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Course Outline
Advanced Neural Networks
- Deep learning architectures
- Convolutional and recurrent neural networks
- Generative models and unsupervised learning
Machine Learning at Scale
- Big data analytics
- Distributed computing for ML
- Advanced optimization techniques
Reinforcement Learning and Decision Making
- Markov decision processes
- Policy gradient methods
- Multi-agent systems and game theory
Natural Language Processing and Understanding
- Advanced NLP techniques
- Sentiment analysis and text classification
- Language models and transformers
Computer Vision and Perception
- Image recognition and object detection
- Video analysis and action recognition
- 3D reconstruction and augmented reality
AI Ethics and Society
- Bias and fairness in AI systems
- AI governance and policy
- Future societal impacts of AI
Lab Project
- Implementing advanced ML models
- Analyzing large datasets
- Collaborating on a group research project
Summary and Next Steps
Requirements
- A solid understanding of basic AI and ML concepts
- Proficiency in Python and familiarity with data science toolkits
- Completion of an introductory course in AI or equivalent experience
Audience
- Data scientists
- Engineers
- AI practitioners
21 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 €6840 online delivery, based on a group of 2 delegates, €2160 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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