دوره آموزشی: AI in telecom

دوره آموزشی: AI in telecom (کاربردهای هوش‌مصنوعی در تلکام)

ساعت آموزشی مورد نیاز: 40 ساعت

مدرس: دکتر وحید محمد زاده

مخاطبین: کارشناسان فنی و مدیران عملیاتی حوزه تلکام

هدف برگزاری: توانمندسازی متخصصان برای استفاده از هوش‌مصنوعی در جهت بهبود خدمات، افزایش بهره‌وری و ایجاد نوآوری در صنعت تلکام از اهداف این دوره است.

پیش‌نیاز: آشنایی با زبان برنامه نویسی Python

سرفصل‌:

1. Customer Service Automation
   • Chatbots for customer queries
   • Voice assistants for call centers
   • Text analysis for sentiment analysis
2. Network Optimization
   • Predictive maintenance of infrastructure
   • Dynamic capacity management
   • Traffic analysis and optimization using AI algorithms
3. Fraud Detection
   • Anomaly detection for unusual patterns
   • Real-time fraud prevention systems
   • Analysis of call patterns for fraudulent behavior
4. Churn Prediction and Management
   • Predictive analytics to identify at-risk customers
   • Recommendation systems for retention strategies
   • Customer segmentation using machine learning
5. Quality Assurance and Management
   • AI-based monitoring of network performance
   • Automated quality testing of calls and connectivity
   • Real-time data analytics for improved service quality
6. Smart Billing Systems
   • AI for personalized pricing models
   • Analysis of billing patterns to avoid errors
   • Automated dispute resolution through AI systems
7. Supply Chain and Inventory Management
   • Demand forecasting using AI algorithms
   • Predictive analytics for stock management
   • Optimization of logistics and delivery plans
8. Market Analysis and Business Intelligence
   • Customer behavior analysis for better decision-making
   • Predictive analytics for new service offerings
   • Social media analysis for brand monitoring
9. Enhanced 5G Deployment
   • AI-driven management of 5G resources
   • Network slicing using AI algorithms
   • Smart antennas and their configurations
10. Data Management and Security
    • AI for data encryption and security monitoring
    • Fraud detection with machine learning in user data
    • Privacy compliance monitoring using AI systems