Machine learning in data science
Advanced training that combines machine learning theory with practical aspects of data science. The program guides participants through the full cycle of an analytics project, from understanding the business problem, to data preparation, to implementation and monitoring of ML models. Classes are delivered in the form of hands-on workshops, where each theoretical issue is immediately verified by working on real data sets and implementing solutions in a production environment.
Issues
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Methodologies for running DS projects
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Advanced data preprocessing
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Feature engineering
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Model selection
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Hyperparameter optimization
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Cross-validation
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Model deployment
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Monitoring of ML models
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Version control in DS
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Pipeline automation
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Interpretability model
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Performance metrics
Benefits
- Upon completion of the training, the participant will be able to independently conduct projects combining data science and machine learning
- In-depth knowledge of data preparation and feature engineering for different types of ML models
- He will develop the ability to select and optimize machine learning algorithms for specific business problems
- Will learn to design and implement scalable ML solutions in a production environment
- Will be able to effectively monitor and maintain implemented models
- Will gain practical experience in interpreting and presenting analysis results to business stakeholders
Who is this training for?
Prerequisites
- Knowledge of the basics of statistics and probability
- Experience in Python programming
- Basic knowledge of data analysis
- Knowledge of the basics of machine learning
Training program
Defining business problems
- Planning the analytical process
- Methodologies for running DS projects
- Measuring the success of ML projects
- Preparation and data mining
Advanced preprocessing techniques
- Feature engineering for ML models
- Exploratory data analysis
- Data quality validation
- Modeling and evaluation
Selection of algorithms for problems
- Hyperparameter tuning
- Model validation techniques
- Interpretation of results
Implementation and maintenance
- Pipeline ML in production
- Monitoring model performance
- Model version management
- Upgrading and retraining
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 Machine learning in data science training for?
This training is designed for professionals looking to develop skills in machine learning in data science. Required level: advanced.
How long is the Machine learning in data science training?
The training lasts 3. 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
Funding Options
Check funding options for your company
Development Services Database
Up to 80% funding for SMEs from EU funds
Check availabilityNational Training Fund
Up to 100% funding for employers
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We train teams at Poland's largest companies
Interested in this training?
Contact us - we'll prepare an offer tailored to your organization's needs.