To provide the knowledge and skills required to understand and support decision making related to Machine Learning and Deep Learning projects.
Account or project managers, directors, stakeholders, IT managers, analysts, CFOs and accountants.
- Introduction to Artificial Intelligence and its role in modern IT
- Fundamentals: neural networks, examples of convolutional and recurrent networks
- Machine learning: the principles of learning and key concepts—data, learning concepts, predictions on new data
- Data to rely on: internal company data, data acquired externally
- Supervised, unsupervised, adaptive and reinforcement training
- Linear models of learning: regression, logistic, predictive (Bayesien, decision trees…)
- Tools for implementation: API, languages, local and Cloud platforms
- Examples of how machine learning is used: decisions, image recognition, natural language processing
- The special case of deep learning, algorithms and API, applications
- Implementing a learning project or deep learning project, required skills, industries