Introduction to Machine Learning & AI for Managers and Architects
Seminar Categories:BI & ML
Machine Learning and AI suggest a set of algorithms and supporting technologies, which allow companies to automatically extract knowledge and make decision using the data they collect. Mastering these algorithms and technologies enables new business opportunities and competitive advantages. This seminar is planned to provide a broad introduction to the field, presenting the typical steps of Machine Learning and AI projects, common algorithmic methods and relevant technologies.
The seminar is suitable to BI and data architects, who need a gentle, yet through introduction to the field.
Who Should Attend
- BI & analysts
Which considering in implementing ML and move to Data Science
- Some orientation with data and data analysis
- Introduction to Artificial Intelligence (AI) and Machine Learning (ML)
- What is it?
- Basic terms
- Business motivation
- Challenges in ML
- Fields where ML is used
- Examples for ML use in organizations today
- CRISP-DM: the typical steps of Machine Learning / AI projects
- Data gathering, understanding and preparations
- Learning Algorithms:
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Evaluating ML models
- Neural Networks and Deep learning
- Concept and building blocks
- Behind the scenes of a Neural Network
- Common types of neural networks
- Convolutional Neural Networks and Computer Vision
- Tools and technologies
- Leading tools and libraries
- ML as a service
- Where to go next?
- Road to data science
- Getting your feet wet