Neural computing in Data Science
The training focuses on the practical application of neural computing in the context of data analysis and data science. The program combines the theoretical foundations of neural networks with their practical use in real analytical projects. Participants, through workshops, learn methods of implementation and optimization of neural models in analytical tasks. The classes are conducted in the form of interactive workshops, where theory is immediately translated into practical implementations using real data sets.
Issues
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Network architectures in data analysis
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Preparation of data for modeling
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Time series analysis
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Dimensionality reduction
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Anomaly detection
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Validation of models
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Interpretation of results
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Analytical pipelines
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Process automation
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Performance monitoring
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Update models
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Optimizing solutions
Benefits
- Upon completion of the training, the participant will be able to effectively use neural computing in data science projects
- The ability to select appropriate network architectures for specific analytical tasks
- Will be able to prepare and process data for neural modeling
- Will master model optimization and validation techniques in the context of data analysis
- Will learn to interpret results and assess the quality of neural models
- Will gain practical experience in implementing neural networks in analytical pipelines
- Will learn methods for automating learning and inference processes
- Will be able to monitor and update models in a production environment
Who is this training for?
Prerequisites
- Basic knowledge of data analysis methods
- Experience in analytical programming
- Understand the basics of statistics
- Knowledge of the basics of machine learning
Training program
Network architectures in the context of data analysis
- Preparation of data for modeling
- Choosing the right architecture
- Techniques for training models
- Implementation in analytical projects
- Structured data processing
Time series analysis
- Dimensionality reduction
Anomaly detection
- Optimization and validation
- Model validation techniques
Hyperparameter tuning
- Interpretation of results
- Quality assessment of models
- Implementation in an analytical environment
- Integration with data science pipelines
Process automation
- Performance monitoring
- Update models
Delivery Methods
Online
- Convenience of participating from anywhere
- Interactive live sessions with trainer
- Materials available for 30 days
- No travel costs
On-site
- Direct contact with trainer and group
- Intensive hands-on workshops
- Networking with other participants
- Full focus on learning
Frequently asked questions
Who is the Neural computing in Data Science training for?
This training is designed for professionals looking to develop skills in neural computing in data science. Required level: intermediate.
How long is the Neural computing in Data Science training?
The training lasts 2. Available in online or on-site format.
Will I receive a certificate?
Yes — every participant receives a completion certificate confirming acquired competencies. EITT holds ISO 9001 accreditation.
Can this training be conducted for a closed group?
Yes — we offer dedicated closed trainings for companies. We customize the program to your team's needs. Contact us for an individual quote.
Request a quote
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