We realise that, due to the COVID-19 virus outbreak, making travel arrangements during this time is difficult. Therefore, registration for this course is open, but it does not require payment at this moment. We will only receive payments once the outbreak has calmed down and travel restrictions have been lifted.
The field of biological sciences is becoming increasingly information-intensive and data-rich. For example, the growing availability of DNA sequence data or clinical measurements from humans promises a better understanding of the important questions in biology. However, the complexity and high-dimensionality of these biological data make it difficult to pull out mechanisms from the data. Machine Learning techniques promise to be useful tools for resolving such questions in biology because they provide a mathematical framework to analyze complex and vast biological data. In turn, the unique computational and mathematical challenges posed by biological data may ultimately advance the field of machine learning as well.
This course will cover basics of the Python programming language as well as the pandas and sklearn Python libraries for data wrangling and machine learning.
By the end of this course, participants will understand:
- How to input and clean data in Python using the pandas library
- How to perform exploratory data analysis in Python
- How to use the sklearn library in Python for machine learning workflows
- How to choose an appropriate machine learning model for the task
- How to use supervised machine learning models (SVM, Decision Trees, Neural Networks, etc.) for classification tasks
- How to use unsupervised machine learning models for clustering tasks
- How to evaluate machine learning models and interpret their results
This course is intended to give participants a conceptual overview of machine learning algorithms and an intuition for the mathematics underlying them, equipping participants to be able to choose and implement appropriate models for biological datasets.
Monday to Friday:
- 9:30 to 13:30 Lessons.
- 13:30 to 15:00 Lunch (included).
- 15:00 to 18:00 Lessons.
The schedule is approximate; it is possible that the content of one day may run into the next and a working day may be longer than advertised.
Accommodation Package Schedule
- 18:30 Meeting at Heraklion Archaeological Museum to take the bus to Gerakári.
- 20:15 Check-in at Alexander Hotel.
- 20:45 Dinner.
Monday to Thursday:
- 8:30 to 9:00 Breakfast.
- 20:30 Dinner.
- 8:30 to 9:00 Breakfast.
- 18:30 Meeting at Alexander Hotel to take the bus to Heraklion or Chania.
- 20:15 Arrival at Heraklion Archaeological Museum
Former participants will have a 5 % discount on the Course Fee.
Furthermore, a 20 % discount on the Course Fee is offered for members of some organizations (Organizations with discount). If you want to apply to this discount please indicate it in the Registration form (proof will be asked later).
Unemployed scientists living in Greece, as well as PhD students based in Greece without any grant or scholarship to develop their PhD, could benefit from a 40 % discount on the Course Fee. If you want to ask for this discount, please contact the course coordinator. That would apply for a maximum of 2 places and they will be covered by strict inscription order.
Discounts are not cumulative and apply only on the fee, not to Accommodation Package or other options.