Python Schulungen
Lokale, instruktorierte Live-Python-Trainingskurse demonstrieren durch praktisches Üben verschiedene Aspekte der Programmiersprache Python Einige der behandelten Themen umfassen die Grundlagen der Python-Programmierung, erweiterte Python-Programmierung, Python für Testautomatisierung, Python-Skripting und Automatisierung und Python für Datenanalyse und Big Data-Anwendungen in Bereichen wie Finanzen, Bankwesen und Versicherungen NobleProg Python Trainingskurse umfassen auch Anfänger- und Fortgeschrittenenkurse in der Verwendung von Python-Bibliotheken und Frameworks für Machine Learning und Deep Learning Python-Training ist als "Live-Training vor Ort" oder "Fern-Live-Training" verfügbar Onsite Live Training kann vor Ort bei Kunden durchgeführt werden Schweiz oder in NobleProg Corporate Trainingszentren in Schweiz Remote-Live-Training wird über einen interaktiven Remote-Desktop durchgeführt NobleProg Ihr lokaler Trainingsanbieter.
Erfahrungsberichte
I liked everything from the preparation and presentation to trainer interaction
Fahad Malalla - Tatweer Petroleum
Course Name: Python programming
What did you like the most about the training?: I liked the fact that we were all the time busy programming, so I had to focus the whole time. Katarzyna Hutnik - University of Oxford, Department of Oncology
Course Name: Introductory R for Biologists
What did you like the most about the training?: I think the trainer was brilliant. A fully qualified teacher with training experience. Enric Domingo - University of Oxford, Department of Oncology
Course Name: Introductory R for Biologists
I preferred the exercise and learning about the nooks and crannies of Python
Connor Brierley-Green
Course Name: Python Programming
Joey has an infectious enthusiasm about programming. And he was very good at adapting to our needs and interests on the fly.
Randy Enkin
Course Name: Python Programming
Many examples made me easy to understand.
Lingmin Cao
Course Name: Python Programming
Die umfassende Kenntnis des Leitfadens zu all unseren Fragen gab Antworten, die meine Erwartungen übertrafen ... Der Dozent führt großartige Diskussionen ... Ihm fehlt es nicht an Geduld ...
Łukasz Matulewicz
Course Name: Programowanie w języku Python
Translated by
Große Kenntnisse des Dozenten, Vielfalt der Werkzeuge und praktische Herangehensweise an das Thema
Magdalena Stupak
Course Name: Programowanie w języku Python
Translated by
großes Wissen des Trainers, wie man übersetzt
Renata Cylejowska
Course Name: Programowanie w języku Python
Translated by
fact that customisation was taken seriously
jurgen linsen
Course Name: Python Programming
I did like the exercises
Office for National Statistics
Course Name: Natural Language Processing with Python
Hilfsbereit und sehr nett.
Natalia Machrowicz
Course Name: Python Programming
Translated by
Wir haben praktische Übungen gemacht (die Skripte, die wir geschrieben haben, können in unserer täglichen Arbeit verwendet werden). Es machte den Kurs sehr interessant. Ich mochte auch, wie der Trainer sein Wissen teilte. Er hat es sehr zugänglich gemacht
Malwina Sawa
Course Name: Python Programming
Translated by
Sehr guter Ansatz zum Einprägen / Wiederholen der wichtigsten Themen. Sehr schöne "Aufwärmübungen"
Course Name: Python Programming
Translated by
* Angenehme Übungen. * Schnell in fortgeschrittenere Themen umgezogen. * Trainer war freundlich und leicht zu verstehen. * Maßgeschneiderter Kurs für die Bedürfnisse des Teams
Matthew Lucas
Course Name: Python Programming
Translated by
felixibility um bestimmte Themen in den Kurs / Unterricht aufzunehmen
Marc Ammann
Course Name: Python Programming
Translated by
Alle mögen es
蒙 李
Course Name: Machine Learning Fundamentals with Python
Translated by
Alle mögen es
蒙 李
Course Name: Machine Learning Fundamentals with Python
Translated by
Der Trainer hat jede Person einzeln betrachtet und ihnen geholfen
Szymon Wolny
Course Name: Programowanie w języku Python
Translated by
Eine Reihe von Übungen, die ideal zum Thema passen. Übungen einfach und "mit einem Stern"
Motorola Solutions Systems Polska Sp. z o.o
Course Name: Programowanie w języku Python
Translated by
Gute Balance-Theorie / Übungen, Anpassung des Niveaus der Vorträge an weniger erfahrene Hörer, ein sehr großes Plus für die Verwendung von Jupiter Notebook und die praktische Umsetzung der Theorie. Ich sammelte auch gerne anonymes Feedback nach dem ersten Teil des Trainings am nächsten Tag wurde alles nach unseren Vorschlägen vorbereitet und obwohl es schon sehr gut war, dann war es noch besser :) Mot
Motorola Solutions Systems Polska Sp. z o.o
Course Name: Programowanie w języku Python
Translated by
Engagement des Lehrers, Vorbereitung, Annäherung an die Zuhörer, Bereitschaft, alle Unklarheiten zu erklären
Małgorzata Konior
Course Name: Programowanie w języku Python
Translated by
Dass der Leiter sich allen nähert, auch wenn er nicht um Hilfe ruft und das Niveau der Übung überprüft.
Agnieszka Bielak
Course Name: Programowanie w języku Python
Translated by
Der Trainer stellte sehr kurze Theorien zu einem bestimmten Thema vor und wir gingen sofort in die Praxis. Eine nette Art, Karten aufzuhängen, die dem Trainer Informationen darüber geben, wie viel Zeit er für eine bestimmte Aufgabe aufwenden muss und wer sonst Probleme mit der Lösung hat.
Motorola Solutions Systems Polska Sp. z o.o
Course Name: Programowanie w języku Python
Translated by
Dass, auch wenn jemand nicht darum gebeten hat, aber man merkt, dass er die Aufgabe nicht vorantreibt, kam Krzysztof und konnte geschickt beraten
Motorola Solutions Systems Polska Sp. z o.o
Course Name: Programowanie w języku Python
Translated by
Die Art zu leiten, die Übungen, alles in allem hat mir gefallen, ich bin sehr froh, dass ich zu solch einem Trainer gekommen bin
Maksym Kolodiy
Course Name: Programowanie w języku Python
Translated by
Echte Beispiele für Übungen
Motorola Solutions Systems Polska Sp. z o.o
Course Name: Programowanie w języku Python
Translated by
Verfügbarkeit von Schulungsmaterialien (Jupyter), die ständig aktualisiert werden, um das Notebook je nach den während des Kurses gestellten Fragen zu aktualisieren. Zweifel zerstreuen, Antworten auf alle Fragen.
Motorola Solutions Systems Polska Sp. z o.o
Course Name: Programowanie w języku Python
Translated by
Zugänglichkeit und eine interessante Art der Bereitstellung von Unterrichtsmaterialien.
Motorola Solutions Systems Polska Sp. z o.o
Course Name: Programowanie w języku Python
Translated by
Arbeite an xlsx- und csv-Dateien
Łukasz Olczyk
Course Name: Python: Automate the boring stuff
Translated by
Indepth Berichterstattung über maschinelles Lernen Themen, insbesondere neuronale Netze. Entmystifiziert eine Menge des Themas
Sacha Nandlall
Course Name: Python for Advanced Machine Learning
Translated by
alles!
UBS Business Solutions Poland Sp. z o.o.
Course Name: Python Programming
Translated by
Personalisierte Hilfe
UBS Business Solutions Poland Sp. z o.o.
Course Name: Python Programming
Translated by
Alles war gut!
UBS Business Solutions Poland Sp. z o.o.
Course Name: Python Programming
Translated by
Es war gut, mit jemandem darüber zu sprechen (ich habe vorher online Kurse gemacht)
UBS Business Solutions Poland Sp. z o.o.
Course Name: Python Programming
Translated by
Expertise des Lehrers, seine Fähigkeit, von den Teilnehmern gegebene Adhoc-Probleme zu lösen. Eine gut vorbereitet den Umfang des Lehrplans
UBS Business Solutions Poland Sp. z o.o.
Course Name: Python Programming
Translated by
Das Training in einer kleinen Gruppe ist ideal, da mehr Aufmerksamkeit auf bestimmte Themen gelegt werden kann
HSCIC
Course Name: Unit Testing with Python
Translated by
Alles was ich am 6. bewertet habe
AB S.A.
Course Name: Machine Learning - szkolenie dedykowane
Translated by
viele Informationen
Tomasz Szumigalski
Course Name: Machine Learning - szkolenie dedykowane
Translated by
Probleme klar erklärt
AB S.A.
Course Name: Machine Learning - szkolenie dedykowane
Translated by
Großes Wissen über den Trainer und die Fähigkeit, die Bedeutung unserer dummen Fragen zu verstehen;)
AB S.A.
Course Name: Machine Learning - szkolenie dedykowane
Translated by
kundenspezifische, interne Dateiverarbeitung und Datenanalyse
Glycom A/S
Course Name: Data Analysis in Python using Pandas and Numpy
Translated by
Die Fallstudien haben uns geholfen zu verstehen, wie wir Python in der Industrie anwenden können. Ich habe die Hilfe des Trainers während der Übungen sehr geschätzt
Rajiv Dhingra - TCS
Course Name: Python Programming
Translated by
Da wir PHP-Entwickler sind, hat er die Situation verstanden und uns erlaubt, die Dinge langsam zwischenzuordnen. Ich mochte die Beispiele und den Humor, den er hinzufügte
Soumya Tyagi - TCS
Course Name: Python Programming
Translated by
Dass wir unsere eigenen Daten als Beispiele verwendet haben
Glycom A/S
Course Name: Data Analysis in Python using Pandas and Numpy
Translated by
Alles
MTU Aero Engines Polska Sp. z o. o.
Course Name: Programowanie w języku Python
Translated by
Interessante Fragen
MTU Aero Engines Polska Sp. z o. o.
Course Name: Programowanie w języku Python
Translated by
Vielzahl von vorbereiteten Ausgaben und Beispielen
MTU Aero Engines Polska Sp. z o. o.
Course Name: Programowanie w języku Python
Translated by
Sehr gute Unterstützung während der Übungen. Trainer hatten ausgezeichnete Kenntnisse des Themas
Marc Pierreux - Proximus
Course Name: Python Fundamentals
Translated by
Es ist Zeit, Übungen und die Verfügbarkeit von Trainern zu machen, um den Code persönlich zu überprüfen und Ratschläge zu geben
Proximus
Course Name: Python Fundamentals
Translated by
die Übungen.
Proximus
Course Name: Python Fundamentals
Translated by
Erfahrung des Trainers.
Proximus
Course Name: Python Fundamentals
Translated by
Schulungsübersicht
| Code | Name | Dauer | Übersicht |
|---|---|---|---|
| pythonprog | Python Programmierung | 28 hours | In diesem Kurs können Sie die Programmiersprache Python erlernen. Der Schwerpunkt des Kurses liegt dabei auf den Grundlagen der Sprache und zentralen Programmbibliotheken. Der Kurs besteht zur Hälfte aus Theorie, zur Hälfte aus praktischen Übungen. Er ist sowohl für Programmierer als auch Nichtprogrammierer geeignet. |
| mlbankingpython_ | Machine Learning for Banking (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 banking 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. Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| 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. |
| progbio | Programmieren in Python für Biologen | 28 hours | Dieser Kurs richtet sich an: Wissenschaftler, die mit biologischen Daten arbeiten. Forscher, die Routineaufgaben automatisieren möchten. Biologen, die Ihre Arbeit mit einfachen Programmen verstärken möchten ohne gleich Vollzeitprogrammierer zu werden. Manager, die ein Grundverständnis für die Arbeit von Programmierern erlangen möchten. Am Ende des Kurses werden die Teilnehmer in der Lage sein kurze Programme selbständig zu schreiben, um biologische Daten zu analysieren und zu manipulieren. |
| 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. |
| 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. |
| 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_nlp | Natural Language Processing with Deep Dive in Python and NLTK | 35 hours | By the end of the training the delegates are expected to be sufficiently equipped with the essential python concepts and should be able to sufficiently use NLTK to implement most of the NLP and ML based operations. The training is aimed at giving not just an executional knowledge but also the logical and operational knowledge of the technology therein. |
| 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. |
| 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. |
| 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. |
| 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. |
| 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 |
| 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. |
| dlfornlp | Deep Learning for NLP (Natural Language Processing) | 28 hours | Deep Learning for NLP allows a machine to learn simple to complex language processing. Among the tasks currently possible are language translation and caption generation for photos. DL (Deep Learning) is a subset of ML (Machine Learning). Python is a popular programming language that contains libraries for Deep Learning for NLP. In this instructor-led, live training, participants will learn to use Python libraries for NLP (Natural Language Processing) as they create an application that processes a set of pictures and generates captions. By the end of this training, participants will be able to: Design and code DL for NLP using Python libraries Create Python code that reads a substantially huge collection of pictures and generates keywords Create Python Code that generates captions from the detected keywords Audience Programmers with interest in linguistics Programmers who seek an understanding of NLP (Natural Language Processing) Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| behave | Behave: BDD with Python (Cucumber/Gherkin for Python) | 7 hours | Behave is an open-source, Python-based BDD framework for writing tests in a natural language style. BDD, or Behavior Driven Development, is an agile software development technique that encourages collaboration among developers, QA and non-technical business people in a software project. This training begins with a discussion of BDD and how the Behave framework can be used to carry out BDD testing for web applications. Participants are given ample opportunity to interact with the instructor and peers while implementing the concepts and tactics learned in this hands-on, practice-based lab environment. By the end of this training, participants will have a firm understanding of BDD and Behave, as well as the necessary practice to implement these techniques and tools in real-world test scenarios. Audience Testers and Developers Format of the course Heavy emphasis on hands-on practice. Most of the concepts are learned through samples, exercises and hands-on development. |
| 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 |
| 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 |
| 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 Audience Developers IT Professionals Data Scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| pythonautomation | Python: Automate the Boring Stuff | 14 hours | This instructor-led training is based on the popular book, "Automate the Boring Stuff with Python", by Al Sweigart. It is aimed at beginners and covers essential Python programming concepts through practical, hands-on exercises and discussions. The focus is on learning to write code to dramatically increase office productivity. By the end of this training, participants will know how to program in Python and apply this new skill for: Automating tasks by writing simple Python programs. Writing programs that can do text pattern recognition with "regular expressions". Programmatically generating and updating Excel spreadsheets. Parsing PDFs and Word documents. Crawling web sites and pulling information from online sources. Writing programs that send out email notifications. Use Python's debugging tools to quickly resolve bugs. Programmatically controlling the mouse and keyboard to click and type for you. Audience Non-programmers wishing to learn programming with Python Professionals and company teams wishing to optimize their office productivity Managers wishing to automate tedious processes and workflows Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| 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 |
| kivy | Kivy: Building Android Apps with Python | 7 hours | Kivy is an open-source cross-platform graphical user interface library written in Python, which allows multi-touch application development for a wide selection of devices. In this instructor-led, live training participants will learn how to install and deploy Kivy on different platforms, customize and manipulate widgets, schedule, trigger and respond to events, modify graphics with multi-touching, resize the screen, package apps for Android, and more. By the end of this training, participants will be able to Relate the Python code and the Kivy language Have a solid understanding of how Kivy works and makes use of its most important elements such as, widgets, events, properties, graphics, etc. Seamlessly develop and deploy Android apps based on different business and design requirements Audience Programmers or developers with Python knowledge who want to develop multi-touch Android apps using the Kivy framework Android developers with Python knowledge 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 |
| pythonmultipurpose | Advanced Python | 28 hours | In this instructor-led training, participants will learn advanced Python programming techniques, including how to apply this versatile language to solve problems in areas such as distributed applications, data analysis and visualization, UI programming and maintenance scripting. Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Notes If you wish to add, remove or customize any section or topic within this course, please contact us to arrange. |
| 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 |
| restfulapi | Designing RESTful APIs | 14 hours | APIs (Application Programming Interface) allow for your application to connect with other applications. In this instructor-led, live training, participants will learn how to write high-quality APIs as they build and secure a backend API server. By the end of this training, participants will be able to: Choose from a number of frameworks for building APIs Understand and model the APIs published by companies such as Google and Facebook Create and publish their own Restful APIs for public consumption Secure their APIs through token-based authentication Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Note To customize this course for other languages, such as PHP, Javascript, etc., please contact us to arrange |
| 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 |
| pythonadvml | Python for Advanced Machine Learning | 21 hours | In this instructor-led, live training, participants will learn the most relevant and cutting-edge machine learning techniques in Python as they build a series of demo applications involving image, music, text, and financial data. By the end of this training, participants will be able to: Implement machine learning algorithms and techniques for solving complex problems Apply deep learning and semi-supervised learning to applications involving image, music, text, and financial data Push Python algorithms to their maximum potential Use libraries and packages such as NumPy and Theano Audience Developers Analysts Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| microservicespython | Developing 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 |
| pythontextml | Python: Machine Learning with Text | 21 hours | In this instructor-led, live training, participants will learn how to use the right machine learning and NLP (Natural Language Processing) techniques to extract value from text-based data. By the end of this training, participants will be able to: Solve text-based data science problems with high-quality, reusable code Apply different aspects of scikit-learn (classification, clustering, regression, dimensionality reduction) to solve problems Build effective machine learning models using text-based data Create a dataset and extract features from unstructured text Visualize data with Matplotlib Build and evaluate models to gain insight Troubleshoot text encoding errors Audience Developers Data Scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
Upcoming Courses
| Course | Schulungsdatum | Kurspreis (Fernkurs / Schulungsraum) |
|---|---|---|
| Python: Automate the Boring Stuff - Bern | Mi, 2018-07-18 09:30 | 3000EUR / 3500EUR |
| Designing RESTful APIs - Basel | Mo, 2018-07-23 09:30 | 3000EUR / 3500EUR |
| Python for Advanced Machine Learning - Zürich | Mo, 2018-08-20 09:30 | 5250EUR / 5900EUR |