由讲师进行实时指导的Python本地培训课程通过动手实践向学员演示Python编程语言的各个方面。本课程涉及的主题包括Python编程基础、高级Python编程、Python用于测试自动化、Python脚本和自动化，以及Python用于金融、银行、保险等领域的数据分析和大数据应用。
NobleProg Python培训课程还涵盖了用于机器学习和深度学习的Python库和框架的初级和高级课程。
Python培训形式包括“现场实时培训”和“远程实时培训”。现场实时培训可在客户位于中国的所在场所或NobleProg位于中国的企业培训中心进行，远程实时培训可通过交互式远程桌面进行。
NobleProg -- 您的本地培训提供商
客户评论
都很喜欢
蒙 李
课程: Machine Learning Fundamentals with Python
我喜欢练习和学习Python的角落和缝隙
Connor Brierley-Green
课程: Python Programming
Machine Translated
乔伊对编程充满热情。他非常擅长动态适应我们的需求和兴趣。
Randy Enkin
课程: Python Programming
Machine Translated
许多例子让我很容易理解。
Lingmin Cao
课程: Python Programming
Machine Translated
对我们所有问题的指导的全面知识给我的期望提供了答案......讲师进行了很好的讨论......他并不缺乏耐心......
Łukasz Matulewicz
课程: Programowanie w języku Python
Machine Translated
对讲师的丰富知识，工具的多样性以及对该主题的实用方法。
Magdalena Stupak
课程: Programowanie w języku Python
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对培训师很了解，如何翻译。
Renata Cylejowska
课程: Programowanie w języku Python
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认真对待定制的事实。
jurgen linsen
课程: Python Programming
Machine Translated
因为我是唯一的参与者，培训可以适应我的需求。
Kevin THIERRY
课程: Web Development with Web2Py
Machine Translated
我确实喜欢这些练习。
Office for National Statistics
课程: Natural Language Processing with Python
Machine Translated
我喜欢乐于助人且非常善良。
Natalia Machrowicz
课程: Python Programming
Machine Translated
我们做了实践练习（我们编写的脚本可以用于我们的日常工作）。它使课程非常有趣。我也喜欢教练分享他的知识的方式。他以一种非常容易接近的方式做到了。
Malwina Sawa
课程: Python Programming
Machine Translated
记住/重复关键主题的非常好的方法。非常好的“热身”练习。
课程: Python Programming
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*愉快的练习。 *快速进入更高级的主题。 *培训师很友好，很容易上手。 *根据团队需求定制课程。
Matthew Lucas
课程: Python Programming
Machine Translated
我喜欢在课程/课程中添加特定主题的灵活性。
Marc Ammann
课程: Python Programming
Machine Translated
培训师分别查看并帮助每个人。
Szymon Wolny
课程: Programowanie w języku Python
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一组理想的练习。轻松练习和“带星星”
Motorola Solutions Systems Polska Sp. z o.o
课程: Programowanie w języku Python
Machine Translated
良好的平衡理论/练习，将讲课级别调整为听众越来越少，更有经验，这对于使用Jupiter Notebook并在实践中展示理论非常重要。我还喜欢在第二天的培训的第一部分收集匿名反馈，一切都按照我们的建议准备好了，即使它已经非常好，后来它甚至更好:)。
Motorola Solutions Systems Polska Sp. z o.o
课程: Programowanie w języku Python
Machine Translated
老师的承诺，准备，倾听者的态度，愿意解释所有含糊之处。
Małgorzata Konior
课程: Programowanie w języku Python
Machine Translated
领导接近每个人，即使他没有求助并检查练习的水平。
Agnieszka Bielak
课程: Programowanie w języku Python
Machine Translated
培训师提出了一个关于某个问题的非常简短的理论，我们立即去练习。一个很好的挂牌方式，给教练信息他需要花费多少时间才能完成某项任务，还有谁还有解决方案问题。
Motorola Solutions Systems Polska Sp. z o.o
课程: Programowanie w języku Python
Machine Translated
即使有人没有提出要求，但显然他不会继续完成任务，但Kr ys tof出现并能够提供专家建议。
Motorola Solutions Systems Polska Sp. z o.o
课程: Programowanie w języku Python
Machine Translated
总之，所有人都喜欢进行练习的方式，我很高兴我来到这样的教练。
Maksym Kolodiy
课程: Programowanie w języku Python
Machine Translated
练习的真实例子
Motorola Solutions Systems Polska Sp. z o.o
课程: Programowanie w języku Python
Machine Translated
培训材料（Jupyter）的可用性，不断更新笔记本，这取决于课程中出现的问题。消除疑虑，回答任何问题..
Motorola Solutions Systems Polska Sp. z o.o
课程: Programowanie w języku Python
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交付教材的方便性和有趣的方式。
Motorola Solutions Systems Polska Sp. z o.o
课程: Programowanie w języku Python
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处理xlsx和csv文件
Łukasz Olczyk
课程: Python: Automate the boring stuff
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深入报道机器学习主题，特别是神经网络。揭开了很多话题的神秘面纱。
Sacha Nandlall
课程: Python for Advanced Machine Learning
Machine Translated
我喜欢定制的内部文件处理和数据分析。
Glycom A/S
课程: Data Analysis in Python using Pandas and Numpy
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案例研究帮助我们了解了如何在行业中应用Python 。在练习期间非常感谢教练的帮助
Rajiv Dhingra - TCS
课程: Python Programming
Machine Translated
由于我们是PHP开发人员，他了解情况并允许我们在两者之间慢慢映射。我喜欢他添加的例子和幽默。
Soumya Tyagi - TCS
课程: Python Programming
Machine Translated
我很高兴我们使用自己的数据作为例子。
Glycom A/S
课程: Data Analysis in Python using Pandas and Numpy
Machine Translated
一切。
MTU Aero Engines Polska Sp. z o. o.
课程: Programowanie w języku Python
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有趣的问题。
MTU Aero Engines Polska Sp. z o. o.
课程: Programowanie w języku Python
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各种准备的问题和例子
MTU Aero Engines Polska Sp. z o. o.
课程: Programowanie w języku Python
Machine Translated
培训不是演示风格。我们和教练一起编码..
Bhutan Telecom
课程: Web Development with Django
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我最喜欢这一切。
Thukten Dendup - Bhutan Telecom
课程: Web Development with Django
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它是一种全新的体验，一种新的框架，并期待使用课堂上学到的知识做一些事情。
Jigme - Bhutan Telecom
课程: Web Development with Django
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我真的很喜欢很多实验室和实践。
Vivian Feng - Destination Canada
课程: Data Analysis with SQL, Python and Spotfire
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练习/实验室是根据我们自己的组织需求量身定制的。
Destination Canada
课程: Data Analysis with SQL, Python and Spotfire
Machine Translated
我一般都喜欢这个主题。
Destination Canada
课程: Data Analysis with SQL, Python and Spotfire
Machine Translated
培训师正在分享真正的文字体验，向真正的专业人士学习是很好的。
Fednot
课程: Python Programming
Machine Translated
培训师非常出色，他随时准备回答我的问题并尽可能多地分享知识。
Fahad Malalla - Tatweer Petroleum
课程: Advanced Python
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1：1非常密集，但学到了很多东西。
Karen Dyke - BT
课程: Python: Automate the Boring Stuff
Machine Translated
强调编码“在投影机上”的例子肯定是汤姆的+。
ADVA OPTICAL NETWORKING SP. ZO O.
课程: Advanced Python
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我最喜欢这个话题。
Proximus
课程: Python Programming
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演习的组织方式: 都是按照自己的节奏进行的, 安东尼奥在那里帮助你进一步。
Proximus
课程: Python Programming
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我喜欢足够和非常详细的阅读材料和例子 (幻灯片)。
HC Consumer Finance Philippines, Inc.
课程: Python Programming
Machine Translated
我真的很喜欢那娜
HC Consumer Finance Philippines, Inc.
课程: Python Programming
Machine Translated
记住/重复关键主题的非常好的方法。非常好的“热身”练习。
课程: Python Programming
Machine Translated
Python课程大纲
课程名称
课程时长
课程概览
课程名称
课程时长
课程概览
28小时
This course is designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python drives businesses and is used by scientists all over the world – it is one of the most popular programming languages.
The course can be delivered using the latest Python version 3.x with practical exercises making use of the full power. This course can be delivered on any operating system (all flavours of UNIX, including Linux and Mac OS X, as well as Microsoft Windows).
The practical exercises constitute about 70% of the course time, and around 30% are demonstrations and presentations. Discussions and questions can be asked throughout the course.
Note: the training can be tailored to specific needs upon prior request ahead of the proposed course date.
The course can be delivered using the latest Python version 3.x with practical exercises making use of the full power. This course can be delivered on any operating system (all flavours of UNIX, including Linux and Mac OS X, as well as Microsoft Windows).
The practical exercises constitute about 70% of the course time, and around 30% are demonstrations and presentations. Discussions and questions can be asked throughout the course.
Note: the training can be tailored to specific needs upon prior request ahead of the proposed course date.
28小时
在这一由讲师引导的培训中，参与者将学习高级Python编程技术，包括如何将这种多功能语言应用于解决分布式应用、财务、数据分析和可视化、UI编程及维护脚本等领域的问题。
受众
- 开发人员
课程形式
- 部分讲座、部分讨论、练习和大量实操
注意事项
- 如果您想添加、移除或自定义本课程中的任一部分或主题，请联系我们以作安排。
受众
- 开发人员
课程形式
- 部分讲座、部分讨论、练习和大量实操
注意事项
- 如果您想添加、移除或自定义本课程中的任一部分或主题，请联系我们以作安排。
21小时
In this instructor-led, live training in 中国, participants will learn how to use Python and Spark together to analyze big data as they work on hands-on exercises.
By the end of this training, participants will be able to:
- Learn how to use Spark with Python to analyze Big Data.
- Work on exercises that mimic real world cases.
- Use different tools and techniques for big data analysis using PySpark.
By the end of this training, participants will be able to:
- Learn how to use Spark with Python to analyze Big Data.
- Work on exercises that mimic real world cases.
- Use different tools and techniques for big data analysis using PySpark.
14小时
This course is designed for those wishing to learn the Python programming language. The emphasis is on the Python language, the core libraries, as well as on the selection of the best and most useful libraries developed by the Python community. Python drives businesses and is used by scientists all over the world – it is one of the most popular programming languages.
35小时
The training course will help the participants prepare for Web Application Development using Python Programming with Data Analytics. Such data visualization is a great tool for Top Management in decision making.
14小时
The aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the Python programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results.
Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
14小时
这一由讲师引导的培训是基于Al Sweigart所著的知名书籍——“用Python自动化枯燥的事物（Automate the Boring Stuff with Python）”。它针对初学者，通过实际操作练习和讨论涵盖了Python编程的基本概念。重点在于学习编写代码以显着提高办公效率。
在本次培训结束后，参与者将知道如何用Python进行编程，并将这项新技能应用于：
- 通过编写简单的Python程序来自动执行任务。
- 编写可以使用“正则表达式”进行文本模式识别的程序。
- 以编程方式生成和更新Excel电子表格。
- 解析PDF和Word文档。
- 抓取网站，并从线上来源提取信息。
- 编写发送电子邮件通知的程序。
- 使用Python的调试工具来快速解决错误。
- 以编程方式控制鼠标和键盘，以执行点击和输入。
受众
- 希望学习用Python编程的非程序员
- 希望优化办公效率的专业人士和公司团队
- 希望自动化繁琐程序和工作流程的经理
课程形式
- 部分讲座、部分讨论、练习和大量实操
在本次培训结束后，参与者将知道如何用Python进行编程，并将这项新技能应用于：
- 通过编写简单的Python程序来自动执行任务。
- 编写可以使用“正则表达式”进行文本模式识别的程序。
- 以编程方式生成和更新Excel电子表格。
- 解析PDF和Word文档。
- 抓取网站，并从线上来源提取信息。
- 编写发送电子邮件通知的程序。
- 使用Python的调试工具来快速解决错误。
- 以编程方式控制鼠标和键盘，以执行点击和输入。
受众
- 希望学习用Python编程的非程序员
- 希望优化办公效率的专业人士和公司团队
- 希望自动化繁琐程序和工作流程的经理
课程形式
- 部分讲座、部分讨论、练习和大量实操
21小时
在这一由讲师引导的现场培训中，参与者将学习Python中最相关及最尖端的机器学习技术，因为它们构建了一系列涉及图像、音乐、文本和财务数据的演示应用程序。
在本次培训结束后，参与者将能够：
- 运用用于解决复杂问题的机器学习算法和技术
- 将深度学习和半监督学习应用于涉及图像、音乐、文本和财务数据的应用程序
- 推动Python算法达到其最大潜力
- 使用例如NumPy和Theano的库和包
受众
- 开发人员
- 分析师
- 数据科学家
课程形式
- 部分讲座、部分讨论、练习和大量实操
在本次培训结束后，参与者将能够：
- 运用用于解决复杂问题的机器学习算法和技术
- 将深度学习和半监督学习应用于涉及图像、音乐、文本和财务数据的应用程序
- 推动Python算法达到其最大潜力
- 使用例如NumPy和Theano的库和包
受众
- 开发人员
- 分析师
- 数据科学家
课程形式
- 部分讲座、部分讨论、练习和大量实操
14小时
Pandas is a Python package that provides data structures for working with structured (tabular, multidimensional, potentially heterogeneous) and time series data.
21小时
In this instructor-led, live training in 中国, participants will learn how to use PyTest to write short, maintainable tests that are elegant, expressive and readable.
By the end of this training, participants will be able to:
- Write readable and maintainable tests without the need for boilerplate code.
- Use the fixture model to write small tests.
- Scale tests up to complex functional testing for applications, packages, and libraries.
- Understand and apply PyTest features such as hooks, assert rewriting and plug-ins.
- Reduce test times by running tests in parallel and across multiple processors.
- Run tests in a continuous integration environment, together with other utilities such as tox, mock, coverage, unittest, doctest and Selenium.
- Use Python to test non-Python applications.
By the end of this training, participants will be able to:
- Write readable and maintainable tests without the need for boilerplate code.
- Use the fixture model to write small tests.
- Scale tests up to complex functional testing for applications, packages, and libraries.
- Understand and apply PyTest features such as hooks, assert rewriting and plug-ins.
- Reduce test times by running tests in parallel and across multiple processors.
- Run tests in a continuous integration environment, together with other utilities such as tox, mock, coverage, unittest, doctest and Selenium.
- Use Python to test non-Python applications.
14小时
This instructor-led, live training in 中国 (online or onsite) is aimed at data analysts who wish to build analytic applications using Python with Plotly and Dash.
By the end of this training, participants will be able to:
- Set up a real-time interactive dashboard for streaming live updating data.
- Build interactive dashboards using Python for data science solutions.
- Secure interactive dashboards with advanced authentication methods.
By the end of this training, participants will be able to:
- Set up a real-time interactive dashboard for streaming live updating data.
- Build interactive dashboards using Python for data science solutions.
- Secure interactive dashboards with advanced authentication methods.
28小时
The aim of this course is to provide general proficiency in applying Machine Learning methods in practice. Through the use of the Python programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results.
Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
28小时
This course introduces linguists or programmers to NLP in Python. During this course we will mostly use nltk.org (Natural Language Tool Kit), but also we will use other libraries relevant and useful for NLP. At the moment we can conduct this course in Python 2.x or Python 3.x. Examples are in English or Mandarin (普通话). Other languages can be also made available if agreed before booking.
35小时
Python is a programming language that has gained huge popularity in the financial industry. Adopted by the largest investment banks and hedge funds, it is being used to build a wide range of financial applications ranging from core trading programs to risk management systems.
In this instructor-led, live training, participants will learn how to use Python to develop practical applications for solving a number of specific finance related problems.
By the end of this training, participants will be able to:
- Understand the fundamentals of the Python programming language
- Download, install and maintain the best development tools for creating financial applications in Python
- Select and utilize the most suitable Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
- Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
- Troubleshoot, integrate, deploy, and optimize a Python application
Audience
- Developers
- Analysts
- Quants
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.
In this instructor-led, live training, participants will learn how to use Python to develop practical applications for solving a number of specific finance related problems.
By the end of this training, participants will be able to:
- Understand the fundamentals of the Python programming language
- Download, install and maintain the best development tools for creating financial applications in Python
- Select and utilize the most suitable Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
- Build applications that solve problems related to asset allocation, risk analysis, investment performance and more
- Troubleshoot, integrate, deploy, and optimize a Python application
Audience
- Developers
- Analysts
- Quants
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
Note
- This training aims to provide solutions for some of the principle problems faced by finance professionals. However, if you have a particular topic, tool or technique that you wish to append or elaborate further on, please please contact us to arrange.
21小时
A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data. The acronym GIS is sometimes used for geographic information science (GIScience) to refer to the academic discipline that studies geographic information systems and is a large domain within the broader academic discipline of geoinformatics.
The use of Python with GIS has substantially increased over the last two decades, particularly with the introduction of Python 2.0 series in 2000, which included many new programming features that made the language much easier to deploy. Since that time, Python has not only been utilized within commercial GIS such as products by Esri but also open source platforms, including as part of QGIS and GRASS. In fact, Python today is by far the most widely used language by GIS users and programmers.
This program covers the usage of Python and its advance libraries like geopandas, pysal, bokeh and osmnx to implement your own GIS features. The program also covers introductory modules around ArcGIS API, and QGIS toolboox.
The use of Python with GIS has substantially increased over the last two decades, particularly with the introduction of Python 2.0 series in 2000, which included many new programming features that made the language much easier to deploy. Since that time, Python has not only been utilized within commercial GIS such as products by Esri but also open source platforms, including as part of QGIS and GRASS. In fact, Python today is by far the most widely used language by GIS users and programmers.
This program covers the usage of Python and its advance libraries like geopandas, pysal, bokeh and osmnx to implement your own GIS features. The program also covers introductory modules around ArcGIS API, and QGIS toolboox.
35小时
This is a 5 day introduction to Data Science and Artificial Intelligence (AI).
The course is delivered with examples and exercises using Python
The course is delivered with examples and exercises using Python
28小时
This is a 4 day course introducing AI and it's application using the Python programming language. There is an option to have an additional day to undertake an AI project on completion of this course.
21小时
Deep Reinforcement Learning refers to the ability of an "artificial agent" to learn by trial-and-error and rewards-and-punishments. An artificial agent aims to emulate a human's ability to obtain and construct knowledge on its own, directly from raw inputs such as vision. To realize reinforcement learning, deep learning and neural networks are used. Reinforcement learning is different from machine learning and does not rely on supervised and unsupervised learning approaches.
In this instructor-led, live training, participants will learn the fundamentals of Deep Reinforcement Learning as they step through the creation of a Deep Learning Agent.
By the end of this training, participants will be able to:
- Understand the key concepts behind Deep Reinforcement Learning and be able to distinguish it from Machine Learning
- Apply advanced Reinforcement Learning algorithms to solve real-world problems
- Build a Deep Learning Agent
Audience
- Developers
- Data Scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn the fundamentals of Deep Reinforcement Learning as they step through the creation of a Deep Learning Agent.
By the end of this training, participants will be able to:
- Understand the key concepts behind Deep Reinforcement Learning and be able to distinguish it from Machine Learning
- Apply advanced Reinforcement Learning algorithms to solve real-world problems
- Build a Deep Learning Agent
Audience
- Developers
- Data Scientists
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
14小时
In this instructor-led, live training in 中国 participants combine the power of Python with Selenium to automate the testing of a sample web application. By combining theory with practice in a live lab environment, participants will gain the knowledge and practice needed to automate their own web testing projects using Python and Selenium.
14小时
In this instructor-led, live training in 中国 (onsite or remote), participants will learn how to combine the capabilities of Python and Excel.
By the end of this training, participants will be able to:
- Install and configure packages for integrating Python and Excel.
- Read, write, and manipulate Excel files using Python.
- Call Python functions from Excel.
By the end of this training, participants will be able to:
- Install and configure packages for integrating Python and Excel.
- Read, write, and manipulate Excel files using Python.
- Call Python functions from Excel.
14小时
In this instructor-led, live training in 中国, participants will learn three different approaches for accessing, analyzing and visualizing data. We start with an introduction to RDMS databases; the focus will be on accessing and querying an Oracle database using the SQL language. Then we look at strategies for accessing an RDMS database programmatically using the Python language. Finally, we look at how to visualize and present data graphically using TIBCO Spotfire.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
7小时
Behave是一个开源的、基于Python的BDD框架，用于以自然语言风格编写测试。
BDD（行为驱动开发）是一种敏捷软件开发技术，鼓励开发人员、QA和非技术业务人员在软件项目中进行协作。
本培训讲首先讨论BDD，以及Behave框架如何用于Web应用程序的BDD测试。学员将有充足的机会与讲师和其他学员进行交流，并在实验室环境中开展动手练习，运用所学的概念和策略。
在本次培训结束后，学员将对BDD和Behave有一个明确的理解，并获得在实际测试场景中使用这些技术和工具的必要实践。
受众
- 测试人员和开发人员
课程形式
- 重视实操。大部分概念是通过示例、练习和动手开发学到的。
BDD（行为驱动开发）是一种敏捷软件开发技术，鼓励开发人员、QA和非技术业务人员在软件项目中进行协作。
本培训讲首先讨论BDD，以及Behave框架如何用于Web应用程序的BDD测试。学员将有充足的机会与讲师和其他学员进行交流，并在实验室环境中开展动手练习，运用所学的概念和策略。
在本次培训结束后，学员将对BDD和Behave有一个明确的理解，并获得在实际测试场景中使用这些技术和工具的必要实践。
受众
- 测试人员和开发人员
课程形式
- 重视实操。大部分概念是通过示例、练习和动手开发学到的。
21小时
PyQt 是一个跨平台库, 用于为 Python 应用程序开发 Gui (图形用户界面)。它将 Python 与 Qt GUI 工具包接口.
本教师指导的现场培训 (现场或远程) 针对的是希望使用 Python 和 Qt UI 框架对具有视觉吸引力的软件应用程序进行编程的人
。
到本次培训结束时, 学员将能够:
- 设置包含所有所需库、包和框架的开发环境。
- 创建一个桌面或服务器应用程序, 其用户界面功能流畅且具有视觉吸引力.
- 实现各种 UI 元素和效果, 包括小部件、图表、图层等, 以实现最大的可用性效果。
- 在设计和开发阶段实施良好的 UI 设计和代码组织。
- 测试和调试应用程序。
课程 格式
- 互动讲座和讨论.
- 大量的练习和练习
- 在现场实验室环境中的实际实现。
课程自定义选项
- 本课程可用于在 Windows、Linux 和 Mac OS 上进行开发.
- 使用所有软件的最新版本, 例如, 本文撰写时的 PyQt 5 等
- 要要求本课程的定制培训, 请联系我们安排
本教师指导的现场培训 (现场或远程) 针对的是希望使用 Python 和 Qt UI 框架对具有视觉吸引力的软件应用程序进行编程的人
。
到本次培训结束时, 学员将能够:
- 设置包含所有所需库、包和框架的开发环境。
- 创建一个桌面或服务器应用程序, 其用户界面功能流畅且具有视觉吸引力.
- 实现各种 UI 元素和效果, 包括小部件、图表、图层等, 以实现最大的可用性效果。
- 在设计和开发阶段实施良好的 UI 设计和代码组织。
- 测试和调试应用程序。
课程 格式
- 互动讲座和讨论.
- 大量的练习和练习
- 在现场实验室环境中的实际实现。
课程自定义选项
- 本课程可用于在 Windows、Linux 和 Mac OS 上进行开发.
- 使用所有软件的最新版本, 例如, 本文撰写时的 PyQt 5 等
- 要要求本课程的定制培训, 请联系我们安排
14小时
This instructor-led, live training in 中国 (online or onsite) is aimed at Matlab users who wish to explore and or transition to Python for data analytics and visualization.
By the end of this training, participants will be able to:
- Install and configure a Python development environment.
- Understand the differences and similarities between Matlab and Python syntax.
- Use Python to obtain insights from various datasets.
- Convert existing Matlab applications to Python.
- Integrate Matlab and Python applications.
By the end of this training, participants will be able to:
- Install and configure a Python development environment.
- Understand the differences and similarities between Matlab and Python syntax.
- Use Python to obtain insights from various datasets.
- Convert existing Matlab applications to Python.
- Integrate Matlab and Python applications.
14小时
Object-Oriented Programming (OOP) is a programming paradigm based around the concept of objects. OOP is more data-focused rather than logic-focused. Python is a high-level programming language famous for its clear syntax and code readibility.
In this instructor-led, live training, participants will learn how to get started with Object-Oriented Programming using Python.
By the end of this training, participants will be able to:
- Understand the fundamental concepts of Object-Oriented Programming
- Understand the OOP syntax in Python
- Write their own object-oriented program in Python
Audience
- Beginners who would like to learn about Object-Oriented Programming
- Developers interested in learning OOP in Python
- Python programmers interested in learning OOP
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
In this instructor-led, live training, participants will learn how to get started with Object-Oriented Programming using Python.
By the end of this training, participants will be able to:
- Understand the fundamental concepts of Object-Oriented Programming
- Understand the OOP syntax in Python
- Write their own object-oriented program in Python
Audience
- Beginners who would like to learn about Object-Oriented Programming
- Developers interested in learning OOP in Python
- Python programmers interested in learning OOP
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
28小时
In this instructor-led, live training in 中国, participants will learn how to implement deep learning models for telecom using Python as they step through the creation of a deep learning credit risk model.
By the end of this training, participants will be able to:
- Understand the fundamental concepts of deep learning.
- Learn the applications and uses of deep learning in telecom.
- Use Python, Keras, and TensorFlow to create deep learning models for telecom.
- Build their own deep learning customer churn prediction model using Python.
By the end of this training, participants will be able to:
- Understand the fundamental concepts of deep learning.
- Learn the applications and uses of deep learning in telecom.
- Use Python, Keras, and TensorFlow to create deep learning models for telecom.
- Build their own deep learning customer churn prediction model using Python.
28小时
This instructor-led, live training in 中国 (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.
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.
7小时
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.
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.
14小时
This instructor-led, live training in 中国 (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.
- 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:
- 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.
7小时
This instructor-led, live training in 中国 (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.
- 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:
- 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.
Last Updated:
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