optimization converge to model, simulate, and operate next-generation 6G infrastructures.

This instructor-led, live training (online or onsite) is aimed at advanced-level professionals who wish to apply digital twin methodologies and AI techniques to design, validate, and optimize 6G network behavior in realistic, reproducible environments.

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

• Explain the role and architecture of digital twins in the lifecycle of 6G networks.
• Build and configure digital twin models for RAN, transport, and edge compute components.
• Apply AI/ML methods for closed-loop optimization, anomaly detection, and predictive maintenance of network elements.
• Integrate real-time telemetry and simulation data to enable model-driven orchestration and intent-based control.
• Design validation and verification workflows using co-simulation, emulation, and digital twin testbeds.

Format of the Course

• Technical lectures and architecture deep-dives.
• Hands-on labs with simulators, twin models, and ML toolchains.
• Case study walkthroughs and a practical mini-project integration exercise.

Course Customization Options

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

Technological advancements and the exponential growth of information are fundamentally transforming business operations across numerous industries, including the public sector. The rate of government data generation and digital archiving is accelerating, driven by the rapid proliferation of mobile devices and applications, smart sensors and IoT devices, cloud computing solutions, and citizen-facing digital portals. As digital information expands in volume and complexity, the challenges associated with information management, processing, storage, security, and disposition become increasingly sophisticated. New tools for capture, search, discovery, and analysis are enabling organizations to derive valuable insights from unstructured data. The government sector is reaching a tipping point, recognizing information as a strategic asset. Governments must now protect, leverage, and analyze both structured and unstructured data to better serve citizens and meet mission requirements. As government leaders strive to evolve into data-driven organizations, they are laying the groundwork to correlate dependencies across events, people, processes, and information.

High-value government solutions are emerging from a combination of the most disruptive technologies:

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

Big Data is one such intelligent industry solution that empowers government entities to make better decisions by taking action based on patterns revealed through the analysis of large volumes of data—whether related or unrelated, structured or unstructured.

However, achieving these capabilities requires more than simply accumulating massive quantities of data. "Making sense of these volumes of Big Data requires 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 noted 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 maximize the potential of the Big Data explosion and the tools necessary to analyze it.

The challenges posed by Big Data are nearly as daunting as its promise is encouraging. One significant challenge is storing data efficiently. With budgets often tight, agencies must minimize the per-megabyte cost of storage while ensuring data remains easily accessible so users can retrieve it when and how they need it. Additionally, backing up massive amounts of data compounds this challenge.

Effectively analyzing data is another major hurdle. Many agencies utilize commercial tools to sift through vast amounts 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 allowing 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 used for more routine tasks, such as sifting through resumes to connect job candidates with hiring managers.

This instructor-led, live training in Botswana (online or on-site) is designed for 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 Botswana (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.

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

This instructor-led live training, available either online or on-site, is designed for beginner-level technical professionals aiming to grasp and apply concepts related to embedded systems and IoT using C programming and microcontroller architectures.

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

• Comprehend the architecture and components of embedded systems.
• Write and compile C code to interact with embedded hardware.
• Utilize microcontroller peripherals such as timers and Analog-to-Digital Converters (ADCs).
• Understand the role of embedded systems within IoT architectures.

Course Format

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

Course Customization Options

• To arrange customized training for this course, please contact us.

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

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

• Grasp the principles and benefits of Federated Learning in IoT and edge computing.
• Implement Federated Learning models on IoT devices for decentralized AI processing.
• Reduce latency and improve real-time decision-making in edge computing environments.
• Address challenges related to data privacy and network constraints in IoT systems.

6G represents the next generation of wireless networking, building upon the advancements of 5G to deliver ultra-low latency, extremely high throughput, pervasive intelligence, and integrated sensing capabilities. These features enable new classes of applications and services that were previously unattainable.

This instructor-led, live training is available online or onsite and is designed for beginner to intermediate-level professionals seeking to understand the technical foundations, regulatory landscape, and strategic business impacts of 6G to inform planning and decision-making.

Upon completing this training, participants will be able to:

• Explain core 6G concepts and distinguish them from 5G.
• Identify key enabling technologies and their practical implications.
• Assess high-value use cases and industry verticals that 6G will facilitate.
• Understand spectrum, regulatory, and policy considerations for 6G adoption.
• Draft a high-level 6G readiness roadmap for their organisation.

Format of the Course

• Interactive lectures with conceptual walkthroughs.
• Case studies and sector-specific examples.
• Group workshop to develop an organisational 6G readiness outline.

Course Customization Options

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

This instructor-led, live training in Botswana (online or onsite) is aimed at advanced-level IoT developers and smart home enthusiasts who wish to automate IoT processes and create innovative solutions using n8n.

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

• Set up and configure n8n for IoT workflow automation.
• Integrate IoT devices and platforms using n8n nodes and connectors.
• Implement custom workflows to automate IoT tasks and processes.
• Use IoT protocols like MQTT and REST APIs within n8n workflows.
• Monitor, troubleshoot, and optimize IoT automation workflows.

In this instructor-led, live training held in Botswana, participants will learn how to maximise Nginx performance by setting up, configuring, monitoring, and troubleshooting it to manage various forms of HTTP and TCP traffic. Topics include configuring the most important Nginx parameters, the operating system, and virtual machines to gain maximum value from Nginx.

This instructor-led, live training in Botswana (online or onsite) is aimed at intermediate-level IoT developers, embedded engineers, and AI practitioners who wish to implement TinyML for predictive maintenance, anomaly detection, and smart sensor applications.

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

• Understand the fundamentals of TinyML and its applications in IoT.
• Set up a TinyML development environment for IoT projects.
• Develop and deploy ML models on low-power microcontrollers.
• Implement predictive maintenance and anomaly detection using TinyML.
• Optimize TinyML models for efficient power and memory usage.