Python and Machine Learning
This online seminar is aimed at Science and Engineering graduates. Its duration is 8 months and consists of four units:
1. Python Programming
2. Python & Data
3. Supervised Learning
4. Unsupervised Learning
The flow of the educational process consists of asynchronous study spanning over two weeks approximately, followed by a three-hour remote synchronous workshop (via Zoom). The workshops have strong interaction with active participation of all trainees. The attendance of the trainees in the workshops is mandatory.
The first introductory meeting will be held on Tuesday, October 24 2023, at 7 pm.
At the end of each unit, a mandatory programming assignment will be submitted.
You can view the detailed scheduling of the seminar at this link
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Στοχοι Βιωσιμης Αναπτυξης
- 1 Περιγραφή
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The purpose of the program is to provide an educational introduction to Machine Learning, starting from the basic prerequisite knowledge. Machine Learning is a highly demanded skill in the job market. The main goal of the program is to equip the learner with a solid foundation and a strong toolset for their professional development. This foundation includes acquiring basic skills such as computer programming and data preprocessing. The tools used to build these skills are the Python programming language and its scientific libraries, namely Numpy, Maplotlib, SciPy, and Pandas. Additionally, a solid mathematical background is also essential as it forms the basis for all Machine Learning Algorithms.
In the second part of the program, the trainees become familiar with two fundamental axes of the field: Supervised Learning and Unsupervised Learning. In Supervised Learning, algorithms are “trained” using data (input) for which their corresponding mappings to other data (output) are known, with the aim of predicting the outcomes of new, unknown data.
In Unsupervised Learning, algorithms are not “trained” but rather attempt to discover patterns or structures in data that are not explicitly linked to any specific conclusion.
Target group
Graduates of Departments of Mathematics, Science or Engineering.
Discount policy
Categories Ποσοστό έκπτωσης 20% · Άνεργοι / Unemployed Yes · Νέοι ηλικίας έως και 30 ετών που είναι Κάτοχοι Ευρωπαϊκής Κάρτας Νέων / Young people up to 30 years old who are European Youth Card holders Yes · Προσωπικό που εργάζεται στα ΑΕΙ, ΑΤΕΙ και Ερευνητικά Κέντρα της ημεδαπής / Staff working at universities, universities of applied sciences and research centres in Greece Yes · Απόφοιτοι του ΠΚ / Graduates of UOC Yes · Μεταπτυχιακοί φοιτητές / Postgraduate students Yes · ΑμεΑ / disabled persons Yes · Γονείς μονογονεϊκών οικογενειών με ετήσιο εισόδημα κάτω από 15.000 ευρώ / Parents of single-parent families with an annual income of less than 15,000 euros Yes · Πολυτεκνία – Τριτεκνία (πολύτεκνος ή μέλος πολύτεκνης οικογένειας) / multiple parent or member of a large family Yes · Γονείς που έχουν ανήλικα τέκνα με ειδικές ανάγκες / Parents who have minor children with special needs Yes · Άτομα με ετήσιο εισόδημα κάτω από 12.000 ευρώ / People with an annual income of less than 12,000 euros Yes · Συμμετοχή στον ίδιο κύκλο σπουδών δύο ή περισσοτέρων ατόμων που συνδέονται με πρώτου και δεύτερου βαθμού συγγένεια. / Participation in the same course of study by two or more persons related by first and second degree of kinship. Yes · Εργαζόμενοι Πανεπιστημίου Κρήτης / Employees of the University of Crete Yes - 2 Περιεχόμενο
- 3 Επιστ. Υπεύθυνος
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Δ. Καλοψικάκης
- 4 Εκπαιδευτές
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Εκπαιδευτές
Ονοματεπώνυμο εκπαιδευτή Dimitrios Kalopsikakis Ιδιότητα εκπαιδευτή Lab Teaching Staff at University of Crete Email kalopsik@uoc.gr Ονοματεπώνυμο εκπαιδευτή Nikos Christakis Ιδιότητα εκπαιδευτή Researcher at University of Crete
Κοστος συμμετοχης
500 €
* Ισχύουν εκπτώσεις για ειδικές κατηγορίες
Διδακτικές Ώρες
400
Έναρξη
07/11/2023
Διάρκεια
8 μήνες
ECVET
16
Επιστ. Υπεύθυνος
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Πληροφορίες & εγγραφές
kedivim@uoc.gr