5G and IoT Application Training Course

Did you know that organizations investing in 5G and IoT integration are seeing transformative results boosting operational efficiency by up to 40%, reducing production downtime, and unlocking real-time decision-making across industries valued at over $1 trillion globally in 2025?

Course Overview

The 5G and IoT Application Training Course by Rcademy is meticulously designed to equip telecommunications and digital transformation professionals with comprehensive knowledge and advanced skills needed for 5G-enabled IoT system design, deployment, and optimization. This comprehensive program delves into cutting-edge 5G methodologies, providing participants with a robust understanding of how to implement network slicing, deploy Multi-Access Edge Computing, and integrate artificial intelligence for intelligent IoT ecosystems while ensuring ultra-low latency, high reliability, and security across diverse vertical industries.

Without specialized 5G and IoT training, engineers may struggle to implement network slicing, manage massive IoT deployments, or integrate AI-driven optimization, which are essential for Industry 4.0 and digital transformation initiatives. The program’s structured curriculum ensures professionals gain end-to-end mastery of 5G-IoT convergence, preparing them for real-world deployment challenges across manufacturing, mining, healthcare, and smart city applications.

The 5G and IoT Application Training Course provides a comprehensive framework covering 5G network architecture, massive IoT technologies, network slicing, edge computing, private networks, security frameworks, and AI integration. Professionals will learn to master 5G network architecture and protocols for IoT ecosystems, develop expertise in deploying massive, critical, and broadband IoT solutions, design network slicing strategies for diverse applications, apply MEC principles for ultra-low latency services, architect private 5G networks for enterprise use, integrate AI/ML for intelligent network optimization, evaluate security frameworks and spectrum management, and lead end-to-end implementation projects for smart cities, Industry 4.0, autonomous systems, and connected healthcare.

Research shows organizations who implement 5G and IoT training gain significant advantages through private 5G deployments, as demonstrated by Bosch’s UK facility where collaboration with Ericsson and British Telecom created the UK’s first private 5G network for Industry 4.0 automation, supporting machine sensors, mobile robotics, and predictive maintenance with real-time production data analysis that boosted efficiency, safety, and reduced operational downtime by 15%. Studies show industrial organizations implementing 5G-enabled smart mining achieve better performance, with Shanxi Coking Coal Group’s 5G network supporting over 50 real-time HD cameras and IoT sensors, enabling autonomous mining trucks and predictive maintenance that achieved 25% improvement in cost efficiency and 10% reduction in energy consumption.

Studies show that individuals who complete 5G and IoT training benefit from mastery of end-to-end 5G IoT design and deployment, as participants gain technical proficiency in designing standalone and non-standalone 5G networks tailored for IoT services, with exposure to real-world case studies equipping professionals with skills in spectrum allocation, massive device management, and low-latency application design. Personal benefits include leadership in AI and network automation, as engineers develop insight to manage intelligent IoT ecosystems through implementation of ML-based orchestration for automated resource distribution, positioning professionals to contribute to telecom innovation and play strategic roles in digital transformation projects. Additional personal benefits include industry readiness for smart systems and IoT integration, as the curriculum bridges technical 5G concepts with enterprise use cases, helping learners apply advanced concepts to sectors such as healthcare, logistics, and manufacturing, with graduates emerging ready to manage cross-domain IoT initiatives combining cloud-native 5G, AI analytics, and edge computing.

Take charge of your 5G expertise. Enroll now in the Rcademy 5G and IoT Application Training Course to master the competencies that drive digital transformation and accelerate your professional advancement.

Who Should Attend?

The 5G and IoT Application Training Course by Rcademy is ideal for:

• Senior network architects and 5G/IoT solution designers
• Principal engineers specializing in mobile networks, IoT platforms, and wireless technologies
• Technical leads and system integrators managing 5G rollouts and IoT infrastructure
• IoT platform architects and embedded systems specialists
• Telecom operations managers overseeing next-generation network deployments
• Industrial automation engineers and Industry 4.0 transformation leaders
• R&D professionals and consultants focused on 5G-IoT convergence
• Smart city project managers
• Healthcare technology specialists implementing connected medical devices
• Logistics and supply chain technology professionals
• Energy sector engineers implementing smart grid solutions
• Autonomous vehicle system developers
• Government technology advisors
• Academic researchers in telecommunications
• Technical sales engineers in telecom equipment

What are the Training Goals?

The main objectives of The 5G and IoT Application Training Course by Rcademy are to enable professionals to:

• Master advanced 5G network architecture, protocols, and service delivery mechanisms for IoT ecosystems
• Develop expertise in deploying massive IoT, critical IoT, and broadband IoT solutions using 5G technologies
• Design and implement network slicing strategies for diverse IoT applications and vertical industries
• Apply Multi-Access Edge Computing (MEC) principles to enable ultra-low latency IoT services
• Architect and deploy private 5G networks for enterprise and industrial IoT applications
• Integrate AI and machine learning techniques for intelligent 5G-IoT network optimization and automation
• Evaluate security frameworks, regulatory compliance, and spectrum management for 5G-enabled IoT deployments
• Lead end-to-end implementation projects for smart cities, Industry 4.0, autonomous systems, and connected healthcare
• Understand the evolution from 4G/LTE to 5G and IMT-2020 specifications
• Implement NB-IoT and LTE-M technologies for massive IoT applications
• Integrate 5G with enterprise IT and OT infrastructure
• Apply security and privacy frameworks for 5G IoT
• Optimize quality of service and performance for IoT traffic
• Apply advanced 5G-Advanced technologies and understand future trends

How Will This Training Course Be Presented?

At Rcademy, the extensive focus is laid on the relevance of the training content to the audience. Thus, content is reviewed and customised as per the professional backgrounds of the audience.

The training framework includes:

• Expert-led lectures delivered by experienced 5G professionals using audio-visual presentations
• Interactive practical training ensured through sample assignments or projects and 5G network simulations
• Trainee participation encouraged through hands-on activities that reinforce theoretical concepts
• Case studies featuring real-world 5G and IoT deployment challenges from various international contexts
• Best practice sharing sessions where participants discuss digital transformation experiences

The theoretical part of training is delivered by an experienced professional from the relevant domain, using audio-visual presentations. This immersive approach fosters practical skill development and real-world application of 5G and IoT principles through comprehensive coverage of network slicing, edge computing, and AI integration.

This theoretical-cum-practical model ensures participants gain both foundational knowledge and practical skills needed for effective 5G IoT system design and deployment excellence.

Register now to experience a truly engaging, participant-focused learning journey designed to equip you for success in next-generation connectivity and digital transformation.

Course Syllabus

Module 1: Foundations of 5G and IoT Convergence

• Evolution from 4G/LTE to 5G and impact on IoT ecosystems
• IMT-2020 specifications and 5G service categories (eMBB, URLLC, mMTC)
• IoT application characteristics and connectivity requirements
• Massive Machine-Type Communications (mMTC) architecture and capabilities
• Critical IoT and Ultra-Reliable Low-Latency Communications (URLLC)
• Industrial IoT, Broadband IoT, and Cellular IoT (CIoT) classifications
• 3GPP standards evolution for IoT (Release 13-18)
• Comparative analysis: NB-IoT, LTE-M, and 5G NR for IoT​

Module 2: 5G Network Architecture for IoT Applications

• 5G System Architecture and Service-Based Architecture (SBA)
• 5G Core Network (5GC) functions and IoT-specific enhancements
• Radio Access Network (RAN) architecture for IoT connectivity
• Network Function Virtualization (NFV) and Software-Defined Networking (SDN)
• Integration of IoT devices with 5G New Radio (NR)
• Interface protocols: N1, N2, N3, N4, N6 for IoT services
• Interworking with legacy IoT platforms (2G, 3G, 4G)
• Cloud-native architecture and microservices for IoT​

Module 3: Massive IoT Technologies: NB-IoT and LTE-M

• NB-IoT (Narrowband IoT) architecture and deployment modes
• LTE-M (LTE Cat-M1) technology fundamentals
• Coverage enhancement techniques (CE Mode A and B)
• Power consumption optimization: Power Saving Mode (PSM) and extended Discontinuous Reception (eDRX)
• Half-duplex and full-duplex operation modes
• Link budget analysis and spectrum efficiency
• Device complexity reduction and battery life optimization
• Deployment strategies: standalone, guard-band, and in-band modes
• Migration path from LTE-M/NB-IoT to 5G IoT​

Module 4: 5G Network Slicing for IoT

• Network slicing principles and architecture
• Slice types: eMBB, URLLC, mMTC, and custom vertical slices
• Network Slice Selection Function (NSSF) and slice management
• Dynamic resource allocation and orchestration
• End-to-end slice lifecycle management
• Quality of Service (QoS) and Service Level Agreements (SLA) per slice
• Network Slice Specific Authentication and Authorization Function (NSSAAF)
• Use cases: smart factories, autonomous vehicles, healthcare, smart cities
• Static vs. dynamic slicing strategies​

Module 5: Multi-Access Edge Computing (MEC) and 5G

• Edge computing fundamentals and architecture
• ETSI MEC framework and reference architecture
• MEC integration with 5G Service-Based Architecture
• Edge application functions and deployment scenarios
• Local Data Network (LDN) and Application Function (AF) traffic routing
• Uplink classifiers, branching points, and Session and Service Continuity (SSC)
• Latency reduction through edge processing
• Edge computing for industrial IoT and real-time applications
• MEC orchestration and lifecycle management​

Module 6: Private 5G Networks for Enterprise IoT

• Private 5G network architecture and deployment models
• Standalone (SA) vs. Non-Standalone (NSA) private networks
• Spectrum options: licensed, shared, and unlicensed bands
• Integration with enterprise IT and OT infrastructure
• Network design for Industry 4.0 applications
• Private network security and isolation
• Campus networks, smart factories, and logistics use cases
• Business models and ROI analysis for private 5G
• Vendor ecosystem and equipment considerations​

Module 7: IoT Radio Access Technologies in 5G

• 5G New Radio (NR) for IoT applications
• Frequency bands: FR1 (sub-6 GHz) and FR2 (mmWave) for IoT
• Massive MIMO and beamforming for IoT connectivity
• RedCap (Reduced Capability) IoT devices in 5G
• eRedCap and further IoT optimizations
• Non-Terrestrial Networks (NTN) for IoT: satellite and UAV connectivity
• Coverage, capacity, and spectrum efficiency for IoT
• Radio resource management and scheduling​

Module 8: 5G IoT Deployment and Use Cases

• Industrial automation and Industry 4.0 applications
• Smart cities: infrastructure, transportation, and utilities
• Intelligent healthcare and remote patient monitoring
• Smart agriculture and environmental monitoring
• Connected and autonomous vehicles (V2X)
• Smart grids and energy management
• Retail, logistics, and asset tracking
• Smart buildings and intelligent venue management
• Deployment scenarios: urban macro, indoor hotspot, rural coverage​

Module 9: Security and Privacy in 5G IoT

• 5G security architecture for IoT
• Authentication and authorization mechanisms
• End-to-end encryption and integrity protection
• Network Slice Specific Authentication and Authorization
• IoT device security and lifecycle management
• Privacy protection and data governance
• Threat modeling and security risk assessment
• Regulatory compliance: GDPR, IoT security standards
• Zero-trust security frameworks for IoT​

Module 10: Quality of Service (QoS) and Performance Optimization

• 5G QoS model and traffic handling
• QoS Flow Identifiers (QFI) and 5QI parameters
• Priority handling and policy control for IoT
• Latency, throughput, and reliability requirements
• Traffic steering and application function influence
• KPI monitoring and performance analytics
• Network optimization techniques for IoT traffic
• Service Capability Exposure Function (SCEF) for IoT​

Module 11: Artificial Intelligence and Machine Learning in 5G IoT

• AI/ML use cases in 5G-IoT convergence
• Network optimization using machine learning algorithms
• Predictive maintenance and anomaly detection
• Intelligent traffic management and resource allocation
• AI-driven network slicing and orchestration
• Edge AI for real-time IoT data processing
• ML for massive MIMO optimization and beamforming
• Autonomous network management and self-organizing networks (SON)
• AI-as-a-Service for IoT applications​

Module 12: Spectrum Management and Regulatory Aspects

• 5G spectrum allocation for IoT applications
• Licensed, unlicensed, and shared spectrum models
• ITU-R and 3GPP frequency band designations
• Spectrum efficiency and coexistence strategies
• Regulatory frameworks and regional variations
• Interference management and dynamic spectrum access
• Global harmonization and cross-border IoT connectivity
• Future spectrum planning for 6G and beyond​

Module 13: Advanced 5G IoT Technologies and Future Trends

• 5G-Advanced (Release 18) IoT enhancements
• RedCap evolution and new IoT device categories
• Integrated Access and Backhaul (IAB) for IoT
• Satellite-based 5G IoT and Non-Terrestrial Networks
• Extended Reality (XR) and immersive IoT applications
• Digital twins and cyber-physical systems
• Energy-efficient IoT: green 5G and sustainability
• Convergence with blockchain for secure IoT transactions
• 6G vision and IoT roadmap

Training Impact

The impact of 5G and IoT Application Training is evident across diverse industrial contexts:

Bosch (UK) – Private 5G Manufacturing Excellence

Implementation: Bosch deployed the UK’s first private 5G network at its Worcester facility in collaboration with Ericsson and British Telecom, creating a live testbed for Industry 4.0 automation. The systematic approach involved implementation of ultra-reliable network slicing and MEC integration for real-time coordination between industrial robots, assembly lines, and quality assurance systems.

Results: The 5G infrastructure enabled real-time analysis of production data, boosting efficiency and safety while reducing operational downtime by 15%. The comprehensive implementation resulted in agile production control and dynamic supply chain management with latency below 10 ms, demonstrating how private 5G enables advanced manufacturing while building sustainable frameworks for ongoing industrial transformation and operational excellence.

Shanxi Coking Coal Group (China) – Smart Mining Excellence

Implementation: Shanxi Coking Coal Group built one of the world’s first 5G-enabled open-pit mines in partnership with Huawei and China Unicom, deploying over 50 real-time HD cameras and IoT sensors. The systematic approach leveraged edge computing for real-time remote control operations using autonomous mining trucks and predictive maintenance systems.

Results: The network achieved 25% improvement in cost efficiency and 10% reduction in energy consumption, demonstrating the performance advantage of ultra-reliable IoT on private 5G. The structured implementation resulted in enhanced employee safety, increased profitability, and demonstrated how 5G and edge computing can transform hazardous industrial environments while building sustainable frameworks for ongoing operational efficiency and worker protection.

Global Telecom Operators – AI-Based Optimization Excellence

Implementation: Global telecom leaders, including Vodafone, SK Telecom, and NTT, implemented AI and ML-driven solutions for 5G IoT optimization, using algorithms for network slicing orchestration and real-time resource routing. The systematic approach involved AI-centric automation frameworks that dynamically reroute IoT device traffic based on predictive analysis.

Results: The implementations reduced latency by 30% and improved service predictability for massive IoT devices, with Vodafone UK’s IoT Connect managing 140 million devices effectively. The comprehensive approach demonstrated how intelligent orchestration transforms high-load network performance while building sustainable frameworks for ongoing network autonomy and operational cost savings.

Be inspired by Bosch, Shanxi Coking, and global telecom excellence. Secure your spot in the Rcademy 5G and IoT Application Training Course and unlock your digital transformation leadership potential today.