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Advanced Courses in Life Sciences

1st Edition

Python Machine Learning in Biology

December 3rd – 7th, 2018, Crete (Greece)

System Biology

Systems Biology Logo

Python Machine Learning in Biology

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.

LOCATION

Arolithos

Servili Tilissos
715 00 Heraklion, Crete (Greece)

DATE

December 3rd – 7th, 2018

LANGUAGE

English

COURSE LENGTH & ECTS

35 hours on-site.

This course is equivalent to 2 ECTS (European Credit Transfer System) at the Life Science Zurich Graduate School.

The recognition of ECTS by other institutions depends on each university or school.

PLACES

Places are limited to 14 participants and will be occupied by strict registration order.

Participants who have completed the course will receive a certificate at the end of it.

Instructor

Nichole Bennett instructor fro Transmitting Science

Nichole Bennett
The University of Texas at Austin
United States of America

Coordinator

Haris Saslis coordinator for Transmitting Science

Dr. Haris Saslis
Transmitting Science
Greece

Requirements

Graduate or postgraduate degree in Life Sciences and basic knowledge of Statistics. While some Python knowledge is useful, the course will cover basic Python skills necessary to input, clean, and explore data as well as build and evaluate machine learning models.

All participants must bring their own personal laptop (Windows, Macintosh, Linux).

Program

Monday, December 3rd, 2018.

Python Foundations

  • Morning: Python Basics, Handling Data in Pandas, Basic Pandas Data Cleaning
  • Afternoon: Exploratory Data Analysis in Pandas, Data Visualization in Python.

Tuesday, December 4th, 2018.

Supervised Machine Learning: Classification

  • Morning: KNN, Introduction to sklearn workflow.
  • Afternoon: Train/Test Split, and Bias-Variance Tradeoff, Model Evaluation.

Wednesday, December 5th, 2018.

Supervised Machine Learning: Classification

  • Morning: Decision Trees and Random Forest
  • Afternoon: Support Vector Machines

Thursday, December 6th, 2018.

Unsupervised Machine Learning

  • Morning: Clustering Methods (K Means Clustering)
  • Afternoon: Advanced Clustering Methods Hierarchical Clustering, DBSCAN

Friday, December 7th, 2018.

  • Special Topics
  • Participants will have the option to learn a particular model or receive an introduction to Neural Networks theory and applications.

Fees

  • Course Fee
  • {{content-1}}
  • Early bird (until September 30th, 2018):
  • 590
  • Regular (after September 30th, 2018):
  • 737
  • This includes course material, coffee breaks and lunches (VAT included).
  • Course Fee + Accommodation Package
  • {{content-1}}
  • Early bird (until September 30th, 2018):
  • 590 + 330 = 920
  • Regular (after September 30th, 2018):
  • 737 + 330 = 1067
  • This includes course material, coffee breaks, transportation from and to Heraklion, accommodation from Sunday to Friday, breakfasts, lunches and dinners (VAT included).

We offer the possibility of paying in two instalments (contact the course coordinator). Discounts (see Funding below) are not cumulative and apply only on the fee, not to Accommodation Package or other options.

Accommodation

If you take the Accommodation Package option you will be hosted in Arolithos (take a look at the venue), in shared en-suite twin or triple rooms, although you will only share rooms with other classmates. The possibility exists that rooms will be mixed. Therefore, if this is an inconvenience for you, and you require staying in a room with only women or only men, please indicate so in the “Comments” field of the Registration form (see below).

A supplemental charge will be added if you prefer to stay in a single room with private bathroom. The number of single rooms is limited and if you prefer to have one please let us know as soon as possible. If you require more information on accommodation issues please contact the course coordinator.

If you do not want the Accommodation Package, there are several accommodation options in Heraklion. However please be aware that it takes about 25 minutes by car from Heraklion to Arolithos and there is no public transport between both. Therefore course participants will find that staying in Arolithos is more convenient.

How to get to Arolithos from Heraklion, Chania or Rethimnon.

Arolithos street

Arolithos street (Heraklion, Crete, Greece)

Arolithos twin room

Arolithos twin room (Heraklion, Crete, Greece)

Arolithos twin room

Arolithos twin room (Heraklion, Crete, Greece)

Schedule

Course Schedule

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

Sunday:

  • 17:00 Registration at the hotel in central Heraklion.
  • 20:30 Dinner in Heraklion.

Monday:

  •  7:30 to 8:30 Breakfast and check-out.
  • 8:30 Transfer from central Heraklion to Arolithos, where the group will stay the rest of the week, and check-in.
  • 20:30 Dinner.

Tuesday to Thursday:

  • 8:30 to 9:00 Breakfast.
  • 20:30 Dinner.

Friday:

  • 8:30 to 9:00 Breakfast.
  • 19:00 Transfer from Arolithos to central Heraklion.
  • 19:45 Arrival in central Heraklion (Archaeological Museum).

Funding

Former participants will have a 5 % discount on the Course Fee.

Unfortunately there are no scholarships available for this course. However 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).

Greek unemployed scientists, as well as Greek PhD students 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.

Organizers

Transmitting Science Logo

Collaborators

Colegio Oficial de Biólogos de Castilla y León Logo
Colegio Oficial de Biólogos de Euskadi Logo
Colexio Oficial de Biólogos de Galicia Logo
Col·legi Oficial de Biòlegs de la Comunitat Valenciana Logo
European Association of Vertebrate Palaeontologists (EAVP) Logo
Sociedade Brasileira de Paleontologia (SBP) Logo

Registration