Python Training Courses
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 training can be carried out locally on customer premises in the UAE or in NobleProg corporate training centers in the UAE. Remote live training is carried out by way of an interactive, remote desktop. NobleProg -- Your Local Training Provider
Client Testimonials
I liked everything from the preparation and presentation to trainer interaction
Fahad Malalla - Tatweer Petroleum
Course Name: 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 Name: Introductory R 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 Name: Introductory R for Biologists
I preferred the exercise and learning about the nooks and crannies of Python
Connor Brierley-Green
Course Name: 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 Name: Python Programming
Many examples made me easy to understand.
Lingmin Cao
Course Name: Python Programming
fact that customisation was taken seriously
jurgen linsen
Course Name: Python Programming
I did like the exercises
Office for National Statistics
Course Name: Natural Language Processing with Python
Helpful and very kind.
Natalia Machrowicz
Course Name: 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 Name: Python Programming
Willingness to share more
Balaram Chandra Paul
Course Name: A practical introduction to Data Analysis and Big Data
Very good approach to memorize/repeat the key topics. Very nice "warm-up" exercises.
Course Name: 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 Name: Python Programming
felixibility to add specific topics into the course / lessons
Marc Ammann
Course Name: Python Programming
It covered a broad range of information.
Continental AG / Abteilung: CF IT Finance
Course Name: A practical introduction to Data Analysis and Big Data
presentation of technologies
Continental AG / Abteilung: CF IT Finance
Course Name: A practical introduction to Data Analysis and Big Data
Overall the Content was good.
Sameer Rohadia
Course Name: A practical introduction to Data Analysis and Big Data
In-depth coverage of machine learning topics, particularly neural networks. Demystified a lot of the topic.
Sacha Nandlall
Course Name: Python for Advanced Machine Learning
everything!
UBS Business Solutions Poland Sp. z o.o.
Course Name: Python Programming
Personalized help
UBS Business Solutions Poland Sp. z o.o.
Course Name: Python Programming
Everything was fine!
UBS Business Solutions Poland Sp. z o.o.
Course Name: 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 Name: 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 Name: Python Programming
Training in a small group is ideal as more focus can be put on items of specific interest
HSCIC
Course Name: Unit Testing with Python
customized, in-house file processing and data analysis
Glycom A/S
Course Name: 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 Name: 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 Name: Python Programming
That we have used our own data as examples
Glycom A/S
Course Name: Data Analysis in Python using Pandas and Numpy
Very good support during the exercises. Trainers had excellent knowledge of the subject
Marc Pierreux - Proximus
Course Name: Python Fundamentals
Time to make exercice and the availability of trainer to personnaly review the code and give advice
Proximus
Course Name: Python Fundamentals
The comprehensive knowledge of the guide to all our questions gave answers overwhelming my expectations ... The lecturer conducts great discussions ... He does not lack patience ...
Łukasz Matulewicz
Course Name: Programowanie w języku Python
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Great knowledge of the lecturer, diversity of tools and practical approach to the topic
Magdalena Stupak
Course Name: Programowanie w języku Python
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great knowledge of the trainer, how to translate
Renata Cylejowska
Course Name: Programowanie w języku Python
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All like it
蒙 李
Course Name: Machine Learning Fundamentals with Python
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All like it
蒙 李
Course Name: Machine Learning Fundamentals with Python
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the trainer looked at and helped each person individually
Szymon Wolny
Course Name: Programowanie w języku Python
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A set of exercises ideally suited to the subject. Exercises easy and "with a star"
Motorola Solutions Systems Polska Sp. z o.o
Course Name: Programowanie w języku Python
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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 Name: Programowanie w języku Python
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commitment of the teacher, preparation, approach to listeners, willingness to explain all ambiguities
Małgorzata Konior
Course Name: Programowanie w języku Python
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That the leader approaches everyone, even when he does not call for help and checks the level of the exercise.
Agnieszka Bielak
Course Name: Programowanie w języku Python
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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 Name: Programowanie w języku Python
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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 Name: Programowanie w języku Python
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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 Name: Programowanie w języku Python
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Real examples of exercises
Motorola Solutions Systems Polska Sp. z o.o
Course Name: Programowanie w języku Python
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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 Name: Programowanie w języku Python
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Accessibility and an interesting way of delivering teaching materials.
Motorola Solutions Systems Polska Sp. z o.o
Course Name: Programowanie w języku Python
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Work on xlsx and csv files
Łukasz Olczyk
Course Name: Python: Automate the boring stuff
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Everything I rated on 6
AB S.A.
Course Name: Machine Learning - szkolenie dedykowane
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a lot of information
Tomasz Szumigalski
Course Name: Machine Learning - szkolenie dedykowane
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Problems clearly explained
AB S.A.
Course Name: Machine Learning - szkolenie dedykowane
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Great knowledge of the trainer and the ability to understand the meaning of our stupid questions;)
AB S.A.
Course Name: Machine Learning - szkolenie dedykowane
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All
MTU Aero Engines Polska Sp. z o. o.
Course Name: Programowanie w języku Python
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Interesting issues
MTU Aero Engines Polska Sp. z o. o.
Course Name: Programowanie w języku Python
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Variety of prepared issues and examples
MTU Aero Engines Polska Sp. z o. o.
Course Name: Programowanie w języku Python
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Course Outlines
| Code | Name | Duration | Overview |
|---|---|---|---|
| pythonprog | Python Programming | 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 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. |
| pytest | Unit Testing with Python | 21 hours | 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 Audience Software testers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| pythonexcel | Python for Excel | 14 hours | 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. |
| progbio | Programming for Biologists | 28 hours | This is a practical course, which shows why programming is a powerful tool in the context of solving biological problems. During the course participants will be taught the Python programming language, a language widely considered both powerful as well as easy to use. This course might be considered as a demonstration how bioinformatics improves biologists lives. The course is designed and aimed for people without computer science background who want to learn programming. 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. |
| mlbankingpython_ | Machine Learning for Banking (with Python) | 21 hours | Machine Learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Python is a programming language famous for its clear syntax and readability. It offers an excellent collection of well-tested libraries and techniques for developing machine learning applications. In this instructor-led, live training, participants will learn how to apply machine learning techniques and tools for solving real-world problems in the banking industry. Participants first learn the key principles, then put their knowledge into practice by building their own machine learning models and using them to complete a number of team projects. Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| chatbotpython | Building Chatbots in Python | 21 hours | 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. |
| mlfunpython | Machine Learning Fundamentals with Python | 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. |
| python_nlp | Natural Language Processing with Deep Dive in Python and NLTK | 35 hours | 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. |
| pygis | Python for Geographic Information System (GIS) | 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. |
| python_nltk | Natural Language Processing with Python | 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. |
| pythonfinance | Python Programming for Finance | 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. |
| mlfsas | Machine Learning Fundamentals with Scala and Apache Spark | 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 Scala 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. |
| textsum | Text Summarization with Python | 14 hours | 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 |
| datapyth | Data Analysis in Python using Pandas and Numpy | 14 hours | Pandas is a Python package that provides data structures for working with structured (tabular, multidimensional, potentially heterogeneous) and time series data. |
| dlfornlp | Deep Learning for NLP (Natural Language Processing) | 28 hours | Deep Learning for NLP allows a machine to learn simple to complex language processing. Among the tasks currently possible are language translation and caption generation for photos. DL (Deep Learning) is a subset of ML (Machine Learning). Python is a popular programming language that contains libraries for Deep Learning for NLP. In this instructor-led, live training, participants will learn to use Python libraries for NLP (Natural Language Processing) as they create an application that processes a set of pictures and generates captions. By the end of this training, participants will be able to: Design and code DL for NLP using Python libraries Create Python code that reads a substantially huge collection of pictures and generates keywords Create Python Code that generates captions from the detected keywords Audience Programmers with interest in linguistics Programmers who seek an understanding of NLP (Natural Language Processing) Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| BigData_ | A Practical Introduction to Data Analysis and Big Data | 35 hours | Participants who complete this training will gain a practical, real-world understanding of Big Data and its related technologies, methodologies and tools. Participants will have the opportunity to put this knowledge into practice through hands-on exercises. Group interaction and instructor feedback make up an important component of the class. The course starts with an introduction to elemental concepts of Big Data, then progresses into the programming languages and methodologies used to perform Data Analysis. Finally, we discuss the tools and infrastructure that enable Big Data storage, Distributed Processing, and Scalability. Audience Developers / programmers IT consultants Format of the course Part lecture, part discussion, hands-on practice and implementation, occasional quizing to measure progress. |
| ooppython | Learn Object-Oriented Programming with Python | 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 |
| behave | Behave: BDD with Python (Cucumber/Gherkin for Python) | 7 hours | Behave is an open-source, Python-based BDD framework for writing tests in a natural language style. BDD, or Behavior Driven Development, is an agile software development technique that encourages collaboration among developers, QA and non-technical business people in a software project. This training 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. Audience Testers and Developers Format of the course Heavy emphasis on hands-on practice. Most of the concepts are learned through samples, exercises and hands-on development. |
| sparkpython | Python and Spark for Big Data (PySpark) | 21 hours | 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 Audience Developers IT Professionals Data Scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| seleniumpython | Selenium with Python for Test Automation | 14 hours | 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 |
| mlfinancepython | Machine Learning for Finance (with Python) | 21 hours | Machine learning is a branch of Artificial Intelligence wherein computers have the ability to learn without being explicitly programmed. Python is a programming language famous for its clear syntax and readability. It offers an excellent collection of well-tested libraries and techniques for developing machine learning applications. In this instructor-led, live training, participants will learn how to apply machine learning techniques and tools for solving real-world problems in the finance industry. Participants first learn the key principles, then put their knowledge into practice by building their own machine learning models and using them to complete a number of team projects. By the end of this training, participants will be able to: Understand the fundamental concepts in machine learning Learn the applications and uses of machine learning in finance Develop their own algorithmic trading strategy using machine learning with Python Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| pythonautomation | Python: Automate the Boring Stuff | 14 hours | This instructor-led 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. Audience Non-programmers wishing to learn programming with Python Professionals and company teams wishing to optimize their office productivity Managers wishing to automate tedious processes and workflows Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| pythonbigdata | Analyzing Big Financial Data with Python | 35 hours | 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 |
| kivy | Kivy: Building Android Apps with Python | 7 hours | 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 |
| pythoncomputervision | Computer Vision with Python | 14 hours | 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 |
| pythonmultipurpose | Advanced Python | 28 hours | In this instructor-led 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. Audience Developers 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. |
| dlforfinancewithpython | Deep Learning for Finance (with Python) | 28 hours | 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 |
| restfulapi | Designing RESTful APIs | 14 hours | APIs (Application Programming Interface) allow for your application to connect with other applications. In this instructor-led, live training, participants will learn how to write high-quality APIs as they build and secure a backend API server. By the end of this training, participants will be able to: Choose from a number of frameworks for building APIs Understand and model the APIs published by companies such as Google and Facebook Create and publish their own Restful APIs for public consumption Secure their APIs through token-based authentication Audience Developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice Note To customize this course for other languages, such as PHP, Javascript, etc., please contact us to arrange |
| microservicespython | Developing Microservices with Python | 7 hours | Microservices refer to an application architecture style that promotes the use of independent, self-contained programs. Python is a dynamic high-level programming language that is ideal for both scripting as welll as application development. Python's expansive library of open source tools and frameworks make it a practical choice for building microservices. In this instructor-led, live training, participants will learn the fundamentals of microservices as they step through the creation of a microservice using Python. By the end of this training, participants will be able to: Understand the basics of building microservices Learn how to use Python to build microservices Learn how to use Docker to deploy Python based microservices Audience Developers Programmers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| pythonadvml | Python for Advanced Machine Learning | 21 hours | 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 Audience Developers Analysts Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
Upcoming Courses
| Course | Course Date | Course Price [Remote / Classroom] |
|---|---|---|
| Python: Machine Learning with Text - Dubai | Tue, 2018-07-03 09:30 | 6000USD / 8100USD |