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

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

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

NobleProg -- Your Local Training Provider

Testimonials

★★★★★

I liked everything from the preparation and presentation to trainer interaction.

Fahad Malalla - Tatweer Petroleum

Course: Python Programming

What did you like the most about the training?: I liked the fact that we were all the time busy programming, so I had to focus the whole time.

Katarzyna Hutnik - University of Oxford, Department of Oncology

Course: Programming for Biologists

What did you like the most about the training?: I think the trainer was brilliant. A fully qualified teacher with training experience.

Enric Domingo - University of Oxford, Department of Oncology

Course: Programming for Biologists

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 really liked everything!.

UBS Business Solutions Poland Sp. z o.o.

Course: Python Programming

I generally liked the personalized help.

UBS Business Solutions Poland Sp. z o.o.

Course: Python Programming

Everything was fine!.

UBS Business Solutions Poland Sp. z o.o.

Course: Python Programming

It was good to talk about it with someone (I did on-line courses before).

UBS Business Solutions Poland Sp. z o.o.

Course: Python Programming

Expertise of the teacher, his ability to solve ad-hoc problems given by the participants. A well prepared the scope of the syllabus.

UBS Business Solutions Poland Sp. z o.o.

Course: Python Programming

Training in a small group is ideal as more focus can be put on items of specific interest.

HSCIC

Course: Unit Testing with Python

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

All like it

蒙李

Course: Machine Learning Fundamentals with Python

Translated by

the trainer looked at and helped each person individually

Szymon Wolny

Course: Python Programming

Translated by

A set of exercises ideally suited to the subject. Exercises easy and "with a star"

Motorola Solutions Systems Polska Sp. z o.o

Course: Python Programming

Translated by

Good balance theory / exercises, adjusting the level of lectures to listeners less and more experienced, a very big plus for using Jupiter Notebook and showing the theory in practice. I also liked to collect anonymous feedback after the first part of the training the next day everything was prepared according to our suggestions and even though it was already very good, it was even better later :)

Motorola Solutions Systems Polska Sp. z o.o

Course: Python Programming

Translated by

commitment of the teacher, preparation, approach to listeners, willingness to explain all ambiguities

Małgorzata Konior

Course: Python Programming

Translated by

That the leader approaches everyone, even when he does not call for help and checks the level of the exercise.

Agnieszka Bielak

Course: Python Programming

Translated by

The trainer presented a very short theories about a given issue and we immediately went to practice. A nice way of hanging out cards, which gives the trainer information about how much time he has to spend on a given task, and who else has problems with the solution.

Motorola Solutions Systems Polska Sp. z o.o

Course: Python Programming

Translated by

That even if someone did not ask for it, but you could see that he was not moving forward with the task, Krzysztof came up and was able to advise skilfully

Motorola Solutions Systems Polska Sp. z o.o

Course: Python Programming

Translated by

The way of conducting, the exercises, all in all it all liked, I'm very happy that I came to such a trainer

Maksym Kolodiy

Course: Python Programming

Translated by

Real examples of exercises

Motorola Solutions Systems Polska Sp. z o.o

Course: Python Programming

Translated by

Availability of training materials (Jupyter), created on an ongoing basis updating the notebook depending on the questions that fell during the course. Dispelling doubts, answers to all questions.

Motorola Solutions Systems Polska Sp. z o.o

Course: Python Programming

Translated by

Accessibility and an interesting way of delivering teaching materials.

Motorola Solutions Systems Polska Sp. z o.o

Course: Python Programming

Translated by

Work on xlsx and csv files

Łukasz Olczyk

Course: Python: Automate the Boring Stuff

Translated by

All

MTU Aero Engines Polska Sp. z o. o.

Course: Python Programming

Translated by

Interesting issues

MTU Aero Engines Polska Sp. z o. o.

Course: Python Programming

Translated by

Variety of prepared issues and examples

MTU Aero Engines Polska Sp. z o. o.

Course: Python Programming

Translated by

emphasis on examples with encoding "on the projector" is definitely on + for Tom.

ADVA OPTICAL NETWORKING SP. ZO O.

Course: Advanced Python

Translated by

Very good approach to memorize/repeat the key topics. Very nice “warm-up” exercises.

Course: Python Programming

Python Subcategories

Python Course Outlines

Title

Duration

Overview

Title

Duration

Overview

Applied AI from Scratch in Python

28 hours

Overview

This is a 4 day course introducing AI and it's application using the Python programming language. There is an option to have an additional day to undertake an AI project on completion of this course.

Python: Machine Learning with Text

21 hours

Overview

In this instructor-led, live training, participants will learn how to use the right machine learning and NLP (Natural Language Processing) techniques to extract value from text-based data.

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

- Solve text-based data science problems with high-quality, reusable code
- Apply different aspects of scikit-learn (classification, clustering, regression, dimensionality reduction) to solve problems
- Build effective machine learning models using text-based data
- Create a dataset and extract features from unstructured text
- Visualize data with Matplotlib
- Build and evaluate models to gain insight
- Troubleshoot text encoding errors

Audience

- Developers
- Data Scientists

Format of the course

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

Python: Automate the Boring Stuff

14 hours

Overview

This instructor-led, live training is based on the popular book, "Automate the Boring Stuff with Python", by Al Sweigart. It is aimed at beginners and covers essential Python programming concepts through practical, hands-on exercises and discussions. The focus is on learning to write code to dramatically increase office productivity.

By the end of this training, participants will know how to program in Python and apply this new skill for:

- Automating tasks by writing simple Python programs.
- Writing programs that can do text pattern recognition with "regular expressions".
- Programmatically generating and updating Excel spreadsheets.
- Parsing PDFs and Word documents.
- Crawling web sites and pulling information from online sources.
- Writing programs that send out email notifications.
- Use Python's debugging tools to quickly resolve bugs.
- Programmatically controlling the mouse and keyboard to click and type for you.

Format of the course

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

Analyzing Big Financial Data with Python

35 hours

Overview

Python is a high-level programming language famous for its clear syntax and code readibility.

In this instructor-led, live training, participants will learn how to use Python for quantitative finance.

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

- Understand the fundamentals of Python programming
- Use Python for financial applications including implementing mathematical techniques, stochastics, and statistics
- Implement financial algorithms using performance Python

Audience

- Developers
- Quantitative analysts

Format of the course

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

Computer Vision with Python

14 hours

Overview

Computer Vision is a field that involves automatically extracting, analyzing, and understanding useful information from digital media. Python is a high-level programming language famous for its clear syntax and code readibility.

In this instructor-led, live training, participants will learn the basics of Computer Vision as they step through the creation of set of simple Computer Vision application using Python.

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

- Understand the basics of Computer Vision
- Use Python to implement Computer Vision tasks
- Build their own face, object, and motion detection systems

Audience

- Python programmers interested in Computer Vision

Format of the course

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

Python for Excel

14 hours

Overview

Python is a high-level programming language famous for its clear syntax and code readability. Excel is a spreadsheet application developed by Microsoft which is widely used in many industries. Adding Python to Excel makes it a powerful tool for data analytics.

In this instructor-led, live training, participants will learn how to combine the capabilities of Python and Excel.

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

- Install and configure packages for integrating Python and Excel
- Read, write, and manipulate Excel files using Python
- Call Python functions from Excel

Audience

- Developers
- Programmers

Format of the course

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

Note

- To request a customized training for this course, please contact us to arrange.

Python Programming for Finance

35 hours

Overview

Python is a programming language that has gained huge popularity in the financial industry. Adopted by the largest investment banks and hedge funds, it is being used to build a wide range of financial applications ranging from core trading programs to risk management systems.

In this instructor-led, live training, participants will learn how to use Python to develop practical applications for solving a number of specific finance related problems.

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

- Understand the fundamentals of the Python programming language
- Download, install and maintain the best development tools for creating financial applications in Python
- Select and utilize the most suitable Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
- Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
- Troubleshoot, integrate, deploy, and optimize a Python application

Audience

- Developers
- Analysts
- Quants

Format of the course

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

Note

- This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.

Python for Matlab Users

14 hours

Overview

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

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

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

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

Format of the Course

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

Course Customization Options

- To request a customized training for this course, please contact us to arrange.

Advanced Python

28 hours

Overview

In this instructor-led, live training, participants will learn advanced Python programming techniques, including how to apply this versatile language to solve problems in areas such as distributed applications, data analysis and visualization, UI programming and maintenance scripting.

Format of the course

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

Notes

- If you wish to add, remove or customize any section or topic within this course, please contact us to arrange.

Python Programming

28 hours

Overview

This course is designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python drives businesses and is used by scientists all over the world – it is one of the most popular programming languages.

The course can be delivered using Python 2.7.x or 3.x, with practical exercises making use of the full power of both versions of the language. This course can be delivered on any operating system (all flavours of UNIX, including Linux and Mac OS X, as well as Microsoft Windows).

The practical exercises constitute about 70% of the course time, and around 30% are demonstrations and presentations. Discussions and questions can be asked throughout the course.

Note: the training can be tailored to specific needs upon prior request ahead of the proposed course date.

Web Scraping with Python

7 hours

Overview

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

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

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

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

Format of the Course

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

Course Customization Options

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

Unit Testing with Python

21 hours

Overview

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

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

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

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

Format of the course

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

Natural Language Processing with Deep Dive in Python and NLTK

35 hours

Overview

By the end of the training the delegates are expected to be sufficiently equipped with the essential python concepts and should be able to sufficiently use NLTK to implement most of the NLP and ML based operations. The training is aimed at giving not just an executional knowledge but also the logical and operational knowledge of the technology therein.

Natural Language Processing with Python

28 hours

Overview

This course introduces linguists or programmers to NLP in Python. During this course we will mostly use nltk.org (Natural Language Tool Kit), but also we will use other libraries relevant and useful for NLP. At the moment we can conduct this course in Python 2.x or Python 3.x. Examples are in English or Mandarin (普通话). Other languages can be also made available if agreed before booking.

Selenium with Python for Test Automation

14 hours

Overview

Selenium is an open source library for automating web application testing across multiple browsers. Selenium interacts with a browser as people do: by clicking links, filling out forms and validating text. It is the most popular tool for web application test automation. Selenium is built on the WebDriver framework and has excellent bindings for numerous scripting languages, including Python.

In this training participants combine the power of Python with Selenium to automate the testing of a sample web application. By combining theory with practice in a live lab environment, participants will gain the knowledge and practice needed to automate their own web testing projects using Python and Selenium.

Audience

- Testers and Developers

Format of the course

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

Natural Language Processing (NLP) with Python spaCy

14 hours

Overview

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

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

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

Format of the Course

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

Course Customization Options

- To request a customized training for this course, please contact us to arrange.
- To learn more about spaCy, please visit: https://spacy.io/

Python and Spark for Big Data (PySpark)

21 hours

Overview

Python is a high-level programming language famous for its clear syntax and code readibility. Spark is a data processing engine used in querying, analyzing, and transforming big data. PySpark allows users to interface Spark with Python.

In this instructor-led, live training, participants will learn how to use Python and Spark together to analyze big data as they work on hands-on exercises.

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

- Learn how to use Spark with Python to analyze Big Data.
- Work on exercises that mimic real world circumstances.
- Use different tools and techniques for big data analysis using PySpark.

Format of the course

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

Data Analysis with SQL, Python and Spotfire

14 hours

Overview

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

Format of the Course

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

Tableau with Python

14 hours

Overview

Tableau is a business intelligence and data visualization tool. Python is a widely used programming language which provides support for a wide variety of statistical and machine learning techniques. Tableau's data visualization power and Python's machine learning capabilities, when combined, help developers rapidly build advanced data analytics applications for various business use cases.

In this instructor-led, live training, participants will learn how to combine Tableau and Python to carry out advanced analytics. Integration of Tableau and Python will be done via the TabPy API.

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

- Integrate Tableau and Python using TabPy API
- Use the integration of Tableau and Python to analyze complex business scenarios with few lines of Python code

Audience

- Developers
- Data scientists

Format of the course

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

Text Summarization with Python

14 hours

Overview

In Python Machine Learning, the Text Summarization feature is able to read the input text and produce a text summary. This capability is available from the command-line or as a Python API/Library. One exciting application is the rapid creation of executive summaries; this is particularly useful for organizations that need to review large bodies of text data before generating reports and presentations.

In this instructor-led, live training, participants will learn to use Python to create a simple application that auto-generates a summary of input text.

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

- Use a command-line tool that summarizes text.
- Design and create Text Summarization code using Python libraries.
- Evaluate three Python summarization libraries: sumy 0.7.0, pysummarization 1.0.4, readless 1.0.17

Audience

- Developers
- Data Scientists

Format of the course

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

Python for Advanced Machine Learning

21 hours

Overview

In this instructor-led, live training, participants will learn the most relevant and cutting-edge machine learning techniques in Python as they build a series of demo applications involving image, music, text, and financial data.

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

- Implement machine learning algorithms and techniques for solving complex problems.
- Apply deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
- Push Python algorithms to their maximum potential.
- Use libraries and packages such as NumPy and Theano.

Format of the course

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

Developing GUI Python Applications with PyQt

21 hours

Overview

PyQt is a cross-platform library for developing GUIs (graphical user interfaces) for Python applications. It interfaces Python with the Qt GUI toolkit.

This instructor-led, live training (onsite or remote) 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.

Format of the course

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

Course Customization Options

- This course can be offered for development on Windows, Linux and Mac OS.
- The latest version of all software is used, e.g., PyQt 5 as of this writing, etc.
- To request a customized training for this course, please contact us to arrange.

Building Chatbots in Python

21 hours

Overview

ChatBots are computer programs that automatically simulate human responses via chat interfaces. ChatBots help organizations maximize their operations efficiency by providing easier and faster options for their user interactions.

In this instructor-led, live training, participants will learn how to build chatbots in Python.

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

- Understand the fundamentals of building chatbots
- Build, test, deploy, and troubleshoot various chatbots using Python

Audience

- Developers

Format of the course

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

Note

- To request a customized training for this course, please contact us to arrange.

Kivy: Building Android Apps with Python

7 hours

Overview

Kivy is an open-source cross-platform graphical user interface library written in Python, which allows multi-touch application development for a wide selection of devices.

In this instructor-led, live training participants will learn how to install and deploy Kivy on different platforms, customize and manipulate widgets, schedule, trigger and respond to events, modify graphics with multi-touching, resize the screen, package apps for Android, and more.

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

- Relate the Python code and the Kivy language
- Have a solid understanding of how Kivy works and makes use of its most important elements such as, widgets, events, properties, graphics, etc.
- Seamlessly develop and deploy Android apps based on different business and design requirements

Audience

- Programmers or developers with Python knowledge who want to develop multi-touch Android apps using the Kivy framework
- Android developers with Python knowledge

Format of the course

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

Data Mining with Python

14 hours

Overview

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

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

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

Format of the Course

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

Course Customization Options

- To request a customized training for this course, please contact us to arrange.

Data Analysis in Python using Pandas and Numpy

14 hours

Overview

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

Web Development with Django

21 hours

Overview

Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design.

Audience

This course is directed at developers and engineers seeking to incorporate Django in their projects

Deep Learning for Banking (with Python)

28 hours

Overview

Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks. Python is a high-level programming language famous for its clear syntax and code readability.

In this instructor-led, live training, participants will learn how to implement deep learning models for banking using Python as they step through the creation of a deep learning credit risk model.

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

- Understand the fundamental concepts of deep learning
- Learn the applications and uses of deep learning in banking
- Use Python, Keras, and TensorFlow to create deep learning models for banking
- Build their own deep learning credit risk model using Python

Audience

- Developers
- Data scientists

Format of the course

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

Deep Learning for Finance (with Python)

28 hours

Overview

Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks. Python is a high-level programming language famous for its clear syntax and code readability.

In this instructor-led, live training, participants will learn how to implement deep learning models for finance using Python as they step through the creation of a deep learning stock price prediction model.

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

- Understand the fundamental concepts of deep learning
- Learn the applications and uses of deep learning in finance
- Use Python, Keras, and TensorFlow to create deep learning models for finance
- Build their own deep learning stock price prediction model using Python

Audience

- Developers
- Data scientists

Format of the course

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

Deep Learning for Telecom (with Python)

28 hours

Overview

Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed.

Deep learning is a subfield of machine learning which uses methods based on learning data representations and structures such as neural networks.

Python is a high-level programming language famous for its clear syntax and code readability.

In this instructor-led, live training, participants will learn how to implement deep learning models for telecom using Python as they step through the creation of a deep learning credit risk model.

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

- Understand the fundamental concepts of deep learning.
- Learn the applications and uses of deep learning in telecom.
- Use Python, Keras, and TensorFlow to create deep learning models for telecom.
- Build their own deep learning customer churn prediction model using Python.

Format of the course

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

Upcoming Python Courses

Data Analysis in Python using Pandas and Numpy

2019-05-21 09:30:00

Dubai

Remote

14700AED

Classroom

20600AED

Machine Learning for Banking (with Python)

2019-06-23 09:30:00

Dubai

Remote

22050AED

Classroom

29800AED

Data Analysis in Python using Pandas and Numpy

2019-07-16 09:30:00

Dubai

Remote

14700AED

Classroom

20600AED

Data Analysis in Python using Pandas and Numpy

2019-09-10 09:30:00

Dubai

Remote

14700AED

Classroom

20600AED

Data Analysis in Python using Pandas and Numpy

2019-11-04 09:30:00

Dubai

Remote

14700AED

Classroom

20600AED

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