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Python Training Courses

Python Training Courses

Local, instructor-led live Python training courses demonstrate through hands-on practice various aspects of the Python programming language. Some of the topics covered include the fundamentals of Python programming, advanced Python programming, Python for test automation, Python scripting and automation, and Python for Data Analysis and Big Data applications in areas such as Finance, Banking and Insurance.

NobleProg Python training courses also cover beginning and advanced courses in the use of Python libraries and frameworks for Machine Learning and Deep Learning.

Python training is available as "onsite live training" or "remote live training". Onsite live Python trainings in Israel can be carried out locally on customer premises or in NobleProg corporate training centers. Remote live training is carried out by way of an interactive, remote desktop.

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Python Subcategories

Django Training CoursesDjango
Web2py Training CoursesWeb2py
PyQt Training CoursesPyQt
Kivy Training CoursesKivy

Python Course Outlines

Title
Duration
Overview
Title
Duration
Overview

Applied AI from Scratch in Python

28 hours
Overview
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.

Web Scraping with Python

7 hours
Overview
Web Scraping is a technique for extracting data from a website then saving it to local file or database.

This instructor-led, live training (onsite or remote) is aimed at developers who wish to use Python to automate the process of crawling many websites to extract data for processing and analysis.

By the end of this training, participants will be able to:

- Install and configure Python and all relevant packages.
- Retrieve and parse data stored across many different websites.
- Understand how websites work and how their HTML is structured.
- Construct spiders to crawl the web at scale.
- Use Selenium to crawl AJAX-driven web pages.

Format of the Course

- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.

Course Customization Options

- This course assumes knowledge of programming.
- To request a customized training for this course, please contact us to arrange.

Analyzing Big Financial Data with Python

35 hours
Overview
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

Computer Vision with Python

14 hours
Overview
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

Python for Excel

14 hours
Overview
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.

Python Programming for Finance

35 hours
Overview
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.

Python for Matlab Users

14 hours
Overview
The Python programming language is becoming more and more popular among Matlab users due to its power and versatility as a data analysis tool as well as a general purpose language.

This instructor-led, live training (onsite or remote) is aimed at Matlab users who wish to explore and or transition to Python for data analytics and visualization.

By the end of this training, participants will be able to:

- Install and configure a Python development environment.
- Understand the differences and similarities between Matlab and Python syntax.
- Use Python to obtain insights from various datasets.
- Convert existing Matlab applications to Python.
- Integrate Matlab and Python applications.

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.

Advanced Python

28 hours
Overview
In this instructor-led, live 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.

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.

Python Programming

28 hours
Overview
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.

Python: Machine Learning with Text

21 hours
Overview
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

Natural Language Processing with Deep Dive in Python and NLTK

35 hours
Overview
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.

Python for Advanced Machine Learning

21 hours
Overview
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.

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

Natural Language Processing with Python

28 hours
Overview
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.

Python Security

14 hours
Overview
This course introduces the student to the Python language. Upon completion of this class, the student will be able to write non trivial Python programs dealing with a wide variety of subject matter domains. Topics include language components, working with a professional IDE, control flow constructs, strings, I/O, collections, classes, modules, and regular expressions. The course is supplemented with many hands-on labs, solutions, and code examples.

After Completing the course students will be able to demonstrate knowledge and understanding of Python Security Principles.

Selenium with Python for Test Automation

14 hours
Overview
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 instructor-led, live 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.

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.

Natural Language Processing (NLP) with Python spaCy

14 hours
Overview
This instructor-led, live training (onsite or remote) is aimed at developers and data scientists who wish to use spaCy to process very large volumes of text to find patterns and gain insights.

By the end of this training, participants will be able to:

- Install and configure spaCy.
- Understand spaCy's approach to Natural Language Processing (NLP).
- Extract patterns and obtain business insights from large-scale data sources.
- Integrate the spaCy library with existing web and legacy applications.
- Deploy spaCy to live production environments to predict human behavior.
- Use spaCy to pre-process text for Deep Learning

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.
- To learn more about spaCy, please visit: https://spacy.io/

Python and Spark for Big Data (PySpark)

21 hours
Overview
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

Data Analysis with SQL, Python and Spotfire

14 hours
Overview
In this instructor-led, live training, participants will learn three different approaches for accessing, analyzing and visualizing data. We start with an introduction to RDMS databases; the focus will be on accessing and querying an Oracle database using the SQL language. Then we look at strategies for accessing an RDMS database programmatically using the Python language. Finally, we look at how to visualize and present data graphically using TIBCO Spotfire.

Format of the Course

- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.

Tableau with Python

14 hours
Overview
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

Text Summarization with Python

14 hours
Overview
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

Python: Automate the Boring Stuff

14 hours
Overview
This instructor-led, live 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.

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

Unit Testing with Python

21 hours
Overview
Unit Testing is a testing approach that tests individual units of source code by modifying their properties or triggering an event to confirm whether the outcome is as expected. PyTest is a full-featured, API-independent, flexible, and extensible testing framework with an advanced, full-bodied fixture model.

In this instructor-led, live training, participants will learn how to use PyTest to write short, maintainable tests that are elegant, expressive and readable.

By the end of this training, participants will be able to:

- Write readable and maintainable tests without the need for boilerplate code.
- Use the fixture model to write small tests.
- Scale tests up to complex functional testing for applications, packages, and libraries.
- Understand and apply PyTest features such as hooks, assert rewriting and plug-ins.
- Reduce test times by running tests in parallel and across multiple processors.
- Run tests in a continuous integration environment, together with other utilities such as tox, mock, coverage, unittest, doctest and Selenium.
- Use Python to test non-Python applications.

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

Building Chatbots in Python

21 hours
Overview
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.

Kivy: Building Android Apps with Python

7 hours
Overview
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.

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

Data Mining with Python

14 hours
Overview
This instructor-led, live training (onsite or remote) is aimed at data analysts and data scientists who wish to implement more advanced data analytics techniques for data mining using Python.

By the end of this training, participants will be able to:

- Understand important areas of data mining, including association rule mining, text sentiment analysis, automatic text summarization, and data anomaly detection.
- Compare and implement various strategies for solving real-world data mining problems.
- Understand and interpret the results.

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.

Data Analysis in Python using Pandas and Numpy

14 hours
Overview
Pandas is a Python package that provides data structures for working with structured (tabular, multidimensional, potentially heterogeneous) and time series data.

Web Development with Django

21 hours
Overview
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

Deep Learning for Banking (with Python)

28 hours
Overview
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

Deep Learning for Finance (with Python)

28 hours
Overview
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

Deep Learning for Telecom (with Python)

28 hours
Overview
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

Upcoming Python Courses

Data Analysis in Python using Pandas and Numpy

2019-07-15 09:30:00
Tel Aviv
Remote
3500EUR
 Classroom
4100EUR
Read more

Python: Automate the Boring Stuff

2019-07-23 09:30:00
Jerusalem
Remote
3000EUR
 Classroom
3600EUR
Read more

Data Analysis in Python using Pandas and Numpy

2019-07-31 09:30:00
Jerusalem
Remote
3500EUR
 Classroom
4100EUR
Read more

Selenium with Python for Test Automation

2019-07-31 09:30:00
Jerusalem
Remote
3000EUR
 Classroom
3600EUR
Read more

Machine Learning with Python

2019-08-06 09:30:00
Jerusalem
Remote
5250EUR
 Classroom
6050EUR
Read more

Other regions

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Other countries

These courses are also available in other countries ››

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Course Discounts

Blockchain: Hyperledger Iroha for Mobile Applications

Wed, 2019-07-24 09:30
Jerusalem
Remote
3500EUR
3150EUR
 Classroom
4100EUR
3750EUR
Read more

IoT security

Tue, 2019-10-08 09:30
Jerusalem
Remote
6000EUR
5400EUR
 Classroom
6800EUR
6200EUR
Read more

Systems Modelling with SysML

Tue, 2019-10-15 09:30
Jerusalem
Remote
5250EUR
4725EUR
 Classroom
6050EUR
5525EUR
Read more

Ethereum for Developers

Tue, 2019-10-15 09:30
Jerusalem
Remote
5250EUR
4725EUR
 Classroom
6050EUR
5525EUR
Read more

Comprehensive BPMN 2 - From Analysis to Execution

Mon, 2019-11-04 09:30
Tel Aviv
Remote
8750EUR
7875EUR
 Classroom
9950EUR
9075EUR
Read more

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