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AI+ Telecommunications Practitioner (AT-2501)

Telecommunications networks must handle growing data volumes, connected devices, security threats, and rising customer expectations.

AI helps providers monitor performance, predict faults, protect infrastructure, and improve service delivery. This course develops practical skills for applying AI across 5G, network operations, customer service, security, data engineering, and modern connected telecommunications systems.

Overview

Overview

Telecommunications teams manage complex networks, large data flows, service interruptions, cyber risks, and millions of connected devices. AI can help them identify problems earlier, allocate resources, automate monitoring, and respond to customers more effectively.

This course covers telecom data engineering, 5G, network optimisation, security, customer experience, connected devices, automated operations centres, and responsible AI. Practical activities help you apply these concepts to common telecommunications challenges using data, systems, and tools.

Prerequisites
  • Basic understanding of telecommunications concepts and technologies

  • Familiarity with networks, 5G, and connected devices

  • Knowledge of programming, preferably Python

  • Basic understanding of data analysis

  • Prior AI experience is helpful but not required

Target Audience
  • Telecommunications engineers working with network automation and performance

  • AI and data professionals applying analytics within telecommunications

  • Network administrators and architects managing monitoring and resources

  • IT and software developers creating AI-based telecommunications applications

  • Business analysts and product managers improving services and customer engagement

  • Students and graduates from computer science, electronics, or telecommunications

  • Consultants and technology entrepreneurs developing telecommunications solutions

Exam Blueprint
  • Introduction to AI in Telecommunications – 6%
  • Data Engineering for Telecom AI – 10%
  • AI for 5G Networks – 10%
  • AI in Network Optimisation – 10%
  • AI for Network Security – 10%
  • Enhancing Customer Experience with AI – 11%
  • IoT Integration with Telecommunications – 11%
  • AI-Integrated Network Operations Centres – 11%
  • Ethical Considerations in Artificial Intelligence – 11%
  • Capstone Project – 10%
FAQs

1. Can the course be taken online?
Yes, the course is available through live virtual instructor-led training or a self-paced online learning option.

2. Is previous AI experience required?
No, previous AI experience is helpful but not required. Participants should understand telecommunications, programming, and basic data analysis.

3. Is in-person training available?
Yes, classroom training is available through AI CERTs Authorized Training Partners.

Course Outline

Module 1: Introduction to AI in Telecommunications
  1. AI Fundamentals in Telecommunications
  2. AI in Network Management
  3. AI in Customer Service
  4. AI for Operational Efficiency
  5. Machine Learning
  6. Customer Behaviour Prediction
  7. Natural Language Processing
  8. Automated Customer Interactions
  9. Computer Vision
  10. Infrastructure Management
  11. AI-Based Decision-Making
  12. Connected Device Integration
  13. Deep Learning
  14. Edge Computing
  15. Case Study
  16. Hands-On Project

 

Module 2: Data Engineering for Telecom AI
  1. Telecom Data Engineering
  2. Telecom Data Pipelines
  3. Call Detail Records
  4. Network Performance Data
  5. Customer Usage Data
  6. Structured Data
  7. Unstructured Data
  8. SQL Databases
  9. NoSQL Databases
  10. Apache Spark
  11. TensorFlow
  12. Data Processing
  13. Network Slicing
  14. Edge Computing
  15. Self-Optimising Networks
  16. Performance Dashboards
  17. Case Study
  18. Hands-On Activity

 

Module 3: AI for 5G Networks
  1. Introduction to 5G
  2. High-Speed Data Transfer
  3. Low-Latency Connections
  4. Connected Device Support
  5. AI Applications in 5G
  6. Spectrum Allocation
  7. Beamforming
  8. Network Traffic Prediction
  9. Network Performance Improvement
  10. Self-Organising Networks
  11. Network Fault Detection
  12. Automated Network Management
  13. Downtime Reduction
  14. Operational Cost Reduction
  15. Case Study
  16. Hands-On Activity

 

Module 4: AI in Network Optimisation
  1. Predictive Network Management
  2. Real-Time Network Data
  3. Historical Network Patterns
  4. Early Fault Detection
  5. Network Performance Improvement
  6. Traffic Management
  7. Network Anomaly Detection
  8. Reinforcement Learning
  9. Bandwidth Allocation
  10. Latency Reduction
  11. Service Quality Management
  12. High-Demand Network Support
  13. Case Study
  14. Hands-On Activity

 

Module 5: AI for Network Security
  1. Security Threats in Telecommunications
  2. Distributed Denial-of-Service Attacks
  3. SIM Card Fraud
  4. Call Spoofing
  5. Insider Threats
  6. Real-Time Threat Detection
  7. Network Anomaly Detection
  8. Phishing Prevention
  9. Threat Intelligence
  10. Behaviour Analysis
  11. Automated Incident Response
  12. Security Information and Event Management
  13. Zero Trust Security
  14. Continuous Authentication
  15. Case Study
  16. Hands-On Activity

 

Module 6: Enhancing Customer Experience with AI
  1. Personalised Customer Service
  2. AI Chatbots
  3. Virtual Assistants
  4. Round-the-Clock Customer Support
  5. Understanding Customer Requests
  6. Service Quality Improvement
  7. Real-Time Service Data
  8. Predicting Service Issues
  9. Customer Segmentation
  10. Personalised Offers
  11. Customer Engagement
  12. Customer Retention
  13. Case Study
  14. Hands-On Activity

 

Module 7: IoT Integration with Telecommunications
  1. Connected Device Fundamentals
  2. Smart Homes
  3. Connected Vehicles
  4. Remote Health Monitoring
  5. Real-Time Communication
  6. Device Data Transfer
  7. Connected Device Security
  8. Network Anomaly Detection
  9. Real-Time Threat Detection
  10. Network Monitoring
  11. Network Fault Detection
  12. Operational Efficiency
  13. Case Study
  14. Hands-On Activity

 

Module 8: AI-Integrated Network Operations Centres
  1. Traditional Network Operations Centres
  2. AI-Based Operations Centres
  3. Machine Learning in Network Operations
  4. Automated Network Monitoring
  5. Predicting Network Issues
  6. Automated Fault Detection
  7. Network Anomaly Detection
  8. Root Cause Analysis
  9. Faster Incident Resolution
  10. Software-Defined Networking
  11. Closed-Loop Automation
  12. AI-Ready Network Design
  13. AI Rollout Planning
  14. Change Management
  15. Case Study

 

Module 9: Ethical Considerations in Artificial Intelligence
  1. Ethical AI in Telecommunications
  2. Customer Data Privacy
  3. Fair AI Decisions
  4. Biased Algorithms
  5. Discriminatory Practices
  6. Responsible AI Deployment
  7. Transparent AI Decisions
  8. Customer Consent
  9. Explainable AI
  10. Human Review of AI Decisions
  11. AI Governance Boards
  12. Data Protection Requirements
  13. General Data Protection Regulation
  14. Case Study
  15. Hands-On Activity

 

Module 10: Capstone Project
  1. Select a Telecommunications Challenge
  2. Define the Project Requirements
  3. Identify Relevant Network Data
  4. Choose a Suitable AI Approach
  5. Design the Proposed Solution
  6. Develop the Project
  7. Test the Solution
  8. Assess Network Performance
  9. Review Security and Ethical Risks
  10. Document the Project
  11. Present the Final Solution
Note : A representative from Datacipher will contact you with further details
Payment Methods

At DataCipher, we offer a variety of payment options for our Fortinet courses. Here are the methods available:

Purchase Order (PO) – If your organization prefers using a purchase order, begin the registration process by clicking the Register button. At the conclusion of the registration form, choose the option “My company will pay for it, please send an invoice with the payment details.” Our training team will then provide an official quote and any necessary additional information that your accounts department might need to issue the PO.

Bank Transfer – DataCipher maintains bank accounts in both the US and Europe, accommodating all standard bank transfer methods such as IBAN/BIC, Swift, ACH, or wire transfer. To make a payment via bank transfer, simply use the Register button to sign up for your selected course.

Credit Card Payments – We accept payments from all major credit cards, including Mastercard, VISA, American Express, Discover & Diners, and Cartes Bancaires. Payments can be made directly through the registration link or by requesting an invoice that includes a web link for online payment. All transactions are secure, and DataCipher does not store any credit card information.

These options are designed to make the registration process as smooth and flexible as possible for all participants.

Status

Guaranteed to Run – DataCipher is committed to running this class unless unforeseen events such as an instructor’s accident or illness occur.

Guaranteed on Next Booking – The course will proceed once an additional student registers.

Scheduled Class – We have scheduled this course and rarely cancel due to low enrollment. We offer a “Cancel No More Than Once” guarantee, ensuring that if a class is canceled due to insufficient enrollment, the next session will run regardless of the number of attendees.

Sold Out – If the class is fully booked, please use our contact form to join the waiting list or to inquire about additional sessions. We’re here to accommodate your training needs and keep you informed of new opportunities.

Half and Full-Day Training

At DataCipher, we offer our training courses in both traditional full-day and convenient half-day formats. Our half-day classes are specifically designed for IT professionals who cannot be away from their workplaces for consecutive full days. This flexible schedule allows participants to dedicate a few hours to learning and then return to their regular work responsibilities.

The curriculum for both the full-day and half-day formats is identical. The primary difference is that the half-day classes spread the coursework over a more extended period, providing a balanced approach to professional education. DataCipher has been successfully running these half-day training sessions for several years, receiving consistently positive feedback from our customers. They appreciate the flexibility and report that the extended timeframe facilitates a deeper understanding of the material, as it gives them more time to absorb and reflect on the information learned.

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