Machine Learning using Python

Location: Erasmus MC

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Machine learning using Python

The Python Course used to be a 4 days Basic and Advanced course
Now we turned it into a 3 days Basic Course (Separate registration) 
This course will be the 2 days Machine learning using Python.(Separate registration) 
Followed up by a 1 day ''Hackathon day'' (Separate registration) 
The Advanced Python Course will prepare you for a professional development in using Machine Learning and modelling in your data analysis challenges. We will cover advanced workflows and predictive models that can significantly expand your possibilities.
How can this course benefit your career?
-You will learn about predictive analytics and how to produce forecasts from datasets.
-You will see how to let the machine build statistical models by learning through data.
-You will learn how to select a neural network typology for your models.
-You will learn the distinction between models of supervised learning and unsupervised and when each applies.
-You will see applications of predictive modelling in your areas of interest.

Audience and participation
This course is meant for people who have taken the Basic Python Course, or have significant experience with the python language and the most commonly used libraries. We will start from the assumption that you have a working knowledge of Jupiter Notebooks..

Luis Rodil-Fernandez:
L. Gonzalez Leon, Erasmus MC:
D. van Zessen, Erasmus MC:

Date, Time & Location

Full participation is  0,8 ECTS.


Course fees 
For non-commercial participants the course fee  €350/2 days

PhD students get a 50% discount and pay €175/ 2 days. 
Participants from the postgraduate school MolMed get a 100% discount and pay €0.
Master students, get a 50% discount and pay €175/ 2 days. 
Master students who have to pay the fee from their personal budget get a 75% discount and pay €87,50/ 2 days. 
If these financial requirements should pose a problem, please contact Frank van Vliet, managing director of the Erasmus Postgraduate School Mol Med, at:

General information
Financial regulation of the Postgraduate School MolMed, from January 1st 2021, the following financial rules apply, but they may differ per course still. Look at the course fee of each course to be sure which discounts are really applied:
• Non-commercial course, symposium or workshop fee: €200/day, €750/week
• Participants of the postgraduate school MolMed: discount of 100%
• However, the Personal Leadership course and the workshops Photoshop/Illustrator/Indesign have to be paid from the ‘personal budget’ of employees, MolMed members and PhD students included. So they will receive an invoice from us which you have to pay and which will be reimbursed by your Department. When you will pay from your personal budget you need to provide us your home address details for the invoice. 
If there is no personal budget left, the MM-members get a discount of 100%.
• PhD students and Master’s students, regardless of institution: discount of 50%.
•The course fees of research master’s students will be paid by their master program at rate of €100/ECTS. For not I&I master students: please inform your master program in advance whether they agree to pay.
•Master’s students who are paying the fee from their private budget: discount of 75%. When you will pay from your personal budget you need to provide us your home address details for the invoice.
•However, 2 courses in statistics are paid centrally by the Dept. of Research policy for all PhD students from Erasmus MC! These are R and the SPSS course. So for Erasmus MC PhD students, these courses are always free, provided you are officially registered as a PhD student.
There is one fee for the entire course. There is no reduction for partial participation.
Commercial participants, companies & sponsors are invited to inquire about commercial tuition fees and about sponsoring.
All invoices will be sent by email to the mail address that you filled in upon registration. If this address is not correct we use your Erasmus MC address.

Those who register for a course, symposium or workshop agree with these financial conditions.


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