Machine learning is as valuable as the problems it solves. Our aim with these courses is to provide the power of this tool to professionals dealing with important problems in healthcare, physics, and manufacturing. We offer a non-technical course for high-level understanding of this technology and a technical course for learning how to develop basic machine learning models on your own. These courses can be extended as consulting services and we can work on solving your challenges together.

Course 1
High-level understanding of machine learning (ML)
Prerequisites: None
Duration: Minimum 30 minutes - Maximum 2 hours

This course is aimed at people who would like to know what machine learning (ML) is and what its implications are for their domain. We explore the basic working principles of this technology, components of an ML project and possible challenges in implementing ML models. Finally there will be concrete ML application examples, tailored to your area of interest.

After this course, participants will be able to:

• ​Recognize projects where machine learning can be helpful.
• Evaluate proposals related to machine learning.
• ​Communicate with machine learning engineers.

Course 2
Hands-on machine learning
Prerequisites: Coding experience
Duration: Minimum 2 hours - Maximum 2 days

This course is aimed at people who are familiar with coding, preferably in Python. After an introduction to machine learning, structure of ML projects and possible challenges, we will dive into solving curated challenges using popular ML algorithms and ML libraries. Coding problems will be selected according to the participants' interest.

After this course, participants will be able to:

• Recognize how ML can solve their problems.
• Build simple ML models.
• Understand the basics of ML algorithms such as neural networks, random forests.
• Understand the basics of ML frameworks such as Keras, scikit learn.

Here are some example coding challenges from our previous trainings:
​https://github.com/MehmetAlicanNoyan

​