Online or onsite, instructor-led live Computer Programming training courses demonstrate through interactive hands-on practice the fundamentals and advanced topics of Programming.
Programming training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Programming training can be carried out locally on customer premises in Egypt or in NobleProg corporate training centers in Egypt.
NobleProg -- Your Local Training Provider
Testimonials
The interaction and enthusiasm he had about the training.
Richard Burgos
Course: Design Patterns in PHP
The New content I learned.
Victor Cayetano
Course: Design Patterns in PHP
I mostly was benefit from the exercise.
Jason Wu
Course: Design Patterns in PHP
I like the support of the trainer and the topics. I came in with a mindset thinking this will be nothing new that I haven't done. But I was surprised of what all I have learned throughout this course. Thank you.
Jorgen Ordonez
Course: Design Patterns in PHP
I liked the examples and the way he explained.
Sandeep Parashar
Course: VBA For Access & Excel
The explanation way and including tips on the best practices in VBA/Access, encouraging via exercise to think more by ourselves on how to solve the problem rather than giving ready solutions.
Daria Rudin
Course: VBA For Access & Excel
Tamil was exceptionally patient and very helpful in figuring out solutions to real needs. He was also very honest about if he didn't know something from the top of his head, which enabled us to quickly jump on in the training and we didn't lose time.
Christine Weiler
Course: VBA For Access & Excel
It is good to have hands-on exercises after lectures.
bonnie lee
Course: AngularJS Good Practices
I liked the code examples and the elaboration.
Antony Ho
Course: AngularJS Good Practices
The trainer focused on each persons requirements for the course and tuned the material to suit our goals.
Daniel Watkins
Course: Visual Studio with VB.Net
I mostly liked the all the in code examples.
Course: Node.js for JavaScript Developers
The code exercises were good and engaging.
Course: Node.js for JavaScript Developers
I was benefit from the hands-on. Lots of help. Lots of space for asking questions and getting answers.
Abdul Zaheer
Course: Node.js for JavaScript Developers
I really liked creating the Connect middle ware.
Course: Node.js for JavaScript Developers
Examples were relate able.
Yongching Tee
Course: Node.js for JavaScript Developers
I felt it was the right mix of lecture and practical application.
David Jaggie
Course: Node.js for JavaScript Developers
I preferred the exercise and learning about the nooks and crannies of Python.
Connor Brierley-Green
Course: 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: Python Programming
Many examples made me easy to understand.
Lingmin Cao
Course: Python Programming
I like the Doctrine concept in Symphony taken by the trainer. The trainer is more energetic and make the sessions more interactive. I think it is a great capability of the trainer.
Kumaran Chandran
Course: Web Development with Symfony3
I liked the trainer's communication & knowledge in Symphony 3 and associated technologies. He had taken enough effort to teach and demonstrate with some examples in the respective topics. I can say my symphony knowledge and confidence level is gone up after this training.
Hari Kumar
Course: Web Development with Symfony3
Abhinav did an excellent job! Within four days he covered all the important concepts that are used in REAL software development. I am so thankful have him as our trainer!.
Vijay Joseph
Course: Web Development with Symfony3
I mostly enjoyed the exercises.
Anna Szumniak
Course: Visual Basic for Applications (VBA) in Excel - Introduction to programming
Training agenda was well thought out.
Przemek Zalasinski
Course: Visual Basic for Applications (VBA) in Excel - Introduction to programming
I genuinely enjoyed the short exercises.
Mateusz Podsiadlo
Course: Visual Basic for Applications (VBA) in Excel - Introduction to programming
Fact that customization was taken seriously.
jurgen linsen
Course: Python Programming
As I was the only participant the training could be adapted to my needs.
Kevin THIERRY
Course: Web Development with Web2Py
His very good knowledge and experience.
Jérémy Coppe
Course: Java Programming
Benchmarking GC
Marek Mrowca
Course: Java Performance Tuning
He's an experienced trainer with a real life experience in the topic he was teaching. That led the course to cover the most important topics which interests any developer working in the field, and small details would be easily overseen if he was not working in this platform. Moreover, he was giving the course using the latest versions of is and Swift (10 \ 3) and that is a huge advantage to be adapting such new technology in short time.
Abdullah Alaradi - Thiqah Business Services
Course: iPhone and iPad Development in Swift for iOS 8 and Xcode 6
I did like the exercises.
Office for National Statistics
Course: Natural Language Processing with Python
I genuinely liked the subject.
Eduardo Hernández
Course: AngularJS Basics
Content and the way it was provided.
Marcin Samborski
Course: Visual Basic for Applications (VBA) in Excel - Advanced
I liked how the trainer explained the subject. Providing real life example is beneficial.
Rhearose Holonowicz
Course: Java Programming
It was a compact and well delivered one.
Antonio Rojas
Course: IIS 8 and ASP.NET Administration
I mostly was benefit from lots of information.
Matthew Wise
Course: Apache Tomcat and Java EE Administration
I really enjoyed the numerous topics / covered spectrum.
Edward Fennen
Course: Apache Tomcat and Java EE Administration
I liked that there were many exercises, Re activity and flexibility of the Trainer.
Badii Bayoudh
Course: Java Spring
I liked that I had a chances to play with code during exercises (not only coding, what trainer prepared).
PITERION GmbH
Course: Java Spring
It was really nice of the trainer that he took a lot of time to answer our questions and helped us improve or gave us hints on how to improve some macros we were already using without fully understanding the code.
David Trieu - CD Projekt SA
Course: Visual Basic for Applications (VBA) in Excel - Introduction to programming
Trainer knowledge about the matter. Exercises done along the training. Trainer was absolutely friendly and approachable.
Jorge Peinado Prado
Course: Apache Tomcat and Java EE Administration
The trainers deep understanding of the subject matter.
Andrew Gorham
Course: Apache Tomcat and Java EE Administration
It was interactive. We got to code as we went.
Barnaby Dellar
Course: Ext JS Fundamentals
Tailored specifically to my needs and lots of Rural examples.
Catherine Redfern
Course: Developing Websites with PHP
I generally was benefit from the hands-on training.
Robert Badeloe
Course: IIS 7 and ASP.NET Administration
I was benefit from the materials, labs and extensive knowledge shown by the trainer.
Richard Hennessy
Course: Apache Tomcat and Java EE Administration
The trainer was very knowledgeable and was great answering questions :).
Gareth Jenkins
Course: AngularJS Basics
I generally liked the serialization in one line.
Tomasz Kawecki
Course: Programming in C#
I liked the advanced subjects about object orientation.
Jorge Romero
Course: Programming in C#
I like how the course was structured and presented in a basic to advance style.
Kolapo Abolarinwa
Course: React: Build highly-interactive web applications
I mostly liked the all the in code examples.
Course: Node.js for JavaScript Developers
The code exercises were good and engaging.
Course: Node.js for JavaScript Developers
I really liked creating the Connect middle ware.
Course: Node.js for JavaScript Developers
Programming Course Outlines in Egypt
Course Name
Duration
Overview
Course Name
Duration
Overview
28 hours
Overview
In this instructor-led, live training in Egypt (online or onsite), participants will learn how to create, test and deploy an Angular application using the latest features in Angular 10.
By the end of this training, participants will be able to:
- Develop Angular 10 applications using TypeScript and the Angular CLI.
- Create loosely coupled web components that can be used in any HTML page.
- Connect these components to services, modules and directives.
- Consume REST web services and WebSocket data from within an Angular 10 application.
- Build custom validation using Reactive Forms.
- Test, debug and deploy an Angular 10 application.
- Organize Angular 10 projects using best practices.
By the end of this training, participants will be able to:
- Develop Angular 10 applications using TypeScript and the Angular CLI.
- Create loosely coupled web components that can be used in any HTML page.
- Connect these components to services, modules and directives.
- Consume REST web services and WebSocket data from within an Angular 10 application.
- Build custom validation using Reactive Forms.
- Test, debug and deploy an Angular 10 application.
- Organize Angular 10 projects using best practices.
28 hours
Overview
In this instructor-led, live training in Egypt (online or onsite), participants will learn how to create, test and deploy an Angular application using the latest features in Angular 9.
By the end of this training, participants will be able to:
- Develop Angular 9 applications using TypeScript and the Angular CLI.
- Create loosely coupled web components that can be used in any HTML page.
- Connect these components to services, modules and directives.
- Consume REST web services and WebSocket data from within an Angular 9 application.
- Build custom validation using Reactive Forms.
- Reduce bundle sizes, eliminate dead code and improve the efficiency of Angular apps using the new Ivy compiler and runtime.
- Test, debug and deploy an Angular 9 application.
- Organize Angular 9 projects using best practices.
By the end of this training, participants will be able to:
- Develop Angular 9 applications using TypeScript and the Angular CLI.
- Create loosely coupled web components that can be used in any HTML page.
- Connect these components to services, modules and directives.
- Consume REST web services and WebSocket data from within an Angular 9 application.
- Build custom validation using Reactive Forms.
- Reduce bundle sizes, eliminate dead code and improve the efficiency of Angular apps using the new Ivy compiler and runtime.
- Test, debug and deploy an Angular 9 application.
- Organize Angular 9 projects using best practices.
21 hours
Overview
This instructor-led, live training in Egypt (online or onsite) is aimed at web developers who wish to use Angular 8 to develop client-side web applications.
By the end of this training, participants will be able to:
- Create and scale SPAs from scratch.
- Build open source Angular libraries.
- Secure an Agular application with JWT authentication.
By the end of this training, participants will be able to:
- Create and scale SPAs from scratch.
- Build open source Angular libraries.
- Secure an Agular application with JWT authentication.
28 hours
Overview
In this instructor-led, live training in Egypt (onsite or remote), participants will learn how to create, test and deploy an Angular application using the latest features in Angular 7.
By the end of this training, participants will be able to:
- Develop Angular 7 applications using Angular CLI.
- Create web components that can be used in any HTML page.
- Consume REST web services and WebSocket data from within an Angular 7 application.
- Implement animations using Angular 7's latest animation features.
- Test, debug and deploy an Angular 7 application.
- Organize Angular 7 projects using best practices.
By the end of this training, participants will be able to:
- Develop Angular 7 applications using Angular CLI.
- Create web components that can be used in any HTML page.
- Consume REST web services and WebSocket data from within an Angular 7 application.
- Implement animations using Angular 7's latest animation features.
- Test, debug and deploy an Angular 7 application.
- Organize Angular 7 projects using best practices.
14 hours
Overview
In this instructor-led, live training, participants will learn how to write and maintain tests for Angular applications.
By the end of this training, participants will be able to
- Decide the most appropriate strategy for testing an Angular application
- Carry out unit testing, component testing, A/B testing and end-to-end on an Angular application
- Choose the right tools for the job: Jasmine, Karma, Protractor, Mocha, etc.
- Write tests in Protractor and Jasmine
- Run and debug tests with Karma and Protractor
- Create a maintainable test suite
- Employ best practices for unit testing in Angular
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- Angular goes by different names and versions, namely: Angular.js, AngularJS, AngularJS 1, Angular 1, Angular 2, etc. To customize the version used in this training, please contact us to arrange.
By the end of this training, participants will be able to
- Decide the most appropriate strategy for testing an Angular application
- Carry out unit testing, component testing, A/B testing and end-to-end on an Angular application
- Choose the right tools for the job: Jasmine, Karma, Protractor, Mocha, etc.
- Write tests in Protractor and Jasmine
- Run and debug tests with Karma and Protractor
- Create a maintainable test suite
- Employ best practices for unit testing in Angular
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- Angular goes by different names and versions, namely: Angular.js, AngularJS, AngularJS 1, Angular 1, Angular 2, etc. To customize the version used in this training, please contact us to arrange.
14 hours
Overview
Reactive programing is an asynchronous programing paradigm that focuses on data streams and the propagation of data by establishing a defined dependency between the underlying execution models and the emitted data streams from one component to another. Many Angular application design inefficiencies when building asynchronous UIs can be overcome by utilizing reactive style patterns offered by the RxJS library.
In this instructor-led, live training, participants will learn how to implement Observable patterns into their Angular application designs as they step through a series of cases showcasing common angular design problems and how they benefit from reactive programing designs.
By the end of this training, participants will be able to:
- Understand the reactive programing paradigm and the RxJS library.
- Build UI heavy Angular applications with scalability, flexibility, and responsiveness in mind using reactive programming patterns.
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.
In this instructor-led, live training, participants will learn how to implement Observable patterns into their Angular application designs as they step through a series of cases showcasing common angular design problems and how they benefit from reactive programing designs.
By the end of this training, participants will be able to:
- Understand the reactive programing paradigm and the RxJS library.
- Build UI heavy Angular applications with scalability, flexibility, and responsiveness in mind using reactive programming patterns.
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.
21 hours
Overview
This instructor-led, live training in Egypt (online or onsite) is aimed at web developers who wish to create a hybrid mobile application with Ionic 4.
By the end of this training, participants will be able to:
- Integrate native device features into a hybrid mobile application.
- Use Angular and Ionic 4 to build a hybrid mobile application.
- Run a hybrid application on a mobile device emulator.
By the end of this training, participants will be able to:
- Integrate native device features into a hybrid mobile application.
- Use Angular and Ionic 4 to build a hybrid mobile application.
- Run a hybrid application on a mobile device emulator.
14 hours
Overview
The course answers questions:
How does the shell works?
How to write programs in a shell?
How does the shell works?
How to write programs in a shell?
21 hours
Overview
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
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
7 hours
Overview
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
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
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
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
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
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
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
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
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
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
21 hours
Overview
In this instructor-led, live training in Egypt, 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 cases.
- Use different tools and techniques for big data analysis using PySpark.
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 cases.
- Use different tools and techniques for big data analysis using PySpark.
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.
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.
14 hours
Overview
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
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
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
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
21 hours
Overview
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
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
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.
21 hours
Overview
In this instructor-led, live training in Egypt, 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.
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.
21 hours
Overview
Natural language generation (NLG) refers to the production of natural language text or speech by a computer.
In this instructor-led, live training, participants will learn how to use Python to produce high-quality natural language text by building their own NLG system from scratch. Case studies will also be examined and the relevant concepts will be applied to live lab projects for generating content.
By the end of this training, participants will be able to:
- Use NLG to automatically generate content for various industries, from journalism, to real estate, to weather and sports reporting
- Select and organize source content, plan sentences, and prepare a system for automatic generation of original content
- Understand the NLG pipeline and apply the right techniques at each stage
- Understand the architecture of a Natural Language Generation (NLG) system
- Implement the most suitable algorithms and models for analysis and ordering
- Pull data from publicly available data sources as well as curated databases to use as material for generated text
- Replace manual and laborious writing processes with computer-generated, automated content creation
Audience
- Developers
- Data scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn how to use Python to produce high-quality natural language text by building their own NLG system from scratch. Case studies will also be examined and the relevant concepts will be applied to live lab projects for generating content.
By the end of this training, participants will be able to:
- Use NLG to automatically generate content for various industries, from journalism, to real estate, to weather and sports reporting
- Select and organize source content, plan sentences, and prepare a system for automatic generation of original content
- Understand the NLG pipeline and apply the right techniques at each stage
- Understand the architecture of a Natural Language Generation (NLG) system
- Implement the most suitable algorithms and models for analysis and ordering
- Pull data from publicly available data sources as well as curated databases to use as material for generated text
- Replace manual and laborious writing processes with computer-generated, automated content creation
Audience
- Developers
- Data scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
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
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
21 hours
Overview
In this instructor-led, live training in Egypt, 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.
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.
21 hours
Overview
The aim of this course is to provide general 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.
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.
14 hours
Overview
This instructor-led, live training in Egypt 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.
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.
28 hours
Overview
In this instructor-led, live training in Egypt, 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.
14 hours
Overview
In this instructor-led, live training in Egypt 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.
21 hours
Overview
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.
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.
21 hours
Overview
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
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
Upcoming Programming Courses in Egypt
2021-07-12 09:30:00
Cairo - Le Méridien Heliopolis
21 hours
2021-07-20 09:30:00
Cairo - Le Méridien Heliopolis
21 hours
2021-08-23 09:30:00
Cairo - Le Méridien Heliopolis
28 hours
2021-08-31 09:30:00
Cairo - Le Méridien Heliopolis
28 hours
2021-08-31 09:30:00
Cairo - Le Méridien Heliopolis
28 hours
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Consulting in Egypt
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