Online or onsite, 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 "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Richmond Hill onsite live Python trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Richmond Hill - The Business Exchange
9225 Leslie Street, Richmond Hill, Canada, L4B 3H6
Place your business in the peaceful surroundings of Richmond Hill, home to leading global brands. Located in the northern suburbs, our The Business Exchange workspace is just a 30-minute drive from central Toronto and the International Airport.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at intermediate-level Python developers who wish to enhance their Python development experience using AWS Cloud9.
By the end of this training, participants will be able to:
Set up and configure AWS Cloud9 for Python development.
Understand the AWS Cloud9 IDE interface and features.
Write, debug, and deploy Python applications in AWS Cloud9.
Collaborate with other developers using the AWS Cloud9 platform.
Integrate AWS Cloud9 with other AWS services for advanced deployments.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at beginner-level developers and data analysts who wish to learn Python programming from scratch using Google Colab.
By the end of this training, participants will be able to:
Understand the basics of Python programming language.
Implement Python code in Google Colab environment.
Utilize control structures to manage the flow of a Python program.
Create functions to organize and reuse code effectively.
Explore and use basic libraries for Python programming.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at expert-level data analysts who wish to leverage Python's data analysis capabilities within Power BI, enhancing their ability to analyze and visualize data effectively.
By the end of this training, participants will be able to:
Learn how Python can be integrated into Power BI for data analysis.
Use Python scripts to load, clean, and preprocess data within the Power BI environment.
Enhance data visualization capabilities by creating custom and interactive visualizations using Python.
Acquire advanced data analysis skills using Python.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at experienced developers who wish to gain a comprehensive understanding of Python programming and its applications in cybersecurity.
By the end of this training, participants will be able to:
Use Python programming for defensive cybersecurity.
Understand and use Python for ethical offensive techniques and digital forensics tasks.
Recognize legal and ethical considerations surrounding offensive cybersecurity and vulnerability disclosure.
This instructor-led, live training in (online or onsite) is aimed at developers who wish to use the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications.
By the end of this training, participants will be able to:
Set up the necessary development environment that integrates FastAPI, React, and MongoDB.
Understand the key concepts, features, and benefits of the FARM stack.
Learn how to build REST APIs with FastAPI.
Learn how to design interactive applications with React.
Develop, test, and deploy applications (front end and back end) using the FARM stack.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at beginner-level to intermediate-level and potentially advanced-level robotics developers who wish to learn how to use ROS to program mobile robots using Python.
By the end of this training, participants will be able to:
Set up a development environment that includes ROS, Python, and a mobile robot platform.
Create and run ROS nodes, topics, services, and actions using Python.
Use ROS tools and utilities to monitor and debug ROS applications.
Use ROS packages and libraries to perform common tasks for mobile robots.
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.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at developers who wish to 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.
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 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.
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.
This instructor-led, live training in Richmond Hill 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.
In this instructor-led, live training in Richmond Hill, 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.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.
By the end of this training, participants will be able to:
Set up a development environment that includes Python, Pandas, and NumPy.
Create a data analysis application using Pandas and NumPy.
Perform advanced data wrangling, sorting, and filtering operations.
Conduct aggregate operations and analyze time series data.
Visualize data using Matplotlib and other visualization libraries.
In this instructor-led, live training in Richmond Hill, 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.
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.
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 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.
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.
In this instructor-led, live training in Richmond Hill 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.
In this instructor-led, live training in Richmond Hill (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.
This instructor-led, live training in Richmond Hill 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.
This instructor-led, live training in Richmond Hill (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.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at persons who wish to learn just enough Python to begin crunching numbers from sales data, traffic analytics, customer interactions, etc..
By the end of this training, participants will be able to:
Install and configure the necessary software, libraries and development environment to begin writing Python code for data analysis.
Analyze data from sources such as Excel, CSV, JSON files and databases.
Clean data to improve its usefulness before analyzing it.
Perform simple statistical analysis.
Generate reports that present the desired data in just the right format, from straight numbers to data visualizations.
Gain valuable insight from data, including trends in performance, problematic areas.
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
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
If you wish to add, remove or customize any section or topic within this course, please contact us to arrange.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at backend developers who wish to build REST APIs with Python and Flask.
By the end of this training, participants will be able to:
Implement a REST API to allow a Flask web application to read and write to a database in the backend.
Develop advanced authentication features like refresh tokens.
Build a reusable backend for future Python projects.
This instructor-led, live training in Richmond Hill (online or onsite) 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.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at data scientists and software engineers who wish to use Dask with the Python ecosystem to build, scale, and analyze large datasets.
By the end of this training, participants will be able to:
Set up the environment to start building big data processing with Dask and Python.
Explore the features, libraries, tools, and APIs available in Dask.
Understand how Dask accelerates parallel computing in Python.
Learn how to scale the Python ecosystem (Numpy, SciPy, and Pandas) using Dask.
Optimize the Dask environment to maintain high performance in handling large datasets.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.
By the end of this training, participants will be able to:
Employ algorithms to buy and sell securities at specialized increments rapidly.
Reduce costs associated with trade using algorithmic trading.
Automatically monitor stock prices and place trades.
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.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at intermediate-level developers who wish to use CUDA to build Python applications that run in parallel on NVIDIA GPUs.
By the end of this training, participants will be able to:
Use the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
Create, compile and launch custom CUDA kernels.
Manage GPU memory.
Convert a CPU based application into a GPU-accelerated application.
This instructor-led, live training (online or onsite) 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.
In this instructor-led, live training in Richmond Hill, participants will learn how to build a smart contract blockchain application with Monax.
By the end of this training, participants will be able to:
Develop and deploy a distributed application using blockchain and smart contract technology.
Understand design and functionality of 'smart contracts' and how to create one.
Implement best practices for secure blockchain application development.
Leverage Monax tools to streamline distributed application development.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs easier and faster.
By the end of this training, participants will be able to:
Set up the necessary development environment to develop APIs with Python and FastAPI.
Create APIs quicker and easier using the FastAPI library.
Learn how to create data models and schemas based on Pydantic and OpenAPI.
Connect APIs to a database using SQLAlchemy.
Implement security and authentication in APIs using the FastAPI tools.
Build container images and deploy web APIs to a cloud server.
This practical course is addressed to Python developers that want to create and maintain their first web applications. It is also addressed to people who are already familiar with other web frameworks such as Django or Web2py, and want to learn how using a microframework (i.e. a framework which glues together third-party libraries instead of providing a self-contained universal solution) changes the process.
A significant part of the course is devoted not to Flask itself (it's tiny), but to third-party libraries and tools often used in Flask projects.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at developers who wish to use the advanced features of Flask to build scalable web applications on top of MongoDB.
By the end of this training, participants will be able to:
Set up the necessary development environment to start developing web applications with Flask.
Get to know the advanced concepts and techniques for real-world Flask projects.
Build a RESTful API server on top of MongoDB.
Learn how to containerize, test, and deploy microservices with Flask, Docker, and Amazon EC2.
Gain some insights on the advanced Flask integrations for scaling web applications.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at data scientists who wish to use TensorFlow to analyze potential fraud data.
By the end of this training, participants will be able to:
Create a fraud detection model in Python and TensorFlow.
Build linear regressions and linear regression models to predict fraud.
Develop an end-to-end AI application for analyzing fraud data.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at network engineers who wish to maintain, manage, and design computer networks with Python.
By the end of this training, participants will be able to:
Optimize and leverage Paramiko, Netmiko, Napalm, Telnet, and pyntc for network automation with Python.
Master multi-threading and multiprocessing in network automation.
In this instructor-led, live training in Richmond Hill, 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.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at developers who wish to use PyGame to create and build games using Python programming.
By the end of this training, participants will be able to:
Set up the necessary development environment to start creating game applications with PyGame and Python.
Learn how to create interactive PyGame applications integrated with animations and multimedia features.
Run and test game programs with PyGame test suite and convert them into executable files.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at penetration testers who wish to penetrate test networks in Kali Linux using Python.
By the end of this training, participants will be able to:
Create Python programs to seek network vulnerabilities.
Explore and use Kali web shells and shellcode in exploits.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at developers who wish to use Python as the server-side language to create a web application. Various techniques and frameworks will be explored to arrive at the most suitable one for a given problem.
By the end of this training, participants will be able to:
Install and configure Python packages and frameworks.
Set up the appropriate development environment to optimize the coding process.
Write the code needed to enable common functionality expected by end users of an application (forms, database queries, calculations, etc.)
Select from a number of popular frameworks such as Django and Flask to automate redundant tasks and reduce development time.
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 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
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.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at developers who wish to use SciPy to create advanced scientific computing functions with Python.
By the end of this training, participants will be able to:
Set up the necessary development environment to start creating scientific computing functions.
Get the full benefit of SciPy features by performing practical examples of complex operations.
Implement and optimize mathematical algorithms and functions to solve scientific problems.
Design data structures and interpolation methods for visualization, processing, and analysis.
This instructor-led, live training (online or onsite) 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/
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
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.
This instructor-led, live training in Richmond Hill (online or onsite) is aimed at data scientists and developers who wish to use Modin to build and implement parallel computations with Pandas for faster data analysis.
By the end of this training, participants will be able to:
Set up the necessary environment to start developing Pandas workflows at scale with Modin.
Understand the features, architecture, and advantages of Modin.
Know the differences between Modin, Dask, and Ray.
Perform Pandas operations faster with Modin.
Implement the entire Pandas API and functions.
Read more...
Last Updated:
Testimonials (23)
The fact of having more practical exercises using more similar data to what we use in our projects (satellite images in raster format)
Matthieu - CS Group
Course - Scaling Data Analysis with Python and Dask
Very interactive with various examples, with a good progression in complexity between the start and the end of the training.
Jenny - Andheo
Course - GPU Programming with CUDA and Python
I thought the trainer was very knowledgeable and answered questions with confidence to clarify understanding.
Jenna - TCMT
Course - Machine Learning with Python – 2 Days
Very good preparation and expertise of a trainer, perfect communication in English. The course was practical (exercises + sharing examples of use cases)
Monika - Procter & Gamble Polska Sp. z o.o.
Course - Developing APIs with Python and FastAPI
It was a though course as we had to cover a lot in a short time frame.
Our trainer knew a lot about the subject and delivered the content to address our requirements.
It was lots of content to learn but our trainer was helpful and encouraging. He answered all our questions with good detail and we feel that we learned a lot.
Exercises were well prepared and tasks were tailored accordingly to our needs. I enjoyed this course
Bozena Stansfield - New College Durham
Course - Build REST APIs with Python and Flask
Exercises were nice
Vyshnavi Iyappan - Red Embedded Consulting Sp. z o.o.
Course - Unit Testing with Python
The explaination
Wei Yang Teo - Ministry of Defence, Singapore
Course - Machine Learning with Python – 4 Days
Very hands-on practice, engaging and good amount of breaks in between. Thus did not feel tired/lethargic.
Charles Lim - Ministry of Defence, Singapore
Course - Python for Data Analysis
Many different examples and topics has been covered, from basic investigation to login management and dynamic page management.
Daniele Tagliaferro - Creditsafe Italia Srl
Course - Web Scraping with Python
The trainer has deep knowledge about the subject and was able to answer all of our questions.
Lefteris Spatharakis - Sioufas & Associates Law Firm
Course - Django CMS for Developers
Trainer was very knowlegable and very open to feedback on what pace to go through the content and the topics we covered. I gained alot from the training and feel like I now have a good grasp of image manipulation and some techniques for building a good training set for an image classification problem.
Anthea King - WesCEF
Course - Computer Vision with Python
Trainer was accommodative. And actually quite encouraging for me to take up the course.
Grace Goh - DBS Bank Ltd
Course - Python in Data Science
Subject presentation knowledge timing
Aly Saleh - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)
Trainer develops training based on participant's pace
Farris Chua
Course - Data Analysis in Python using Pandas and Numpy
The trainer was a professional in the subject field and related theory with application excellently
Fahad Malalla - Tatweer Petroleum
Course - Applied AI from Scratch in Python
The trainer was great! If he would have more time I think we could have learned a lot more.
Zarim Jei Serrano - Cloudstaff Philippines, Inc.
Course - Python Programming Fundamentals
1:1 very intensive but learnt a lot.
Karen Dyke - BT
Course - Python: Automate the Boring Stuff
The trainer was excellent, He was always ready to answer my questions and share as much knowledge as he could.
Fahad Malalla - Tatweer Petroleum
Course - Advanced Python
I mostly enjoyed everything.
Thukten Dendup - Bhutan Telecom
Course - Web Development with Django
In-depth coverage of machine learning topics, particularly neural networks. Demystified a lot of the topic.
Sacha Nandlall
Course - Python for Advanced Machine Learning
I did like the exercises.
Office for National Statistics
Course - Natural Language Processing with Python
As I was the only participant the training could be adapted to my needs.
Kevin THIERRY
Course - Web Development with Web2Py
I preferred the exercise and learning about the nooks and crannies of Python.
Online Python training in Richmond Hill, Python training courses in Richmond Hill, Weekend Python courses in Richmond Hill, Evening Python training in Richmond Hill, Python instructor-led in Richmond Hill, Python instructor in Richmond Hill, Python coaching in Richmond Hill, Python on-site in Richmond Hill, Python boot camp in Richmond Hill, Python trainer in Richmond Hill, Python classes in Richmond Hill, Evening Python courses in Richmond Hill, Online Python training in Richmond Hill, Python private courses in Richmond Hill, Python one on one training in Richmond Hill, Python instructor-led in Richmond Hill, Weekend Python training in Richmond Hill
