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Course Outline
Introduction to Qwen for NLP
- Overview of Qwen's architecture and capabilities
- Setting up the environment and accessing Qwen API
- Key features and NLP-focused functionalities
Advanced Text Processing with Qwen
- Text generation and language modeling
- Sentiment analysis and emotion detection
- Summarization and paraphrasing
- Entity recognition and text classification
Integrating Qwen into NLP Workflows
- APIs and libraries for seamless integration
- Building pipelines for text preprocessing and analysis
- Deploying Qwen models in production environments
Customization and Fine-Tuning
- Adapting Qwen to specific NLP tasks
- Training custom models with domain-specific data
- Techniques for improving model performance
Evaluation and Performance Optimization
- Metrics for assessing NLP model quality
- Evaluating Qwen’s output and error analysis
- Optimizing computational efficiency
Case Studies and Best Practices
- Applications of Qwen in industry-specific NLP tasks
- Best practices for large-scale deployment
- Addressing challenges and limitations of Qwen
Summary and Next Steps
Requirements
- Advanced knowledge of natural language processing (NLP)
- Experience with AI model development
- Proficiency in Python programming
Audience
- NLP specialists
- Data scientists
- AI researchers
14 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €4560 online delivery, based on a group of 2 delegates, €1440 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
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