
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. Onsite live Python trainings in Israel can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Testimonials
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
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
I did like the exercises.
Office for National Statistics
Course: Natural Language Processing with Python
I liked the helpful and very kind.
Natalia Machrowicz
Course: Python Programming
We did practical exercises (the scripts we wrote can be used in our everyday work). It made the course very interesting. I also liked the way the trainer shared his knowledge. He did it in a very accessible way.
Malwina Sawa
Course: Python Programming
Very good approach to memorize/repeat the key topics. Very nice “warm-up” exercises.
Course: Python Programming
* Enjoyable exercises. * Quickly moved into more advanced topics. * Trainer was friendly and easy to get on with. * Customized course for needs of team.
Matthew Lucas
Course: Python Programming
I enjoyed the felixibility to add specific topics into the course / lessons.
Marc Ammann
Course: Python Programming
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 liked the customized, in-house file processing and data analysis.
Glycom A/S
Course: Data Analysis in Python using Pandas and Numpy
The case studies helped us understand how we can apply Python in the industry. Really appreciated the trainer's help during the exercises.
Rajiv Dhingra - TCS
Course: Python Programming
As we are PHP developers, he understood the situation and allowed us to slowly map things between. I liked the examples and the humor he added.
Soumya Tyagi - TCS
Course: Python Programming
I enjoyed the that we have used our own data as examples.
Glycom A/S
Course: Data Analysis in Python using Pandas and Numpy
the training is not presentation styled. We were coding with he trainer.
Bhutan Telecom
Course: Web Development with Django
I mostly enjoyed everything.
Thukten Dendup - Bhutan Telecom
Course: Web Development with Django
Its a new experience, a new framework and looking forward to do something using the lesson learnt in the classes.
Jigme - Bhutan Telecom
Course: Web Development with Django
I genuinely enjoyed the lots of labs and practices.
Vivian Feng - Destination Canada
Course: Data Analysis with SQL, Python and Spotfire
The exercises/labs were tailored to our own organizational needs.
Destination Canada
Course: Data Analysis with SQL, Python and Spotfire
I generally liked the subject matter.
Destination Canada
Course: Data Analysis with SQL, Python and Spotfire
The trainer was sharing real word experiences, it's nice to learn from real professional.
Fednot
Course: Python Programming
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
1:1 very intensive but learnt a lot.
Karen Dyke - BT
Course: Python: Automate the Boring Stuff
I mostly enjoyed the subject.
Proximus
Course: Python Programming
The way the exercises were organized : all on own tempo and Antonio there to help you further.
Proximus
Course: Python Programming
I liked the sufficient and very detailed reading materials and examples (slides).
HC Consumer Finance Philippines, Inc.
Course: Python Programming
I genuinely liked the na.
HC Consumer Finance Philippines, Inc.
Course: Python Programming
What I like the most about the training is that everything in the course outline is something that will be useful for our projects.
Joanna Marie Escueta - Aarki, Inc.
Course: Python Programming
The overview/the recommendations
frddy de meersman - Proximus
Course: Python Programming
Labs
Proximus
Course: Python Programming
The informal exchanges we had during the lectures really helped me deepen my understanding of the subject
Explore
Course: Deep Reinforcement Learning with Python
practice tasks
Pawel Kozikowski - GE Medical Systems Polska Sp. Zoo
Course: Python and Spark for Big Data (PySpark)
Recap of previous day, trainer very knowledgable in answering questions
Mateusz Jaros - GE Medical Systems Polska Sp. Zoo
Course: Python Programming
It gave me a broad overview of the possibilites
GE Medical Systems Polska Sp. Zoo
Course: Python Programming
really kind, good approach to trainees, helpful
GE Medical Systems Polska Sp. Zoo
Course: Python Programming
I like pace of the training. It was good and we were able to cover many aspects of programming language. Trainer was able to show many applications of Python in very informative way. Trainer sent to us many scripts and micro-programs for furher reference which is very useful. I like, that we started training with some technical remarks and setting up virtual environment.
Bartosz Rosiek - GE Medical Systems Polska Sp. Zoo
Course: Python Programming
I thought John was very knowledgeable and able to diseminate information in a very understandable way.
Crux Product Design
Course: Python Programming Fundamentals
John was a very friendly and knowledgeable trainer and was keen to adapt the course to our requests.
Crux Product Design
Course: Python Programming Fundamentals
Gaining a better understanding of object oriented programming as this is a key difference to programming in Matlab (which I am much more familiar with). The training should hopefully be very useful!
Crux Product Design
Course: Python Programming Fundamentals
knew his subject well
Albert JACOB - Proximus
Course: Python Programming
The exercises combined with the experienced help of the trainer
Proximus
Course: Python Programming
The fact that we could practice a lot. Even though for me being a newbe the pace was to fast and explanation too few. However, probably due to the mixed knowkedge level of the students attending the class.
Proximus
Course: Python Programming
Trainer obviously had a great holistic understanding of programming.
Crux Product Design
Course: Python Programming Fundamentals
the last day. generation part
Accenture Inc
Course: Python for Natural Language Generation
The topics referring to NLG. The team was able to learn something new in the end with topics that were interesting but it was only in the last day. There were also more hands on activities than slides which was good.
Accenture Inc
Course: Python for Natural Language Generation
I enjoyed the sentinal analysis/ data science aspect of the course.
Jake Hamilton - Scottish Government
Course: Python Programming
pace and explanations
Centric IT Solutions Lithuania
Course: Advanced Python
I like that it focuses more on the how-to of the different text summarization methods
Course: Text Summarization with Python
Very good approach to memorize/repeat the key topics. Very nice “warm-up” exercises.
Course: Python Programming
I like that it focuses more on the how-to of the different text summarization methods
Course: Text Summarization with Python
Python Course Outlines in Israel
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 is delivered with examples and exercises using Python
By the end of this training, participants will be able to:
- Plan, build, and deploy machine learning models in KNIME.
- Make data driven decisions for operations.
- Implement end to end data science projects.
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.
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.
- Use GNS3 and Python for network programming.
By the end of this training, participants will be able to:
- Build GIS applications using Python and ArcGIS tools.
- Develop with the ArcGIS package ArcPy, using Python.
- Apply the ArcGIS modules for map automation using object classes in Python.
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:
- Apply deep learning with supervised or unsupervised learning methods.
- Develop, train, and implement concurrent neural networks and recurrent neural networks.
- Use Keras and Python to build deep learning models to solve problems involving images, text, sound, and more.
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.
- Apply various Kali tools for penetration testing.
- Exploit systems with Python.
By the end of this training, participants will be able to:
- Identify whether data is an anomaly or is an expected value.
- Implement algorithms for anomaly detection.
- Use various techniques and methods to detect anomalies.
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.
- Simplify storage of data with SQLAlchemy.
- Deploy REST APIs onto a cloud based server.
By the end of this training, participants will be able to:
- Create a self documenting REST API.
- Deploy REST APIs onto a cloud based server.
- Implement APIs for application authentication.
- Build a reusable backend for future Python projects.
By the end of this training, participants will be able to:
- Use geography managers to lay out the GUI.
- Organize widgets inside of frames.
- Build a GUI application with Python Tkinter.
After Completing the course students will be able to demonstrate knowledge and understanding of Python Security Principles.
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:
- Install and configure Python and all relevant packages.
- Retrieve and parse data stored across many different websites.
- Understand how websites work and how their HTML is structured.
- Construct spiders to crawl the web at scale.
- Use Selenium to crawl AJAX-driven web pages.
By the end of this training, participants will be able to:
- View, load, and classify images and videos using OpenCV 4.
- Implement deep learning in OpenCV 4 with TensorFlow and Keras.
- Run deep learning models and generate impactful reports from images and videos.
By the end of this training, participants will be able to:
- Implement parallel programming techniques for performance improvements.
- Synchronize threads and use multi-threading.
- Execute distributed computational tasks.
- Use parallel processing solutions for web applications.
The course is designed and aimed for people without computer science background who want to learn to program.
This course is suited for:
- Researchers dealing with biological data.
- Scientists who would like to learn how to automate everyday tasks and analyse data.
- Managers who want to learn how programming improves workflows and conducting projects.
By the end of the course, participants will be able to write short programs, which will allow them to manipulate, analyse and deal with biological data and present results in a graphical format.
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.
By the end of this training, participants will be able to use Apache Kafka to monitor and manage conditions in continuous data streams using Python programming.
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.
Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks.
Python is a high-level programming language famous for its clear syntax and code readability.
In this instructor-led, live training, participants will learn how to implement deep learning models for telecom using Python as they step through the creation of a deep learning credit risk model.
By the end of this training, participants will be able to:
- Understand the fundamental concepts of deep learning.
- Learn the applications and uses of deep learning in telecom.
- Use Python, Keras, and TensorFlow to create deep learning models for telecom.
- Build their own deep learning customer churn prediction model using Python.
Format of the Course
- 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.
By the end of this training, participants will be able to:
- Set up the necessary development environment to start developing.
- Create and customize pages, menus, and forms to give personality to a website.
- Test, debug, optimize and deploy a fully functional website.
- Optimize websites for SEO.
By the end of this training, participants will be able to:
- Set up the necessary development environment to start developing.
- Create custom page templates and plugins.
- Linking functionality from another application with a DJango system.
- Integrate an entire Django web application with a Django CMS website.
By the end of this training, participants will be able to:
- Install and configure a production-grade Django CMS website.
- Define user roles and permissions.
- Configure database and perform maintenance operations.
- Secure, monitor, optimize, and troubleshoot a live Django CMS system.
- Peform administration tasks, including backup, restore and site migration.
- Launch multisite instances of Django CMS on-premise or to a public cloud.
- Integrate a Django CMS with third-party applications and systems.
By the end of this training, participants will be able to:
- Setup, configure and manage RabbitMQ.
- Understand RabbitMQ's role in the design and implementation of a microservice's architecture.
- Understand how RabbitMQ compares to other Message Queuing Architectures.
- Set up and use RabbitMQ as a broker for handling asynchronous and synchronous messages for real-world Python applications.
By the end of this training, participants will be able to:
- Install and configure Gunicorn.
- Understand the building blocks for deploying a Python web application
- Explain Gunicorn's role and how it compares to Java's Servlet API.
- Integrate Gunicorn with a variety of Python web frameworks.