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 trainings in Canada can be carried out locally on customer premises or in NobleProg corporate training centers.
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 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
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 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
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
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
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 appreciated Folio's wide breadth of knowledge. Not only was he familiar with the course content, but he also knew of constructs in languages we were familiar with to make examples more meaningful to us. During intervals he shared his knowledge of technologies and solutions outside the training scope to provide insights into other solutions we could use in future (and future training).
Raphael Keymer - Markit Valuations Limited
Course: Developing Desktop Applications with Visual Studio 2012, VB.NET and SQL Server 2012
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
I generally enjoyed the practical examples.
Marika Agius
Course: Visual Basic for Applications (VBA) for Analysts
I liked the step by step and hands on realistic data examples.
CARL MIFSUD
Course: Visual Basic for Applications (VBA) for Analysts
I mostly liked the hands-on practice and exercises.
Godwin Spiteri
Course: Visual Basic for Applications (VBA) for Analysts
Tamil has an excellent way of explaining things. He speaks clearly and will take the time to explain things individually when necessary.
Theresa Fenech
Course: Visual Basic for Applications (VBA) for Analysts
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
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Programming Course Outlines in Canada
Course Name
Duration
Overview
Course Name
Duration
Overview
21 hours
Overview
Node.js is a platform for easily building fast, scalable network applications. Learn how to use the event-driven, non-blocking I/O model to build data-intensive real-time applications that run across distributed devices. We will explore the design choices that make Node.js unique, how this changes the way applications are built and how systems of applications work most effectively in this model. Learn how to create modular code that’s robust, expressive and clear. Understand when to use callbacks, event emitters and streams. Use streams to easily manipulate data that would be impossible to fit in application memory. Gain confidence in handling errors effectively to ensure runtime reliability. The course has extensive lab exercises to reinforce the concepts and techniques covered.
Objectives
On completion of this course, students will be able to:
- Clearly understand the platform design choices that led to Node.js choosing an event loop and what this means for applications built on that foundation.
- Understand the unique trade-offs present in event-driven programming.
- Create Node.js modules and express code modularity in an application.
- Understand the core flow control patterns in Node.js and know when it is appropriate to use callbacks, event emitters or streams.
- Create and manipulate buffers efficiently.
- Understand how to manage error state and know when a process should exit due to an error.
- Build network applications with Node.js.
Node.js is a platform for easily building fast, scalable network applications. Learn how to use the event-driven, non-blocking I/O model to build data-intensive real-time applications that run across distributed devices. We will explore the design choices that make Node.js unique, how this changes the way applications are built and how systems of applications work most effectively in this model. Learn how to create modular code that’s robust, expressive and clear. Understand when to use callbacks, event emitters and streams. Use streams to easily manipulate data that would be impossible to fit in application memory. Gain confidence in handling errors effectively to ensure runtime reliability. The course has extensive lab exercises to reinforce the concepts and techniques covered.
Objectives
On completion of this course, students will be able to:
- Clearly understand the platform design choices that led to Node.js choosing an event loop and what this means for applications built on that foundation.
- Understand the unique trade-offs present in event-driven programming.
- Create Node.js modules and express code modularity in an application.
- Understand the core flow control patterns in Node.js and know when it is appropriate to use callbacks, event emitters or streams.
- Create and manipulate buffers efficiently.
- Understand how to manage error state and know when a process should exit due to an error.
- Build network applications with Node.js.
28 hours
This course is designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python drives businesses and is used by scientists all over the world – it is one of the most popular programming languages.
The course can be delivered using the latest Python version 3.x with practical exercises making use of the full power. 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.
The course can be delivered using the latest Python version 3.x with practical exercises making use of the full power. 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.
14 hours
JavaScript is a programming language designed for manipulating a web page.
28 hours
In this instructor-led, live training in Canada, 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.
21 hours
In this instructor-led, live training in Canada, 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.
14 hours
This course is designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python drives businesses and is used by scientists all over the world – it is one of the most popular programming languages.
35 hours
The training course will help the participants prepare for Web Application Development using Python Programming with Data Analytics. Such data visualization is a great tool for Top Management in decision making.
14 hours
This instructor-led, live training in Canada (online or onsite) is aimed at data analysts who wish to use VBA in Excel for automating tasks.
By the end of this training, participants will be able to:
- Record and edit macros as required.
- Write procedures using data from the sheet.
- Create your own functions.
- Handle an event (opening worksheet cell update etc.) by means of the handler.
- Create a form.
By the end of this training, participants will be able to:
- Record and edit macros as required.
- Write procedures using data from the sheet.
- Create your own functions.
- Handle an event (opening worksheet cell update etc.) by means of the handler.
- Create a form.
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.
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
This instructor-led, live training in Canada 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.
21 hours
In this instructor-led, live training in Canada, 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.
14 hours
Pandas is a Python package that provides data structures for working with structured (tabular, multidimensional, potentially heterogeneous) and time series data.
21 hours
In this instructor-led, live training in Canada, 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.
14 hours
This instructor-led, live training in Canada (online or onsite) is aimed at data analysts who wish to build analytic applications using Python with Plotly and Dash.
By the end of this training, participants will be able to:
- Set up a real-time interactive dashboard for streaming live updating data.
- Build interactive dashboards using Python for data science solutions.
- Secure interactive dashboards with advanced authentication methods.
By the end of this training, participants will be able to:
- Set up a real-time interactive dashboard for streaming live updating data.
- Build interactive dashboards using Python for data science solutions.
- Secure interactive dashboards with advanced authentication methods.
28 hours
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.
28 hours
This instructor-led, live training in Canada (online or onsite) is aimed at developers who wish to containerize their Java EE 8 applications and run them as microservices in the cloud.
By the end of this training, participants will be able to:
- Build and deploy Java microservices in Docker containers.
- Manage Docker containers using Kubernetes.
- Integrate microservices with an existing monolithic system.
- Monitor, test, and secure microservices.
- Troubleshoot containers and orchestration environments.
By the end of this training, participants will be able to:
- Build and deploy Java microservices in Docker containers.
- Manage Docker containers using Kubernetes.
- Integrate microservices with an existing monolithic system.
- Monitor, test, and secure microservices.
- Troubleshoot containers and orchestration environments.
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.
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.
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.
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.
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.
35 hours
This is a 5 day introduction to Data Science and Artificial Intelligence (AI).
The course is delivered with examples and exercises using Python
The course is delivered with examples and exercises using Python
28 hours
This is a 4 day course introducing AI and it's application using the Python programming language. There is an option to have an additional day to undertake an AI project on completion of this course.
21 hours
Deep Reinforcement Learning refers to the ability of an "artificial agent" to learn by trial-and-error and rewards-and-punishments. An artificial agent aims to emulate a human's ability to obtain and construct knowledge on its own, directly from raw inputs such as vision. To realize reinforcement learning, deep learning and neural networks are used. Reinforcement learning is different from machine learning and does not rely on supervised and unsupervised learning approaches.
In this instructor-led, live training, participants will learn the fundamentals of Deep Reinforcement Learning as they step through the creation of a Deep Learning Agent.
By the end of this training, participants will be able to:
- Understand the key concepts behind Deep Reinforcement Learning and be able to distinguish it from Machine Learning
- Apply advanced Reinforcement Learning algorithms to solve real-world problems
- Build a Deep Learning Agent
Audience
- Developers
- Data Scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
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
14 hours
In this instructor-led, live training in Canada 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.
14 hours
In this instructor-led, live training in Canada (onsite or remote), 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.
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.
14 hours
In this instructor-led, live training in Canada, 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.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
7 hours
This instructor-led, live training in Canada 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.
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.
21 hours
This instructor-led, live training in Canada (online or onsite) is aimed at persons who wish to program a visually attractive software application using Python and the Qt UI framework.
By the end of this training, participants will be able to:
- Set up a development environment that includes all needed libraries, packages and frameworks.
- Create a desktop or server application whose user interface functions smoothly and is visually appealing.
- Implement various UI elements and effects, including widgets, charts, layers, etc. to achieve maximum effect in usability.
- Implement good UI design and code organization during the design and development phase.
- Test and debug the application.
By the end of this training, participants will be able to:
- Set up a development environment that includes all needed libraries, packages and frameworks.
- Create a desktop or server application whose user interface functions smoothly and is visually appealing.
- Implement various UI elements and effects, including widgets, charts, layers, etc. to achieve maximum effect in usability.
- Implement good UI design and code organization during the design and development phase.
- Test and debug the application.
14 hours
This instructor-led, live training in Canada (online or onsite) 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.
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.
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
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
28 hours
In this instructor-led, live training in Canada, 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.
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.
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Upcoming Programming Courses in Canada
Java Advanced - one day
10-02-2022 09:30
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21-02-2022 09:30
21 hours
Java Intermediate - one day
14-03-2022 09:30
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Standard Java Security
16-03-2022 09:30
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Java fundamentals with Maven
21-03-2022 09:30
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