Azure Cognitive Services
Introduction to Azure Cognitive Services
- Overview of Azure Cognitive Services: Capabilities and use cases
- Key Concepts: AI, machine learning, and cognitive APIs
- Azure Cognitive Services Pricing and Plans
Setting Up Azure Cognitive Services
- Creating an Azure Cognitive Services Resource
- Configuring APIs and Keys
- Managing Cognitive Services in the Azure Portal
Vision Services
- Computer Vision: Analyzing images and extracting information
- Face API: Detecting and recognizing faces in images
- Custom Vision: Training and deploying custom image classifiers
Speech Services
- Speech-to-Text: Converting audio to text
- Text-to-Speech: Generating spoken audio from text
- Speech Translation: Translating spoken language in real-time
Language Services
- Text Analytics: Analyzing text for sentiment, entities, and key phrases
- Translator: Translating text between multiple languages
- Language Understanding (LUIS): Building natural language understanding models
Search Services
- Bing Search APIs: Implementing web search, image search, and news search
- Custom Search: Creating tailored search experiences
- Bing Entity Search: Extracting information about entities from the web
Decision Services
- Personalizer: Providing personalized content and experiences
- Anomaly Detector: Detecting anomalies in time-series data
- Metrics Advisor: Monitoring and diagnosing metrics for business insights
Security and Compliance
- Securing Cognitive Services: API keys and access control
- Data Privacy and Compliance: GDPR, HIPAA, and other regulations
- Implementing Security Best Practices: Protecting data and managing permissions
Monitoring and Diagnostics
- Monitoring Usage: Metrics, logs, and alerts
- Diagnosing Issues: Troubleshooting and resolving errors
- Using Azure Monitor and Application Insights with Cognitive Services
Integration and Customization
- Integrating Cognitive Services with Other Azure Services: Logic Apps, Functions, and more
- Customizing Models: Training custom models and deploying solutions
- Building Custom Applications: Using Cognitive Services APIs in applications
Cost Management and Optimization
- Managing Costs: Understanding pricing models and usage
- Cost Optimization Best Practices: Reducing costs while maintaining performance
- Using Azure Cost Management Tools: Cost analysis and budgeting
Disaster Recovery and Business Continuity
- Implementing Backup Strategies: Data backup and recovery
- Ensuring High Availability: Designing for fault tolerance
- Planning for Disaster Recovery: Strategies for continuity and failover
Real-World Projects and Case Studies
- Implementing Cognitive Solutions: Case studies and success stories
- Best Practices and Lessons Learned: Insights from real-world implementations
Career Development and Azure Certifications
- Azure Certifications Overview: Paths and preparation tips for Cognitive Services and related certifications
- Building a Career with Azure Cognitive Services: Skills development and career opportunities
- Interview Preparation: Common interview questions and scenarios related to cognitive services
Azure Cognitive Services Syllabus
1. Introduction to Azure Cognitive Services
- Overview of Azure Cognitive Services
- Key features and benefits
- Cognitive Services APIs overview
2. Vision APIs
- Computer Vision API
- Image analysis and tagging
- Object detection and recognition
- Optical character recognition (OCR)
- Face API
- Face detection and identification
- Emotion detection
- Face verification
3. Speech APIs
- Speech to Text API
- Speech recognition
- Transcription of spoken language
- Text to Speech API
- Speech synthesis
- Convert text into spoken language
4. Language APIs
- Text Analytics API
- Sentiment analysis
- Key phrase extraction
- Language detection
- Translator Text API
- Language translation
- Text transliteration
5. Decision APIs
- Content Moderator API
- Text moderation
- Image moderation
- Personalizer API
- Personalized recommendations
- Content customization
- QnA Maker API
- Build and deploy Q&A bots
- Natural language understanding
6. Integration and Deployment
- Integrating Azure Cognitive Services into applications
- Deployment considerations and best practices
- Monitoring and troubleshooting Cognitive Services
7. Advanced Topics
- Customizing and training models
- Cognitive Services Containers
- Ethical considerations and privacy concerns
8. Custom Vision Service
- Creating and training custom image classification models
- Object detection and image segmentation using Custom Vision
- Integration with Azure IoT Edge for edge deployment
9. Speech Translation and Speech Synthesis Customization
- Customizing Neural Text to Speech (TTS) models
- Advanced techniques in speech synthesis and voice cloning
- Multi-language and dialect support in Translator Text API
10. Natural Language Processing (NLP) Enhancements
- Entity recognition and linking with Named Entity Recognition (NER) APIs
- Advanced sentiment analysis techniques
- Fine-tuning language models with Text Analytics API
11. Deep Learning with Azure Cognitive Services
- Using Azure Machine Learning to train and deploy custom models
- Transfer learning with pretrained models in Vision and Language APIs
- Implementing neural network architectures for specific use cases
12. Cognitive Services Integration Patterns
- Building complex workflows using multiple Cognitive Services APIs
- Implementing real-time analytics pipelines with Cognitive Services
- Integration with Azure Functions and Logic Apps for event-driven scenarios
13. Cognitive Services Security and Compliance
- Data privacy considerations with Cognitive Services
- Implementing encryption and access controls
- Compliance with GDPR and other regulatory frameworks
14. Performance Optimization and Scalability
- Techniques for optimizing Cognitive Services for speed and efficiency
- Scaling Cognitive Services for high availability and global deployments
- Monitoring and performance tuning strategies
15. Ethical AI and Bias Mitigation
- Understanding ethical considerations in AI and Cognitive Services
- Bias detection and mitigation techniques in model training
Training
Basic Level Training
Duration : 1 Month
Advanced Level Training
Duration : 1 Month
Project Level Training
Duration : 1 Month
Total Training Period
Duration : 3 Months
Course Mode :
Available Online / Offline
Course Fees :
Please contact the office for details