由講師進行實時指導的Python本地培訓課程通過動手實踐向學員演示Python編程語言的各個方面。本課程涉及的主題包括Python編程基礎、高級Python編程、Python用于測試自動化、Python腳本和自動化，以及Python用于金融、銀行、保險等領域的數據分析和大數據應用。
NobleProg Python培訓課程還涵蓋了用于機器學習和深度學習的Python庫和框架的初級和高級課程。
Python培訓形式包括“現場實時培訓”和“遠程實時培訓”。現場實時培訓可在客戶位于台灣的所在場所或NobleProg位于台灣的企業培訓中心進行，遠程實時培訓可通過交互式遠程桌面進行。
NobleProg -- 您的本地培訓提供商
客戶評論
我喜歡練習和學習Python的角落和縫隙
Connor Brierley-Green
課程: Python Programming
Machine Translated
喬伊對編程充滿熱情。他非常擅長動態適應我們的需求和興趣。
Randy Enkin
課程: Python Programming
Machine Translated
許多例子讓我很容易理解。
Lingmin Cao
課程: Python Programming
Machine Translated
對我們所有問題的指導的全面知識給我的期望提供了答案......講師進行了很好的討論......他並不缺乏耐心......
Łukasz Matulewicz
課程: Programowanie w języku Python
Machine Translated
對講師的豐富知識，工具的多樣性以及對該主題的實用方法。
Magdalena Stupak
課程: Programowanie w języku Python
Machine Translated
對培訓師很了解，如何翻譯。
Renata Cylejowska
課程: Programowanie w języku Python
Machine Translated
認真對待定制的事實。
jurgen linsen
課程: Python Programming
Machine Translated
因為我是唯一的參與者，培訓可以適應我的需求。
Kevin THIERRY
課程: Web Development with Web2Py
Machine Translated
我確實喜歡這些練習。
Office for National Statistics
課程: Natural Language Processing with Python
Machine Translated
我喜歡樂於助人且非常善良。
Natalia Machrowicz
課程: Python Programming
Machine Translated
我們做了實踐練習（我們編寫的腳本可以用於我們的日常工作）。它使課程非常有趣。我也喜歡教練分享他的知識的方式。他以一種非常容易接近的方式做到了。
Malwina Sawa
課程: Python Programming
Machine Translated
記住/重複關鍵主題的非常好的方法。非常好的“熱身”練習。
課程: Python Programming
Machine Translated
*愉快的練習。 *快速進入更高級的主題。 *培訓師很友好，很容易上手。 *根據團隊需求定制課程。
Matthew Lucas
課程: Python Programming
Machine Translated
我喜歡在課程/課程中添加特定主題的靈活性。
Marc Ammann
課程: Python Programming
Machine Translated
都很喜歡
蒙 李
課程: Machine Learning Fundamentals with Python
Machine Translated
培訓師分別查看並幫助每個人。
Szymon Wolny
課程: Programowanie w języku Python
Machine Translated
一組理想的練習。輕鬆練習和“帶星星”
Motorola Solutions Systems Polska Sp. z o.o
課程: Programowanie w języku Python
Machine Translated
良好的平衡理論/練習，將講課級別調整為聽眾越來越少，更有經驗，這對於使用Jupiter Notebook並在實踐中展示理論非常重要。我還喜歡在第二天的培訓的第一部分收集匿名反饋，一切都按照我們的建議準備好了，即使它已經非常好，後來它甚至更好:)。
Motorola Solutions Systems Polska Sp. z o.o
課程: Programowanie w języku Python
Machine Translated
老師的承諾，準備，傾聽者的態度，願意解釋所有含糊之處。
Małgorzata Konior
課程: Programowanie w języku Python
Machine Translated
領導者接近每個人，即使他沒有求助並檢查練習的水平。
Agnieszka Bielak
課程: Programowanie w języku Python
Machine Translated
培訓師提出了一個關於某個問題的非常簡短的理論，我們立即去練習。一個很好的掛牌方式，給教練信息他需要花費多少時間才能完成某項任務，還有誰還有解決方案問題。
Motorola Solutions Systems Polska Sp. z o.o
課程: Programowanie w języku Python
Machine Translated
即使有人沒有提出要求，但顯然他不會繼續完成任務，但Krzysztof出現並能夠提供專家建議。
Motorola Solutions Systems Polska Sp. z o.o
課程: Programowanie w języku Python
Machine Translated
總之，所有人都喜歡進行練習的方式，我很高興我來到這樣的教練。
Maksym Kolodiy
課程: Programowanie w języku Python
Machine Translated
練習的真實例子
Motorola Solutions Systems Polska Sp. z o.o
課程: Programowanie w języku Python
Machine Translated
培訓材料（Jupyter）的可用性，不斷更新筆記本，這取決於課程中出現的問題。消除疑慮，回答任何問題..
Motorola Solutions Systems Polska Sp. z o.o
課程: Programowanie w języku Python
Machine Translated
交付教材的方便性和有趣的方式。
Motorola Solutions Systems Polska Sp. z o.o
課程: Programowanie w języku Python
Machine Translated
處理xlsx和csv文件
Łukasz Olczyk
課程: Python: Automate the boring stuff
Machine Translated
深入報導機器學習主題，特別是神經網絡。揭開了很多話題的神秘面紗。
Sacha Nandlall
課程: Python for Advanced Machine Learning
Machine Translated
我喜歡定制的內部文件處理和數據分析。
Glycom A/S
課程: Data Analysis in Python using Pandas and Numpy
Machine Translated
案例研究幫助我們了解瞭如何在行業中應用Python 。在練習期間非常感謝教練的幫助
Rajiv Dhingra - TCS
課程: Python Programming
Machine Translated
由於我們是PHP開發人員，他了解情況並允許我們在兩者之間慢慢映射。我喜歡他添加的例子和幽默。
Soumya Tyagi - TCS
課程: Python Programming
Machine Translated
我很高興我們使用自己的數據作為例子。
Glycom A/S
課程: Data Analysis in Python using Pandas and Numpy
Machine Translated
一切。
MTU Aero Engines Polska Sp. z o. o.
課程: Programowanie w języku Python
Machine Translated
有趣的問題。
MTU Aero Engines Polska Sp. z o. o.
課程: Programowanie w języku Python
Machine Translated
各種準備的問題和例子
MTU Aero Engines Polska Sp. z o. o.
課程: Programowanie w języku Python
Machine Translated
培訓不是演示風格。我們和教練一起編碼..
Bhutan Telecom
課程: Web Development with Django
Machine Translated
我最喜歡這一切。
Thukten Dendup - Bhutan Telecom
課程: Web Development with Django
Machine Translated
它是一種全新的體驗，一種新的框架，並期待使用課堂上學到的知識做一些事情。
Jigme - Bhutan Telecom
課程: Web Development with Django
Machine Translated
我真的很喜歡很多實驗室和實踐。
Vivian Feng - Destination Canada
課程: Data Analysis with SQL, Python and Spotfire
Machine Translated
練習/實驗室是根據我們自己的組織需求量身定制的。
Destination Canada
課程: Data Analysis with SQL, Python and Spotfire
Machine Translated
我一般都喜歡這個主題。
Destination Canada
課程: Data Analysis with SQL, Python and Spotfire
Machine Translated
培訓師正在分享真正的文字體驗，向真正的專業人士學習是很好的。
Fednot
課程: Python Programming
Machine Translated
培訓師非常出色，他隨時準備回答我的問題並儘可能多地分享知識。
Fahad Malalla - Tatweer Petroleum
課程: Advanced Python
Machine Translated
1：1非常密集，但學到了很多東西。
Karen Dyke - BT
課程: Python: Automate the Boring Stuff
Machine Translated
強調編碼“在投影機上”的例子肯定是湯姆的+。
ADVA OPTICAL NETWORKING SP. ZO O.
課程: Advanced Python
Machine Translated
我最喜歡這個話題。
Proximus
課程: Python Programming
Machine Translated
演習的組織方式: 都是按照自己的節奏進行的, 安東尼奧在那裡説明你進一步。
Proximus
課程: Python Programming
Machine Translated
我喜歡足夠和非常詳細的閱讀材料和例子 (幻燈片)。
HC Consumer Finance Philippines, Inc.
課程: Python Programming
Machine Translated
我真的很喜歡那娜
HC Consumer Finance Philippines, Inc.
課程: Python Programming
Machine Translated
我最喜歡的是, 課程大綱中的一切都對我們的專案有用。
Joanna Marie Escueta - Aarki, Inc.
課程: Python Programming
Machine Translated
記住/重複關鍵主題的非常好的方法。非常好的“熱身”練習。
課程: Python Programming
Machine Translated
Python課程大綱
課程名稱
課程時長
概觀
課程名稱
課程時長
概觀
21小時
This instructor-led, live training in 台灣 (online or onsite) is aimed at developers who wish to use and integrate Spark, Hadoop, and Python to process, analyze, and transform large and complex data sets.
By the end of this training, participants will be able to:
- Set up the necessary environment to start processing big data with Spark, Hadoop, and Python.
- Understand the features, core components, and architecture of Spark and Hadoop.
- Learn how to integrate Spark, Hadoop, and Python for big data processing.
- Explore the tools in the Spark ecosystem (Spark MlLib, Spark Streaming, Kafka, Sqoop, Kafka, and Flume).
- Build collaborative filtering recommendation systems similar to Netflix, YouTube, Amazon, Spotify, and Google.
- Use Apache Mahout to scale machine learning algorithms.
By the end of this training, participants will be able to:
- Set up the necessary environment to start processing big data with Spark, Hadoop, and Python.
- Understand the features, core components, and architecture of Spark and Hadoop.
- Learn how to integrate Spark, Hadoop, and Python for big data processing.
- Explore the tools in the Spark ecosystem (Spark MlLib, Spark Streaming, Kafka, Sqoop, Kafka, and Flume).
- Build collaborative filtering recommendation systems similar to Netflix, YouTube, Amazon, Spotify, and Google.
- Use Apache Mahout to scale machine learning algorithms.
14小時
This instructor-led, live training in 台灣 (online or onsite) is aimed at data scientists and developers who wish to use and integrate SQL, Python, and Tableau to perform complex data analysis, processing, and visualization.
By the end of this training, participants will be able to:
- Set up the necessary environment to perform data analysis with SQL, Python, and Tableau.
- Understand the key concepts of software integration (data, servers, clients, APIs, endpoints, etc.).
- Get a refresher on the fundamentals of Python and SQL.
- Perform data pre-processing techniques in Python.
- Learn how to connect Python and SQL for data analysis.
- Create insightful data visualizations and charts with Tableau.
By the end of this training, participants will be able to:
- Set up the necessary environment to perform data analysis with SQL, Python, and Tableau.
- Understand the key concepts of software integration (data, servers, clients, APIs, endpoints, etc.).
- Get a refresher on the fundamentals of Python and SQL.
- Perform data pre-processing techniques in Python.
- Learn how to connect Python and SQL for data analysis.
- Create insightful data visualizations and charts with Tableau.
14小時
This instructor-led, live training in 台灣 (online or onsite) is aimed at developers who wish to use the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications.
By the end of this training, participants will be able to:
- Set up the necessary development environment that integrates FastAPI, React, and MongoDB.
- Understand the key concepts, features, and benefits of the FARM stack.
- Learn how to build REST APIs with FastAPI.
- Learn how to design interactive applications with React.
- Develop, test, and deploy applications (front end and back end) using the FARM stack.
By the end of this training, participants will be able to:
- Set up the necessary development environment that integrates FastAPI, React, and MongoDB.
- Understand the key concepts, features, and benefits of the FARM stack.
- Learn how to build REST APIs with FastAPI.
- Learn how to design interactive applications with React.
- Develop, test, and deploy applications (front end and back end) using the FARM stack.
28小時
本課程專為希望學習Python編程語言的人設計。重點是Python語言，核心庫，以及Python社區開發的最好和最有用的庫的選擇。 Python推動了業務，並被世界各地的科學家使用 - 它是最流行的編程語言之一。
該課程可以使用Python 2.7.x或3.x進行，實踐練習充分利用了該語言的兩個版本。本課程可以在任何操作系統（所有UNIX版本，包括Linux和Mac OS X，以及Microsoft Windows）上提供。
實踐練習約佔課程時間的70％，約30％是演示和演示。整個課程都可以詢問討論和問題。
注意：在提議的課程日期之前，可根據事先要求定制培訓以滿足特定需求。
該課程可以使用Python 2.7.x或3.x進行，實踐練習充分利用了該語言的兩個版本。本課程可以在任何操作系統（所有UNIX版本，包括Linux和Mac OS X，以及Microsoft Windows）上提供。
實踐練習約佔課程時間的70％，約30％是演示和演示。整個課程都可以詢問討論和問題。
注意：在提議的課程日期之前，可根據事先要求定制培訓以滿足特定需求。
28小時
在這一由講師引導的培訓中，參與者將學習高級Python編程技術，包括如何將這種多功能語言應用于解決分布式應用、財務、數據分析和可視化、UI編程及維護腳本等領域的問題。
受衆
- 開發人員
課程形式
- 部分講座、部分討論、練習和大量實操
注意事項
- 如果您想添加、移除或自定義本課程中的任一部分或主題，請聯系我們以作安排。
受衆
- 開發人員
課程形式
- 部分講座、部分討論、練習和大量實操
注意事項
- 如果您想添加、移除或自定義本課程中的任一部分或主題，請聯系我們以作安排。
21小時
In this instructor-led, live training in 台灣, 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小時
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小時
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小時
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小時
這一由講師引導的培訓是基于Al Sweigart所著的知名書籍——“用Python自動化枯燥的事物（Automate the Boring Stuff with Python）”。它針對初學者，通過實際操作練習和討論涵蓋了Python編程的基本概念。重點在于學習編寫代碼以顯著提高辦公效率。
在本次培訓結束後，參與者將知道如何用Python進行編程，並將這項新技能應用于：
- 通過編寫簡單的Python程序來自動執行任務。
- 編寫可以使用“正則表達式”進行文本模式識別的程序。
- 以編程方式生成和更新Excel電子表格。
- 解析PDF和Word文檔。
- 抓取網站，並從線上來源提取信息。
- 編寫發送電子郵件通知的程序。
- 使用Python的調試工具來快速解決錯誤。
- 以編程方式控制鼠標和鍵盤，以執行點擊和輸入。
受衆
- 希望學習用Python編程的非程序員
- 希望優化辦公效率的專業人士和公司團隊
- 希望自動化繁瑣程序和工作流程的經理
課程形式
- 部分講座、部分討論、練習和大量實操
在本次培訓結束後，參與者將知道如何用Python進行編程，並將這項新技能應用于：
- 通過編寫簡單的Python程序來自動執行任務。
- 編寫可以使用“正則表達式”進行文本模式識別的程序。
- 以編程方式生成和更新Excel電子表格。
- 解析PDF和Word文檔。
- 抓取網站，並從線上來源提取信息。
- 編寫發送電子郵件通知的程序。
- 使用Python的調試工具來快速解決錯誤。
- 以編程方式控制鼠標和鍵盤，以執行點擊和輸入。
受衆
- 希望學習用Python編程的非程序員
- 希望優化辦公效率的專業人士和公司團隊
- 希望自動化繁瑣程序和工作流程的經理
課程形式
- 部分講座、部分討論、練習和大量實操
21小時
在這一由講師引導的現場培訓中，參與者將學習Python中最相關及最尖端的機器學習技術，因爲它們構建了一系列涉及圖像、音樂、文本和財務數據的演示應用程序。
在本次培訓結束後，參與者將能夠：
- 運用用于解決複雜問題的機器學習算法和技術
- 將深度學習和半監督學習應用于涉及圖像、音樂、文本和財務數據的應用程序
- 推動Python算法達到其最大潛力
- 使用例如NumPy和Theano的庫和包
受衆
- 開發人員
- 分析師
- 數據科學家
課程形式
- 部分講座、部分討論、練習和大量實操
在本次培訓結束後，參與者將能夠：
- 運用用于解決複雜問題的機器學習算法和技術
- 將深度學習和半監督學習應用于涉及圖像、音樂、文本和財務數據的應用程序
- 推動Python算法達到其最大潛力
- 使用例如NumPy和Theano的庫和包
受衆
- 開發人員
- 分析師
- 數據科學家
課程形式
- 部分講座、部分討論、練習和大量實操
14小時
Pandas是一個Python包，它提供了用于處理結構化（表格式，多維，可能異構）和時間序列數據的數據結構。
21小時
單元測試是一種測試方法，它通過修改其屬性或觸發事件來測試源代碼的各個單元，以確認結果是否如預期的那樣。 PyTest是一個全功能，獨立于API的，靈活且可擴展的測試框架，具有先進的全功能夾具模型。 在這個有指導意義的實時培訓中，參與者將學習如何使用PyTest編寫簡潔，可維護的測試，這些測試是優雅，富有表現力和可讀性的。 在培訓結束後，參與者將能夠： 編寫可讀和可維護的測試，而不需要樣板代碼使用夾具模型編寫小測試擴展到應用程序，包和庫的複雜功能測試理解並應用PyTest的特性，如挂鈎，聲明重寫和插件通過在多個處理器上並行運行測試來縮短測試時間在持續集成環境中運行測試，以及其他工具，如tox，mock，coverage，unittest，doctest和Selenium 使用Python來測試nonPython應用程序 聽衆 軟件測試人員 課程的格式 部分講座，部分討論，練習和沈重的練習
14小時
This instructor-led, live training in 台灣 (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小時
本課程的目的是提供在實踐中應用機器學習方法的一般熟練程度。通過使用 Python 程式設計語言及其各種庫, 並基於大量的實際示例, 本課程教授如何使用機器學習最重要的構建塊, 如何做出資料建模決策, 解釋輸出並驗證結果
我們的目標是讓您能夠自信地理解和使用機器學習工具箱中最基本的工具, 並避免資料科學應用的常見陷阱。
我們的目標是讓您能夠自信地理解和使用機器學習工具箱中最基本的工具, 並避免資料科學應用的常見陷阱。
28小時
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小時
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小時
地理信息系統（ GIS ）是一種旨在捕獲，存儲，操縱，分析，管理和呈現空間或地理數據的系統。縮略詞GIS有時用於地理信息科學（ GIS科學），指的是研究地理信息系統的學科，是更廣泛的地理信息學學科的一個大領域。
在過去的二十年中， Python與GIS的使用大大增加，特別是在2000年引入了Python 2.0系列，其中包括許多新的編程功能，使語言更容易部署。從那時起， Python不僅被用於商業GIS例如Esri的產品，還被用於開源平台，包括作為Q GIS和GRASS的一部分。事實上，今天的Python是迄今為止GIS用戶和程序員使用最廣泛的語言。
該程序涵蓋了Python及其高級庫（如geopandas，pysal，bokeh和osmnx）的使用，以實現您自己的GIS功能。該程序還包括圍繞Arc GIS API和Q GIS toolboox的入門模塊。
在過去的二十年中， Python與GIS的使用大大增加，特別是在2000年引入了Python 2.0系列，其中包括許多新的編程功能，使語言更容易部署。從那時起， Python不僅被用於商業GIS例如Esri的產品，還被用於開源平台，包括作為Q GIS和GRASS的一部分。事實上，今天的Python是迄今為止GIS用戶和程序員使用最廣泛的語言。
該程序涵蓋了Python及其高級庫（如geopandas，pysal，bokeh和osmnx）的使用，以實現您自己的GIS功能。該程序還包括圍繞Arc GIS API和Q GIS toolboox的入門模塊。
28小時
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小時
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小時
In this instructor-led, live training in 台灣 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小時
Python是一種高級編程語言，以其清晰的語法和代碼可讀性而聞名。 Excel是Microsoft開發的電子表格應用程序，廣泛應用於許多行業。將Python添加到Excel使其成為數據分析的強大工具。
在這個以講師為主導的現場培訓中，參與者將學習如何結合Python和Excel的功能。
在培訓結束時，參與者將能夠：
- 安裝和配置用於集成Python和Excel包
- 使用Python讀取，寫入和操作Excel文件
- 從Excel調用Python函數
聽眾
- 開發商
- 程序員
課程形式
- 部分講座，部分討論，練習和繁重的實踐練習
注意
- 要申請本課程的定制培訓，請聯繫我們安排。
在這個以講師為主導的現場培訓中，參與者將學習如何結合Python和Excel的功能。
在培訓結束時，參與者將能夠：
- 安裝和配置用於集成Python和Excel包
- 使用Python讀取，寫入和操作Excel文件
- 從Excel調用Python函數
聽眾
- 開發商
- 程序員
課程形式
- 部分講座，部分討論，練習和繁重的實踐練習
注意
- 要申請本課程的定制培訓，請聯繫我們安排。
14小時
In this instructor-led, live training in 台灣, 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小時
This instructor-led, live training in 台灣 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.
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.
21小時
PyQt 是一個跨平台庫, 用于爲 Python 應用程序開發 Gui (圖形用戶界面)。它將 Python 與 Qt GUI 工具包接口.
本教師指導的現場培訓 (現場或遠程) 針對的是希望使用 Python 和 Qt UI 框架對具有視覺吸引力的軟件應用程序進行編程的人
。
到本次培訓結束時, 學員將能夠:
- 設置包含所有所需庫、包和框架的開發環境。
- 創建一個桌面或服務器應用程序, 其用戶界面功能流暢且具有視覺吸引力.
- 實現各種 UI 元素和效果, 包括小部件、圖表、圖層等, 以實現最大的可用性效果。
- 在設計和開發階段實施良好的 UI 設計和代碼組織。
- 測試和調試應用程序。
課程 格式
- 互動講座和討論.
- 大量的練習和練習
- 在現場實驗室環境中的實際實現。
課程自定義選項
- 本課程可用于在 Windows、Linux 和 Mac OS 上進行開發.
- 使用所有軟件的最新版本, 例如, 本文撰寫時的 PyQt 5 等
- 要要求本課程的定制培訓, 請聯系我們安排
本教師指導的現場培訓 (現場或遠程) 針對的是希望使用 Python 和 Qt UI 框架對具有視覺吸引力的軟件應用程序進行編程的人
。
到本次培訓結束時, 學員將能夠:
- 設置包含所有所需庫、包和框架的開發環境。
- 創建一個桌面或服務器應用程序, 其用戶界面功能流暢且具有視覺吸引力.
- 實現各種 UI 元素和效果, 包括小部件、圖表、圖層等, 以實現最大的可用性效果。
- 在設計和開發階段實施良好的 UI 設計和代碼組織。
- 測試和調試應用程序。
課程 格式
- 互動講座和討論.
- 大量的練習和練習
- 在現場實驗室環境中的實際實現。
課程自定義選項
- 本課程可用于在 Windows、Linux 和 Mac OS 上進行開發.
- 使用所有軟件的最新版本, 例如, 本文撰寫時的 PyQt 5 等
- 要要求本課程的定制培訓, 請聯系我們安排
14小時
This instructor-led, live training in 台灣 (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小時
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小時
In this instructor-led, live training in 台灣, 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小時
This instructor-led, live training in 台灣 (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.
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