Τα τοπικά μαθήματα κατάρτισης Python, καθοδηγούμενα από εκπαιδευτές, αποδεικνύουν μέσω πρακτικής άσκησης διάφορες πτυχές της γλώσσας προγραμματισμού της Python. Ορισμένα από τα θέματα που καλύπτονται περιλαμβάνουν τα βασικά στοιχεία του προγραμματισμού Python, τον προηγμένο προγραμματισμό Python, την Python για αυτοματοποίηση δοκιμών, τη δέσμευση Python και τον αυτοματισμό και την Python για ανάλυση δεδομένων και εφαρμογές μεγάλων δεδομένων σε τομείς όπως η χρηματοδότηση, η τραπεζική και η ασφάλιση. Τα μαθήματα κατάρτισης NobleProg Python καλύπτουν επίσης τα αρχικά και προχωρημένα μαθήματα στη χρήση των βιβλιοθηκών Python και των πλαισίων για την εκμάθηση μηχανών και τη βαθιά εκμάθηση. Η εκπαίδευση Python είναι διαθέσιμη ως "onsite live training" ή "remote live training". Η επιτόπια κατάρτιση σε πραγματικό χρόνο μπορεί να πραγματοποιηθεί σε τοπικό επίπεδο στις εγκαταστάσεις του πελάτη Ελλάδα ή σε εταιρικά κέντρα κατάρτισης NobleProg στο Ελλάδα . Η απομακρυσμένη ζωντανή προπόνηση πραγματοποιείται μέσω μιας διαδραστικής, απομακρυσμένης επιφάνειας εργασίας. NobleProg - Ο τοπικός παροχέας εκπαίδευσης
Μου άρεσαν τα πάντα από την προετοιμασία και την παρουσίαση στην αλληλεπίδραση εκπαιδευτή
Fahad Malalla - Tatweer Petroleum
Course: Python Programming
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Τι σας άρεσε περισσότερο για την εκπαίδευση ;: Μου άρεσε το γεγονός ότι ήμασταν όλη την ώρα απασχολημένος προγραμματισμός, οπότε έπρεπε να επικεντρωθώ όλη την ώρα.
Katarzyna Hutnik - University of Oxford, Department of Oncology
Course: Programming for Biologists
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Τι σας άρεσε πολύ για την προπόνηση; Νομίζω ότι ο προπονητής ήταν λαμπρός. Ένας πλήρως εκπαιδευμένος εκπαιδευτικός με εμπειρία κατάρτισης.
Enric Domingo - University of Oxford, Department of Oncology
Course: Programming for Biologists
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Προτίμησα την άσκηση και τη μάθηση σχετικά με τις γωνίες και τις ακρότητες της Python
Connor Brierley-Green
Course: Python Programming
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Ο Joey έχει μολυσματικό ενθουσιασμό για τον προγραμματισμό. Και ήταν πολύ καλός στην προσαρμογή στις ανάγκες και τα συμφέροντά μας.
Randy Enkin
Course: Python Programming
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Πολλά παραδείγματα μου έκαναν εύκολο να καταλάβω.
Lingmin Cao
Course: Python Programming
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Η ολοκληρωμένη γνώση του χειριστή - όλες οι ερωτήσεις μας έδωσαν απαντήσεις που υπερέβησαν τις προσδοκίες μου ... Ο λέκτορας διεξάγει μεγάλες συζητήσεις ... Δεν του λείπει υπομονή ...
Łukasz Matulewicz
Course: Python Programming
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Μεγάλη γνώση του διδάσκοντος, ποικιλία εργαλείων και πρακτική προσέγγιση του θέματος
Magdalena Stupak
Course: Python Programming
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μεγάλη γνώση του εκπαιδευτή, πώς να μεταφράσει
Renata Cylejowska
Course: Python Programming
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γεγονός ότι η προσαρμογή έγινε σοβαρά
jurgen linsen
Course: Python Programming
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Καθώς ήμουν ο μόνος συμμετέχων, η εκπαίδευση θα μπορούσε να προσαρμοστεί στις ανάγκες μου.
Kevin THIERRY
Course: Web Development with Web2Py
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Μου άρεσαν οι ασκήσεις
Office for National Statistics
Course: Natural Language Processing with Python
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Χρήσιμο και πολύ ευγενικό.
Natalia Machrowicz
Course: Python Programming
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Κάναμε πρακτικές ασκήσεις (τα σενάρια που γράψαμε μπορούν να χρησιμοποιηθούν στην καθημερινή μας εργασία). Έκανε το μάθημα πολύ ενδιαφέρον. Μου άρεσε επίσης ο τρόπος με τον οποίο ο εκπαιδευτής μοιράστηκε τις γνώσεις του. Το έκανε με πολύ προσιτό τρόπο.
Malwina Sawa
Course: Python Programming
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Πολύ καλή προσέγγιση για να απομνημονεύσετε / επαναλάβετε τα βασικά θέματα. Πολύ ωραίες ασκήσεις "προθέρμανσης".
Course: Python Programming
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* Ευχάριστες ασκήσεις. * Μεταφέρθηκε γρήγορα σε πιο προηγμένα θέματα. * Ο εκπαιδευτής ήταν φιλικός και εύκολος να προχωρήσει. * Προσαρμοσμένη σειρά μαθημάτων για τις ανάγκες της ομάδας.
Matthew Lucas
Course: Python Programming
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ευελιξία για να προσθέσετε συγκεκριμένα θέματα στο μάθημα / μαθήματα
Marc Ammann
Course: Python Programming
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Μου αρέσει πάρα πολύ.
蒙 李
Course: Machine Learning Fundamentals with Python
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ο εκπαιδευτής εξέτασε και βοήθησε κάθε άτομο ξεχωριστά
Szymon Wolny
Course: Python Programming
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Ένα σύνολο ασκήσεων ιδανικό για το θέμα. Ασκήσεις εύκολη και "με ένα αστέρι"
Motorola Solutions Systems Polska Sp. z o.o
Course: Python Programming
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Καλή θεωρία / ασκήσεις ισορροπίας, προσαρμόζοντας το επίπεδο διαλέξεων στους ακροατές λιγότερο και πιο έμπειρους, ένα πολύ μεγάλο πλεονέκτημα για τη χρήση του Jupiter Notebook και την παρουσίαση της θεωρίας στην πράξη. Επίσης, μου άρεσε να συλλέγω ανώνυμο σχόλιο μετά το πρώτο μέρος της εκπαίδευσης - την επόμενη μέρα τα πάντα προετοιμάστηκαν σύμφωνα με τις προτάσεις μας και παρόλο που ήταν ήδη πολύ καλό, ήταν ακόμα καλύτερα αργότερα :)
Motorola Solutions Systems Polska Sp. z o.o
Course: Python Programming
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τη δέσμευση του εκπαιδευτικού, την προετοιμασία, την προσέγγιση των ακροατών, την προθυμία να εξηγήσουν όλες τις ασάφειες
Małgorzata Konior
Course: Python Programming
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Ότι ο ηγέτης προσεγγίζει όλους, ακόμα και όταν δεν ζητά βοήθεια και ελέγχει το επίπεδο της άσκησης.
Agnieszka Bielak
Course: Python Programming
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Ο εκπαιδευτής παρουσίασε πολύ σύντομες θεωρίες σχετικά με ένα συγκεκριμένο ζήτημα και πήγαμε αμέσως στην πράξη. Ένας καλός τρόπος να κρεμάσετε κάρτες, ο οποίος δίνει στον εκπαιδευτή πληροφορίες σχετικά με το πόσο χρόνο πρέπει να δαπανήσει για ένα συγκεκριμένο έργο και ποιος άλλος έχει προβλήματα με τη λύση.
Motorola Solutions Systems Polska Sp. z o.o
Course: Python Programming
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Ότι ακόμη και αν κάποιος δεν το ζήτησε, αλλά θα μπορούσατε να δείτε ότι δεν προχώρησε με το έργο, ο Krzysztof ήρθε και ήταν σε θέση να συμβουλεύσει επιδέξια
Motorola Solutions Systems Polska Sp. z o.o
Course: Python Programming
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Ο τρόπος διεξαγωγής, οι ασκήσεις, όλα από όλα τα άρεσε, είμαι πολύ χαρούμενος που ήρθα σε έναν τέτοιο εκπαιδευτή
Maksym Kolodiy
Course: Python Programming
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Πραγματικά παραδείγματα ασκήσεων
Motorola Solutions Systems Polska Sp. z o.o
Course: Python Programming
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Διαθεσιμότητα εκπαιδευτικού υλικού (Jupyter), που δημιουργήθηκε σε τακτική βάση - ενημέρωση του φορητού υπολογιστή ανάλογα με τις ερωτήσεις που έπεσαν κατά τη διάρκεια του μαθήματος. Διώξεις αμφιβολιών, απαντήσεις σε όλες τις ερωτήσεις.
Motorola Solutions Systems Polska Sp. z o.o
Course: Python Programming
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Προσβασιμότητα και ένας ενδιαφέροντος τρόπος παροχής εκπαιδευτικού υλικού.
Motorola Solutions Systems Polska Sp. z o.o
Course: Python Programming
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Εργασία στα αρχεία xlsx και csv
Łukasz Olczyk
Course: Python: Automate the Boring Stuff
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Σε βάθος κάλυψη των θεμάτων μηχανικής μάθησης, ιδιαίτερα των νευρωνικών δικτύων. Απομονώθηκε ένα μεγάλο μέρος του θέματος.
Sacha Nandlall
Course: Python for Advanced Machine Learning
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τα παντα!
UBS Business Solutions Poland Sp. z o.o.
Course: Python Programming
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Εξατομικευμένη βοήθεια
UBS Business Solutions Poland Sp. z o.o.
Course: Python Programming
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Ολα ηταν μια χαρα!
UBS Business Solutions Poland Sp. z o.o.
Course: Python Programming
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ήταν καλό να μιλήσω γι 'αυτό με κάποιον (έκανα μαθήματα on-line πριν)
UBS Business Solutions Poland Sp. z o.o.
Course: Python Programming
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Η εξειδίκευση του καθηγητή, η ικανότητά του να επιλύει ad-hoc προβλήματα που έδωσαν οι συμμετέχοντες. Έχει προετοιμαστεί καλά το πεδίο εφαρμογής του αναλυτικού προγράμματος.
UBS Business Solutions Poland Sp. z o.o.
Course: Python Programming
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Η κατάρτιση σε μια μικρή ομάδα είναι ιδανική, καθώς μπορεί να δοθεί περισσότερη προσοχή σε αντικείμενα ειδικού ενδιαφέροντος
HSCIC
Course: Unit Testing with Python
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προσαρμοσμένη εσωτερική επεξεργασία αρχείων και ανάλυση δεδομένων
Glycom A/S
Course: Data Analysis in Python using Pandas and Numpy
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Οι μελέτες περίπτωσης μας βοήθησαν να καταλάβουμε πώς μπορούμε να εφαρμόσουμε την Python στη βιομηχανία. Εκτίμησα πραγματικά τη βοήθεια του εκπαιδευτή κατά τη διάρκεια των ασκήσεων
Rajiv Dhingra - TCS
Course: Python Programming
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Καθώς είμαστε προγραμματιστές της PHP, κατάλαβε την κατάσταση και μας επέτρεψε να χαρτογραφούμε αργά τα πράγματα μεταξύ. Μου άρεσαν τα παραδείγματα και το χιούμορ που πρόσθεσε.
Soumya Tyagi - TCS
Course: Python Programming
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Ότι χρησιμοποιήσαμε τα δικά μας δεδομένα ως παραδείγματα
Glycom A/S
Course: Data Analysis in Python using Pandas and Numpy
Translated by
όλα
MTU Aero Engines Polska Sp. z o. o.
Course: Python Programming
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Ενδιαφέροντα θέματα
MTU Aero Engines Polska Sp. z o. o.
Course: Python Programming
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Ποικιλία προετοιμασμένων θεμάτων και παραδειγμάτων.
MTU Aero Engines Polska Sp. z o. o.
Course: Python Programming
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η εκπαίδευση δεν είναι στυλ παρουσίασης. Κωδικοποιούσαμε με τον εκπαιδευτή ..
Bhutan Telecom
Course: Web Development with Django
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Απόλαυσα τα πάντα.
Thukten Dendup - Bhutan Telecom
Course: Web Development with Django
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Είναι μια νέα εμπειρία, ένα νέο πλαίσιο και ανυπομονούμε να κάνουμε κάτι χρησιμοποιώντας το μάθημα που μαθαίνουμε στα μαθήματα ..
Jigme - Bhutan Telecom
Course: Web Development with Django
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Ο εκπαιδευτής μοιράζετο πραγματικές εμπειρίες, είναι ωραίο να μαθαίνεις από πραγματικούς επαγγελματίες.
Fednot
Course: Python Programming
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Ο εκπαιδευτής ήταν εξαιρετικός, ήταν πάντα έτοιμος να απαντήσει στις ερωτήσεις μου και να μοιραστεί όσο το δυνατόν περισσότερες γνώσεις.
Fahad Malalla - Tatweer Petroleum
Course: Advanced Python
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1: 1 πολύ εντατική, αλλά έμαθε πολλά.
Karen Dyke - BT
Course: Python: Automate the Boring Stuff
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η έμφαση στα παραδείγματα με κωδικοποίηση "στον προβολέα" είναι σίγουρα σε + για τον Tom.
ADVA OPTICAL NETWORKING SP. ZO O.
Course: Advanced Python
Translated by
Πολύ καλή προσέγγιση για να απομνημονεύσετε / επαναλάβετε τα βασικά θέματα. Πολύ ωραίες ασκήσεις "προθέρμανσης".
Course: Python Programming
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| Code | Name | Duration | Overview |
|---|---|---|---|
| pythonprog | Python Programming | 28 hours | This course is designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python drives businesses and is used by scientists all over the world – it is one of the most popular programming languages. The course can be delivered using Python 2.7.x or 3.x, with practical exercises making use of the full power of both versions of the language. This course can be delivered on any operating system (all flavours of UNIX, including Linux and Mac OS X, as well as Microsoft Windows). The practical exercises constitute about 70% of the course time, and around 30% are demonstrations and presentations. Discussions and questions can be asked throughout the course. Note: the training can be tailored to specific needs upon prior request ahead of the proposed course date. |
| pygis | Python for Geographic Information System (GIS) | 21 hours | A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data. The acronym GIS is sometimes used for geographic information science (GIScience) to refer to the academic discipline that studies geographic information systems and is a large domain within the broader academic discipline of geoinformatics. The use of Python with GIS has substantially increased over the last two decades, particularly with the introduction of Python 2.0 series in 2000, which included many new programming features that made the language much easier to deploy. Since that time, Python has not only been utilized within commercial GIS such as products by Esri but also open source platforms, including as part of QGIS and GRASS. In fact, Python today is by far the most widely used language by GIS users and programmers. This program covers the usage of Python and its advance libraries like geopandas, pysal, bokeh and osmnx to implement your own GIS features. The program also covers introductory modules around ArcGIS API, and QGIS toolboox. |
| mlfinancepython | Machine Learning for Finance (with Python) | 21 hours | Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Python is a programming language famous for its clear syntax and readability. It offers an excellent collection of well-tested libraries and techniques for developing machine learning applications. In this instructor-led, live training, participants will learn how to apply machine learning techniques and tools for solving real-world problems in the finance industry. Participants first learn the key principles, then put their knowledge into practice by building their own machine learning models and using them to complete a number of team projects. By the end of this training, participants will be able to: - Understand the fundamental concepts in machine learning - Learn the applications and uses of machine learning in finance - Develop their own algorithmic trading strategy using machine learning with Python Audience - Developers - Data scientists Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| sparkpython | Python and Spark for Big Data (PySpark) | 21 hours | Python is a high-level programming language famous for its clear syntax and code readibility. Spark is a data processing engine used in querying, analyzing, and transforming big data. PySpark allows users to interface Spark with Python. In this instructor-led, live training, participants will learn how to use Python and Spark together to analyze big data as they work on hands-on exercises. By the end of this training, participants will be able to: - Learn how to use Spark with Python to analyze Big Data. - Work on exercises that mimic real world circumstances. - Use different tools and techniques for big data analysis using PySpark. Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| pythonbigdata | Analyzing Big Financial Data with Python | 35 hours | Python is a high-level programming language famous for its clear syntax and code readibility. In this instructor-led, live training, participants will learn how to use Python for quantitative finance. By the end of this training, participants will be able to: - Understand the fundamentals of Python programming - Use Python for financial applications including implementing mathematical techniques, stochastics, and statistics - Implement financial algorithms using performance Python Audience - Developers - Quantitative analysts Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| pythoncomputervision | Computer Vision with Python | 14 hours | Computer Vision is a field that involves automatically extracting, analyzing, and understanding useful information from digital media. Python is a high-level programming language famous for its clear syntax and code readibility. In this instructor-led, live training, participants will learn the basics of Computer Vision as they step through the creation of set of simple Computer Vision application using Python. By the end of this training, participants will be able to: - Understand the basics of Computer Vision - Use Python to implement Computer Vision tasks - Build their own face, object, and motion detection systems Audience - Python programmers interested in Computer Vision Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| dlforbankingwithpython | Deep Learning for Banking (with Python) | 28 hours | Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks. Python is a high-level programming language famous for its clear syntax and code readability. In this instructor-led, live training, participants will learn how to implement deep learning models for banking using Python as they step through the creation of a deep learning credit risk model. By the end of this training, participants will be able to: - Understand the fundamental concepts of deep learning - Learn the applications and uses of deep learning in banking - Use Python, Keras, and TensorFlow to create deep learning models for banking - Build their own deep learning credit risk model using Python Audience - Developers - Data scientists Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| dlforfinancewithpython | Deep Learning for Finance (with Python) | 28 hours | Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks. Python is a high-level programming language famous for its clear syntax and code readability. In this instructor-led, live training, participants will learn how to implement deep learning models for finance using Python as they step through the creation of a deep learning stock price prediction model. By the end of this training, participants will be able to: - Understand the fundamental concepts of deep learning - Learn the applications and uses of deep learning in finance - Use Python, Keras, and TensorFlow to create deep learning models for finance - Build their own deep learning stock price prediction model using Python Audience - Developers - Data scientists Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| microservicespython | Building Microservices with Python | 7 hours | Microservices refer to an application architecture style that promotes the use of independent, self-contained programs. Python is a dynamic high-level programming language that is ideal for both scripting as welll as application development. Python's expansive library of open source tools and frameworks make it a practical choice for building microservices. In this instructor-led, live training, participants will learn the fundamentals of microservices as they step through the creation of a microservice using Python. By the end of this training, participants will be able to: - Understand the basics of building microservices - Learn how to use Python to build microservices - Learn how to use Docker to deploy Python based microservices Audience - Developers - Programmers Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| tableaupython | Tableau with Python | 14 hours | Tableau is a business intelligence and data visualization tool. Python is a widely used programming language which provides support for a wide variety of statistical and machine learning techniques. Tableau's data visualization power and Python's machine learning capabilities, when combined, help developers rapidly build advanced data analytics applications for various business use cases. In this instructor-led, live training, participants will learn how to combine Tableau and Python to carry out advanced analytics. Integration of Tableau and Python will be done via the TabPy API. By the end of this training, participants will be able to: - Integrate Tableau and Python using TabPy API - Use the integration of Tableau and Python to analyze complex business scenarios with few lines of Python code Audience - Developers - Data scientists Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| textsum | Text Summarization with Python | 14 hours | In Python Machine Learning, the Text Summarization feature is able to read the input text and produce a text summary. This capability is available from the command-line or as a Python API/Library. One exciting application is the rapid creation of executive summaries; this is particularly useful for organizations that need to review large bodies of text data before generating reports and presentations. In this instructor-led, live training, participants will learn to use Python to create a simple application that auto-generates a summary of input text. By the end of this training, participants will be able to: - Use a command-line tool that summarizes text. - Design and create Text Summarization code using Python libraries. - Evaluate three Python summarization libraries: sumy 0.7.0, pysummarization 1.0.4, readless 1.0.17 Audience - Developers - Data Scientists Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| drlpython | Deep Reinforcement Learning with Python | 21 hours | Deep Reinforcement Learning refers to the ability of an "artificial agent" to learn by trial-and-error and rewards-and-punishments. An artificial agent aims to emulate a human's ability to obtain and construct knowledge on its own, directly from raw inputs such as vision. To realize reinforcement learning, deep learning and neural networks are used. Reinforcement learning is different from machine learning and does not rely on supervised and unsupervised learning approaches. In this instructor-led, live training, participants will learn the fundamentals of Deep Reinforcement Learning as they step through the creation of a Deep Learning Agent. By the end of this training, participants will be able to: - Understand the key concepts behind Deep Reinforcement Learning and be able to distinguish it from Machine Learning - Apply advanced Reinforcement Learning algorithms to solve real-world problems - Build a Deep Learning Agent Audience - Developers - Data Scientists Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| iotpython | Programming for IoT with Python | 14 hours | Internet of Things (IoT) is a network infrastructure that connects physical objects and software applications wirelessly, allowing them to communicate with each other and exchange data via network communications, cloud computing, and data capture. Python is a high-level programming language recommended for IoT due to its clear syntax and large community support. In this instructor-led, live training, participants will learn how to program IoT solutions with Python. By the end of this training, participants will be able to: - Understand the fundamentals of IoT architecture - Learn the basics of using Raspberry Pi - Install and configure Python on Raspberry Pi - Learn the benefits of using Python in programming IoT systems - Build, test, deploy, and troubleshoot an IoT system using Python and Raspberry Pi Audience - Developers - Engineers Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice Note - To request a customized training for this course, please contact us to arrange. |
| pythonexcel | Python for Excel | 14 hours | Python is a high-level programming language famous for its clear syntax and code readability. Excel is a spreadsheet application developed by Microsoft which is widely used in many industries. Adding Python to Excel makes it a powerful tool for data analytics. In this instructor-led, live training, participants will learn how to combine the capabilities of Python and Excel. By the end of this training, participants will be able to: - Install and configure packages for integrating Python and Excel - Read, write, and manipulate Excel files using Python - Call Python functions from Excel Audience - Developers - Programmers Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice Note - To request a customized training for this course, please contact us to arrange. |
| chatbotpython | Building Chatbots in Python | 21 hours | ChatBots are computer programs that automatically simulate human responses via chat interfaces. ChatBots help organizations maximize their operations efficiency by providing easier and faster options for their user interactions. In this instructor-led, live training, participants will learn how to build chatbots in Python. By the end of this training, participants will be able to: - Understand the fundamentals of building chatbots - Build, test, deploy, and troubleshoot various chatbots using Python Audience - Developers Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice Note - To request a customized training for this course, please contact us to arrange. |
| dlfortelecomwithpython | Deep Learning for Telecom (with Python) | 28 hours | Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks. Python is a high-level programming language famous for its clear syntax and code readability. In this instructor-led, live training, participants will learn how to implement deep learning models for telecom using Python as they step through the creation of a deep learning credit risk model. By the end of this training, participants will be able to: - Understand the fundamental concepts of deep learning - Learn the applications and uses of deep learning in telecom - Use Python, Keras, and TensorFlow to create deep learning models for telecom - Build their own deep learning customer churn prediction model using Python Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| appaipy | Applied AI from Scratch in Python | 28 hours | This is a 4 day course introducing AI and it's application using the Python programming language. There is an option to have an additional day to undertake an AI project on completion of this course. |
| mongodbpython | MongoDB for Python Developers | 14 hours | This instructor-led, live training (onsite or remote) is aimed at developers wishing to learn how to use MongoDB as the database for Python their applications. By the end of this training, participants will be able to: - Install and configure MongoDB - Understand the difference between accessing a NoSQL document database and a traditional relational databases' (e.g., MySQL) - Query a MongoDB database from within Python - Create and write data to a MongoDB databasse - Understand MongoDB's "data processing pipeline" - Perform real-time analytics and statistical analysis - Generate reports for dashboarding - Implement exception handling in Python application Format of the Course: - Interactive lecture and discussion - Lots of exercises and practice - Hands-on implementation in a live-lab environment Course Customization Options: - To request a customized training for this course, please contact us to arrange. |
| dataminpython | Data Mining with Python | 14 hours | αυτή η καθοδηγούμενη από εκπαιδευτές, ζωντανή εκπαίδευση (επιτόπου ή απομακρυσμένη) απευθύνεται σε αναλυτές δεδομένων και επιστήμονες δεδομένων που επιθυμούν να εφαρμόσουν πιο προηγμένες τεχνικές ανάλυσης δεδομένων για την εξόρυξη δεδομένων χρησιμοποιώντας την Python. μέχρι το τέλος αυτής της εκπαίδευσης, οι συμμετέχοντες θα είναι σε θέση να: - κατανοούν σημαντικούς τομείς εξόρυξης δεδομένων, συμπεριλαμβανομένης της εξόρυξης κανόνων σύνδεσης, της ανάλυσης συναισθήματος κειμένου, του αυτόματου Σύνοψη κειμένου και της ανίχνευσης ανωμαλιών δεδομένων. - συγκρίνετε και να εφαρμόσουν διάφορες στρατηγικές για την επίλυση προβλημάτων εξόρυξης δεδομένων πραγματικού κόσμου. - Κατανοήστε και ερμηνεύστε τα αποτελέσματα. μορφή του μαθήματος - διαδραστική διάλεξη και συζήτηση. - πολλές ασκήσεις και εξάσκηση. - εφαρμογή σε περιβάλλον ζωντανού εργαστηρίου. επιλογές προσαρμογής μαθήματος - για να ζητήσετε μια προσαρμοσμένη εκπαίδευση για αυτό το μάθημα, παρακαλούμε επικοινωνήστε μαζί μας για να κανονίσετε. |
| ooppython | Learn Object-Oriented Programming with Python | 14 hours | Object-Oriented Programming (OOP) is a programming paradigm based around the concept of objects. OOP is more data-focused rather than logic-focused. Python is a high-level programming language famous for its clear syntax and code readibility. In this instructor-led, live training, participants will learn how to get started with Object-Oriented Programming using Python. By the end of this training, participants will be able to: - Understand the fundamental concepts of Object-Oriented Programming - Understand the OOP syntax in Python - Write their own object-oriented program in Python Audience - Beginners who would like to learn about Object-Oriented Programming - Developers interested in learning OOP in Python - Python programmers interested in learning OOP Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice |
| pythonfinance | Python Programming for Finance | 35 hours | Python is a programming language that has gained huge popularity in the financial industry. Adopted by the largest investment banks and hedge funds, it is being used to build a wide range of financial applications ranging from core trading programs to risk management systems. In this instructor-led, live training, participants will learn how to use Python to develop practical applications for solving a number of specific finance related problems. By the end of this training, participants will be able to: - Understand the fundamentals of the Python programming language - Download, install and maintain the best development tools for creating financial applications in Python - Select and utilize the most suitable Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.) - Build applications that solve problems related to asset allocation, risk analysis, investment performance and more - Troubleshoot, integrate, deploy, and optimize a Python application Audience - Developers - Analysts - Quants Format of the course - Part lecture, part discussion, exercises and heavy hands-on practice Note - This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange. |
| progbio | Programming for Biologists | 28 hours | This is a practical course, which shows why programming is a powerful tool in the context of solving biological problems. During the course participants will be taught the Python programming language, a language widely considered both powerful as well as easy to use. This course might be considered as a demonstration how bioinformatics improves biologists lives. The course is designed and aimed for people without computer science background who want to learn to program. This course is suited for: - Researchers dealing with biological data. - Scientists who would like to learn how to automate everyday tasks and analyse data. - Managers who want to learn how programming improves workflows and conducting projects. By the end of the course, participants will be able to write short programs, which will allow them to manipulate, analyse and deal with biological data and present results in a graphical format. |
| seleniumpython | Selenium with Python for Test Automation | 14 hours | Selenium is an open source library for automating web application testing across multiple browsers. Selenium interacts with a browser as people do: by clicking links, filling out forms and validating text. It is the most popular tool for web application test automation. Selenium is built on the WebDriver framework and has excellent bindings for numerous scripting languages, including Python. In this training participants combine the power of Python with Selenium to automate the testing of a sample web application. By combining theory with practice in a live lab environment, participants will gain the knowledge and practice needed to automate their own web testing projects using Python and Selenium. Audience - Testers and Developers Format of the course - Part lecture, part discussion, heavy hands-on practice |
| mlfunpython | Machine Learning Fundamentals with Python | 14 hours | The aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the Python programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results. Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications. |
| python_nltk | Natural Language Processing with Python | 28 hours | This course introduces linguists or programmers to NLP in Python. During this course we will mostly use nltk.org (Natural Language Tool Kit), but also we will use other libraries relevant and useful for NLP. At the moment we can conduct this course in Python 2.x or Python 3.x. Examples are in English or Mandarin (普通话). Other languages can be also made available if agreed before booking. |
| mlfsas | Machine Learning Fundamentals with Scala and Apache Spark | 14 hours | The aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the Scala programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results. Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications. |
| django | Web Development with Django | 21 hours | Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. Audience This course is directed at developers and engineers seeking to incorporate Django in their projects |
| web2py | Web Development with Web2Py | 28 hours | Web2py is a python based free open source full-stack framework for rapid development of fast, scalable, secure and portable database-driven web-based applications. Audience This course is directed at Engineers and Developers using web2py as a framework for web development |
| datapyth | Data Analysis in Python using Pandas and Numpy | 14 hours | Pandas is a Python package that provides data structures for working with structured (tabular, multidimensional, potentially heterogeneous) and time series data. |
| flask | Web application development with Flask | 14 hours | This practical course is addressed to Python developers that want to create and maintain their first web applications. It is also addressed to people who are already familiar with other web frameworks such as Django or Web2py, and want to learn how using a microframework (i.e. a framework which glues together third-party libraries instead of providing a self-contained universal solution) changes the process. A significant part of the course is devoted not to Flask itself (it's tiny), but to third-party libraries and tools often used in Flask projects. |
| Course | Course Date | Course Price [Remote / Classroom] |
|---|---|---|
| Data Mining with Python - Πάτρα (Patras) | Mon, 2019-03-25 09:30 | 3000EUR / 3600EUR |
| Data Mining with Python - Θεσσαλονίκη (Thessaloniki) | Tue, 2019-03-26 09:30 | 3000EUR / 3600EUR |
| Data Mining with Python - Nicosia, Jacovides Tower | Mon, 2019-04-29 09:30 | 3000EUR / 3600EUR |
| Data Mining with Python - Θεσσαλονίκη (Thessaloniki) | Wed, 2019-05-15 09:30 | 3000EUR / 3600EUR |
| Data Mining with Python - Πάτρα (Patras) | Thu, 2019-06-13 09:30 | 3000EUR / 3600EUR |
| Course | Venue | Course Date | Course Price [Remote / Classroom] |
|---|---|---|---|
| Introduction to Embedded Computers | Αθήνα (Athens), Acropolis | Mon, 2019-02-25 09:30 | 3150EUR / 3750EUR |
| Neural computing – Data science | Αθήνα (Athens), Acropolis | Mon, 2019-06-03 09:30 | 3150EUR / 3750EUR |
| Introduction to Ansible Automation | Θεσσαλονίκη (Thessaloniki) | Mon, 2019-06-10 09:30 | 1350EUR / 1750EUR |
| Introduction to R with Time Series Analysis | Αθήνα (Athens), Acropolis | Wed, 2019-07-31 09:30 | 4725EUR / 5525EUR |
| AI Awareness for Telecom | Πάτρα (Patras) | Thu, 2019-09-05 09:30 | 3150EUR / 3750EUR |
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