5G and IoT Training Course

This instructor-led, live training in Botswana (online or onsite) is designed for intermediate-level telecom professionals, AI engineers, and IoT specialists who wish to investigate how 5G networks accelerate Edge AI applications.

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

• Grasp the fundamentals of 5G technology and its impact on Edge AI.
• Deploy AI models optimised for low-latency applications within 5G environments.
• Implement real-time decision-making systems using Edge AI and 5G connectivity.
• Optimise AI workloads for efficient performance on edge devices.

This instructor-led, live training in Botswana (online or onsite) is aimed at intermediate-level professionals who wish to understand and evaluate the behaviour, scope, and implementation of 5G networks in technical environments.

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

• Analyze the behavior of 5G networks in clustered environments.
• Understand the RF environment specific to 5G technology.
• Evaluate real-world cases of 5G implementation from other countries.
• Assess 5G coverage capabilities and limitations.
• Interpret and analyze 5G network quality parameters on a technical level.

5G represents the fifth generation of mobile network technology, delivering enhanced speeds, reduced latency, and more dependable connectivity for a diverse array of applications.

This instructor-led live training, available either online or on-site, is designed for intermediate IT professionals and technical managers seeking to grasp the fundamentals, architecture, and business impact of 5G networks.

After completing this training, participants will be equipped with the knowledge and skills to:

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

Course Format

• Interactive lectures and group discussions.
• Case studies and scenario-based exercises.
• Hands-on 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, subject to request.

6G represents the upcoming generation of wireless communication standards, set to revolutionize IoT ecosystems by offering ultra-fast connectivity, sophisticated sensing, and integrated artificial intelligence capabilities.

This instructor-led, live training (available online or onsite) is designed for advanced-level participants seeking to comprehend and exploit the emerging synergy between 6G technologies and IoT applications.

Upon completing this course, learners will be able to:

• Articulate the core technical concepts underpinning 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 organizational technology roadmap, 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.

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 (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.

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.