オンラインまたはオンサイトのインストラクター主導のライブPythonトレーニングコースでは、Pythonプログラミング言語のさまざまな側面を実践的に実践して実演します。取り上げるトピックのいくつかには、Pythonプログラミング、高度なPythonプログラミング、テスト自動化のためのPython、Pythonのスクリプト作成と自動化、およびFinance、Banking、Insuranceなどの分野におけるデータ分析のためのPythonとBig Dataアプリケーションの基礎が含まれます。
NobleProg Pythonトレーニングコースでは、機械学習およびディープラーニングのためのPythonライブラリおよびフレームワークの使用に関する初級コースおよび上級コースもカバーしています。
Pythonトレーニングは、「オンラインライブトレーニング」または「オンサイトライブトレーニング」として利用できます。オンラインライブトレーニング（別名「リモートライブトレーニング」）は、インタラクティブなリモートデスクトップで行われます。現地でのライブトレーニングは、日本のお客様のオフィスまたは日本のNobleProg提携の企業トレーニングセンターにて実施が可能です。
NobleProg - 現地のトレーニングプロバイダー
お客様の声
私は演習を好み、 Python隅々について学びました
Connor Brierley-Green
コース: Python Programming
Machine Translated
ジョーイはプログラミングに関する熱狂的な熱意を持っています。そして、彼は、私たちのニーズと興味をその場で適応させることに非常に恵まれました。
Randy Enkin
コース: Python Programming
Machine Translated
多くの例がわかりやすくなりました。
Lingmin Cao
コース: Python Programming
Machine Translated
オペレータの総合的な知識 - 私たちの質問のすべてが私の期待を覆す答えを与えました...講師は偉大な議論を行います...彼は忍耐に欠けていません...
Łukasz Matulewicz
コース: Programowanie w języku Python
Machine Translated
講師に関する豊富な知識、ツールの多様性、およびトピックへの実践的なアプローチ
Magdalena Stupak
コース: Programowanie w języku Python
Machine Translated
トレーナーの優れた知識、翻訳方法
Renata Cylejowska
コース: Programowanie w języku Python
Machine Translated
カスタマイズが真剣に行われたという事実。
jurgen linsen
コース: Python Programming
Machine Translated
私が唯一の参加者だったので、トレーニングは私のニーズに合わせることができました。
Kevin THIERRY
コース: Web Development with Web2Py
Machine Translated
私は練習が好きでした。
Office for National Statistics
コース: Natural Language Processing with Python
Machine Translated
私は助けてとても親切だった。
Natalia Machrowicz
コース: Python Programming
Machine Translated
私たちは実践的な演習を行いました（私たちが書いたスクリプトは日々の仕事に使用できます）。コースをとても面白くしました。私はトレーナーが自分の知識を共有する方法も好きでした。彼は非常にアクセス可能な方法でそれをやった。
Malwina Sawa
コース: Python Programming
Machine Translated
重要なトピックを記憶/再現するための非常に良いアプローチ。非常に良い "ウォームアップ"演習。
コース: Python Programming
Machine Translated
*楽しい練習。 *すばやくより高度なトピックに移動しました。 *トレーナーはフレンドリーで、乗りやすい*チームのニーズに合わせたカスタマイズコース。
Matthew Lucas
コース: Python Programming
Machine Translated
私はコース/レッスンに特定のトピックを追加するための柔軟性を楽しんだ。
Marc Ammann
コース: Python Programming
Machine Translated
私はそれがとても好きです。
蒙 李
コース: Machine Learning Fundamentals with Python
Machine Translated
トレーナーは一人ひとりを見て助けて
Szymon Wolny
コース: Programowanie w języku Python
Machine Translated
対象に最適な一連のエクササイズ。簡単で「星付き」のエクササイズ
Motorola Solutions Systems Polska Sp. z o.o
コース: Programowanie w języku Python
Machine Translated
バランスのとれた理論/演習、受講者への講義のレベルの調整、経験の豊富さ、Jupiter Notebookを使用して理論を実際に示すための非常に大きなプラス。私はまた、トレーニングの最初の部分の後に匿名のフィードバックを集めるのが好きでした - 翌日、私たちの提案に従ってすべてが準備されました。
Motorola Solutions Systems Polska Sp. z o.o
コース: Programowanie w języku Python
Machine Translated
教師のコミットメント、準備、リスナーへのアプローチ、すべてのあいまいさを説明する意思
Małgorzata Konior
コース: Programowanie w języku Python
Machine Translated
たとえ彼が助けを求めないで、そして演習のレベルをチェックする時でさえ、リーダーが皆に近づくこと。
Agnieszka Bielak
コース: Programowanie w języku Python
Machine Translated
トレーナーは与えられた問題について非常に短い理論を提示し、私たちはすぐに練習に行きました。これは、与えられたタスクにどれだけの時間を費やす必要があるか、および他の誰が解決策に問題を抱えているかに関する情報をトレーナーに提供します。
Motorola Solutions Systems Polska Sp. z o.o
コース: Programowanie w języku Python
Machine Translated
誰かがそれを要求しなかったとしても、彼がそのタスクを進めていないことをあなたは見ることができました、Krzysztofは上がってきて、そして巧みに助言することができました
Motorola Solutions Systems Polska Sp. z o.o
コース: Programowanie w języku Python
Machine Translated
指揮の仕方、演習、そしてすべてが好きだったので、私はそのようなトレーナーに来たことをとても嬉しく思います
Maksym Kolodiy
コース: Programowanie w języku Python
Machine Translated
演習の実際の例
Motorola Solutions Systems Polska Sp. z o.o
コース: Programowanie w języku Python
Machine Translated
定期的に作成されたトレーニング教材（Jupyter）の入手可能性 - コース中に落ちた質問に応じてノートブックを更新する。疑問を払拭し、すべての質問に答えます。
Motorola Solutions Systems Polska Sp. z o.o
コース: Programowanie w języku Python
Machine Translated
アクセシビリティと教材提供の興味深い方法
Motorola Solutions Systems Polska Sp. z o.o
コース: Programowanie w języku Python
Machine Translated
xlsxファイルとcsvファイルで作業する
Łukasz Olczyk
コース: Python: Automate the boring stuff
Machine Translated
機械学習の話題、特にニューラルネットワークについて詳しく解説します。話題の多くを解読しました。
Sacha Nandlall
コース: Python for Advanced Machine Learning
Machine Translated
カスタマイズされた社内のファイル処理とデータ分析が好きでした。
Glycom A/S
コース: Data Analysis in Python using Pandas and Numpy
Machine Translated
ケーススタディは、業界でPythonを適用する方法を理解するのに役立ちました。エクササイズ中にトレーナーの助けを本当に感謝します
Rajiv Dhingra - TCS
コース: Python Programming
Machine Translated
私たちはPHP開発者であるため、彼は状況を理解し、ゆっくりと物事をマッピングできるようにしました。私は例と彼が付け加えたユーモアが好きだった。
Soumya Tyagi - TCS
コース: Python Programming
Machine Translated
例として私たち自身のデータを使っていることを楽しんだ。
Glycom A/S
コース: Data Analysis in Python using Pandas and Numpy
Machine Translated
全て
MTU Aero Engines Polska Sp. z o. o.
コース: Programowanie w języku Python
Machine Translated
興味深い問題
MTU Aero Engines Polska Sp. z o. o.
コース: Programowanie w języku Python
Machine Translated
さまざまな準備された問題と例。
MTU Aero Engines Polska Sp. z o. o.
コース: Programowanie w języku Python
Machine Translated
トレーニングはプレゼンテーションスタイルではありません。彼はトレーナーと一緒にコーディングしていた..
Bhutan Telecom
コース: Web Development with Django
Machine Translated
私はほとんどすべてを楽しんだ。
Thukten Dendup - Bhutan Telecom
コース: Web Development with Django
Machine Translated
その新しい経験、新しいフレームワーク、クラスで学んだレッスンを使って何かを楽しみにしている..
Jigme - Bhutan Telecom
コース: Web Development with Django
Machine Translated
私は本当に多くのラボや実践を楽しんだ。
Vivian Feng - Destination Canada
コース: Data Analysis with SQL, Python and Spotfire
Machine Translated
エクササイズ/ラボは、私たち自身の組織ニーズに合わせて調整されました。
Destination Canada
コース: Data Analysis with SQL, Python and Spotfire
Machine Translated
私は一般的に主題が好きだった。
Destination Canada
コース: Data Analysis with SQL, Python and Spotfire
Machine Translated
トレーナーは本物の言葉の経験を共有していました。本物のプロから学ぶのは素晴らしいことです。
Fednot
コース: Python Programming
Machine Translated
トレーナーは優秀でした。彼はいつも私の質問に答えて、できる限り多くの知識を共有する準備ができていました。
Fahad Malalla - Tatweer Petroleum
コース: Advanced Python
Machine Translated
1：1は非常に集中的ですが、多くのことを学びました。
Karen Dyke - BT
コース: Python: Automate the Boring Stuff
Machine Translated
"プロジェクター上での"エンコーディングの例を重視するのは間違いなくTomのためです。
ADVA OPTICAL NETWORKING SP. ZO O.
コース: Advanced Python
Machine Translated
私は主にその主題を楽しんだ。
Proximus
コース: Python Programming
Machine Translated
練習の仕方は、自分のテンポとアントニオでさらにあなたを助けるためにありました。
Proximus
コース: Python Programming
Machine Translated
私は十分かつ非常に詳細な読み物と例 (スライド) が好きでした。
HC Consumer Finance Philippines, Inc.
コース: Python Programming
Machine Translated
私は純粋に na が好きでした。
HC Consumer Finance Philippines, Inc.
コース: Python Programming
Machine Translated
私が一番気に入っているのは、コース概要のすべてがプロジェクトに役立つものであるということです。
Joanna Marie Escueta - Aarki, Inc.
コース: Python Programming
Machine Translated
重要なトピックを記憶/再現するための非常に良いアプローチ。非常に良い "ウォームアップ"演習。
コース: Python Programming
Machine Translated
Pythonコース概要
コース名
期間
概要
コース名
期間
概要
28 時間
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 時間
In this instructor-led, live training in 日本, 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.
21 時間
In this instructor-led, live training in 日本, 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 時間
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 時間
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 時間
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 時間
This instructor-led, live training in 日本 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.
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.
21 時間
In this instructor-led, live training in 日本, 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.
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.
14 時間
Pandas is a Python package that provides data structures for working with structured (tabular, multidimensional, potentially heterogeneous) and time series data.
21 時間
In this instructor-led, live training in 日本, 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 時間
This instructor-led, live training in 日本 (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 時間
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 時間
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 時間
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 時間
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 時間
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 時間
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 時間
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 時間
In this instructor-led, live training in 日本 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 時間
In this instructor-led, live training in 日本 (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 時間
In this instructor-led, live training in 日本, 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 時間
This instructor-led, live training in 日本 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 時間
This instructor-led, live training in 日本 (online or onsite) is aimed at persons who wish to program a visually attractive software application using Python and the Qt UI framework.
By the end of this training, participants will be able to:
- Set up a development environment that includes all needed libraries, packages and frameworks.
- Create a desktop or server application whose user interface functions smoothly and is visually appealing.
- Implement various UI elements and effects, including widgets, charts, layers, etc. to achieve maximum effect in usability.
- Implement good UI design and code organization during the design and development phase.
- Test and debug the application.
By the end of this training, participants will be able to:
- Set up a development environment that includes all needed libraries, packages and frameworks.
- Create a desktop or server application whose user interface functions smoothly and is visually appealing.
- Implement various UI elements and effects, including widgets, charts, layers, etc. to achieve maximum effect in usability.
- Implement good UI design and code organization during the design and development phase.
- Test and debug the application.
14 時間
This instructor-led, live training in 日本 (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 時間
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 時間
In this instructor-led, live training in 日本, 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 時間
This instructor-led, live training in 日本 (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 時間
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 時間
This instructor-led, live training in 日本 (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 時間
This instructor-led, live training in 日本 (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:
今後のPythonコース
Data Analysis with SQL, Python and Spotfire
07-02-2022 10:00
14 時間
Applied AI from Scratch in Python
08-02-2022 10:00
28 時間
MongoDB for Python Developers
10-02-2022 10:00
14 時間
Data Mining with Python
17-03-2022 10:00
14 時間
Natural Language Processing (NLP) with Python spaCy
23-03-2022 10:00
14 時間
週末Pythonコース, 夜のPythonトレーニング, Pythonブートキャンプ, Python インストラクターよる, 週末Pythonトレーニング, 夜のPythonコース, Python指導, Pythonインストラクター, Pythonレーナー, Pythonレーナーコース, Pythonクラス, Pythonオンサイト, Pythonプライベートコース, Python1対1のトレーニング
.jpg "procter & gamble (p&g)")
_ireland.gif "environmental protection agency (epa) ireland")
.png "european space agency (esa)")
