Python Training in Hsinchu

Python serves as the foundational language driving the development and coordination of autonomous AI agents. This course emphasizes practical implementation using contemporary SDKs and frameworks such as LangChain and AutoGen to construct, connect, and manage agent workflows.

This instructor-led, live training (available both online and onsite) is designed for intermediate-level backend engineers, platform engineers, and ML engineers who are interested in implementing and orchestrating autonomous agents using Python tools and APIs.

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

• Set up and configure Python-based environments for agentic systems.
• Utilize popular agent SDKs like LangChain and AutoGen to develop functional agents.
• Integrate various tools and APIs to enhance agent capabilities.
• Coordinate multi-agent workflows and communication patterns.
• Apply best practices for debugging, testing, and maintaining agentic codebases.

Format of the Course

• Interactive lectures and discussions.
• Hands-on programming exercises and live demonstrations.
• Practical projects building end-to-end agent workflows.

Course Customization Options

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

This course provides hands-on engineering techniques for designing, building, testing, and deploying autonomous systems using Python. It covers the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production considerations.

This instructor-led, live training (available both online and onsite) is designed for intermediate to advanced ML engineers, AI developers, and software engineers who aim to build robust, production-ready autonomous agents using Python.

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

• Design and implement the agent loop and decision-making processes.
• Integrate external tools and APIs to enhance agent capabilities.
• Implement short-term and long-term memory architectures for agents.
• Coordinate multi-step orchestrations and ensure agent composability.
• Apply best practices for safety, access control, and observability in deployed agents.

Format of the Course

• Interactive lectures and discussions.
• Hands-on labs for building agents using Python and popular SDKs.
• Project-based exercises that result in deployable prototypes.

Course Customization Options

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

Artificial Intelligence with Python involves the creation of intelligent systems utilizing Python’s rich ecosystem of AI and machine learning libraries.

This instructor-led, live training (available both online and onsite) is designed for intermediate-level Python programmers who are interested in designing, implementing, and deploying AI solutions using Python.

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

• Implement AI algorithms using Python’s core AI libraries.
• Work with supervised, unsupervised, and reinforcement learning models.
• Integrate AI solutions into existing applications and workflows.
• Evaluate model performance and optimize for accuracy and efficiency.

Format of the Course

• Interactive lecture and discussion.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

This instructor-led, live training in Hsinchu (online or onsite) is aimed at intermediate-level Python developers who wish to enhance their Python development experience using AWS Cloud9.

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

• Set up and configure AWS Cloud9 for Python development.
• Understand the AWS Cloud9 IDE interface and features.
• Write, debug, and deploy Python applications in AWS Cloud9.
• Collaborate with other developers using the AWS Cloud9 platform.
• Integrate AWS Cloud9 with other AWS services for advanced deployments.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at expert-level data analysts who wish to leverage Python's data analysis capabilities within Power BI, enhancing their ability to analyze and visualize data effectively.

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

• Learn how Python can be integrated into Power BI for data analysis.
• Use Python scripts to load, clean, and preprocess data within the Power BI environment.
• Enhance data visualization capabilities by creating custom and interactive visualizations using Python.
• Acquire advanced data analysis skills using Python.

Python is a versatile programming language widely utilized for data manipulation, automation, and analytics. Libraries such as Pandas and Polars offer robust, practical tools for handling large-scale tabular data.

This instructor-led, live training (available online or onsite) is designed for professionals at the beginner to intermediate level who aim to apply Python for everyday data analysis, file processing, and process automation using Pandas and Polars.

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

• Utilize Python to read, transform, and write CSV and Excel files.
• Execute common data cleaning and transformation tasks with Pandas and Polars.
• Automate repetitive data processes through Python scripts.
• Create simple scripts into executables and adhere to best practices for projects.

Format of the Course

• Interactive coding demonstrations and concise lectures.
• Hands-on exercises with guided code examples.
• Practical mini-projects to automate real-world tasks.

Course Customization Options

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

This instructor-led, live training in Hsinchu (online or onsite) is aimed at experienced developers who wish to gain a comprehensive understanding of Python programming and its applications in cybersecurity.

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

• Use Python programming for defensive cybersecurity.
• Understand and use Python for ethical offensive techniques and digital forensics tasks.
• Recognize legal and ethical considerations surrounding offensive cybersecurity and vulnerability disclosure.

This intensive, hands-on course delves into advanced Python techniques, engineering best practices, and commonly used design patterns to help build maintainable, testable, and high-performance Python applications. It emphasizes modern tooling, typing, concurrency models, architecture patterns, and deployment-ready workflows.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced-level Python developers who wish to adopt professional practices and patterns for production-grade Python systems.

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

• Utilize Python typing, dataclasses, and type-checking to enhance code reliability.
• Apply design patterns and architecture principles to structure robust applications.
• Correctly implement concurrency and parallelism using asyncio and multiprocessing.
• Create well-tested code with pytest, property-based testing, and CI pipelines.
• Profile, optimize, and secure Python applications for production use.
• Package, distribute, and deploy Python projects using modern tools and containers.

Format of the Course

• Interactive lectures and short demonstrations.
• Hands-on labs and coding exercises each day.
• A capstone mini-project that integrates patterns, testing, and deployment.

Course Customization Options

• To request a customized training or to focus on specific areas (data, web, or infrastructure), please contact us to arrange.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at beginner-level developers and data analysts who wish to learn Python programming from scratch using Google Colab.

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

• Understand the basics of Python programming language.
• Implement Python code in Google Colab environment.
• Utilize control structures to manage the flow of a Python program.
• Create functions to organize and reuse code effectively.
• Explore and use basic libraries for Python programming.

This instructor-led, live training in (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.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at beginner-level to intermediate-level and potentially advanced-level robotics developers who wish to learn how to use ROS to program mobile robots using Python.

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

• Set up a development environment that includes ROS, Python, and a mobile robot platform.
• Create and run ROS nodes, topics, services, and actions using Python.
• Use ROS tools and utilities to monitor and debug ROS applications.
• Use ROS packages and libraries to perform common tasks for mobile robots.
• Integrate ROS with other frameworks and tools.
• Troubleshooting and debugging ROS applications.

This course is tailored for individuals eager to master the Python programming language. It focuses on both the Python language itself and its core libraries, along with an in-depth exploration of the most beneficial libraries contributed by the Python community. Python is widely used across businesses and scientific communities globally, making it one of the most sought-after programming languages.

The course will utilize the latest version of Python 3.x, featuring practical exercises that fully leverage its capabilities. This course can be conducted on any operating system, including various versions of UNIX (such as Linux and Mac OS X) and Microsoft Windows.

Practical exercises account for approximately 70% of the course time, while demonstrations and presentations make up around 30%. Participants are encouraged to ask questions and engage in discussions throughout the session.

Note: The training can be customized to meet specific requirements with prior notice before the scheduled course date.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at developers who wish to 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.

This course is tailored for individuals who are keen to master the Python programming language. The focus lies on understanding the Python language itself, its core libraries, and the selection of top-notch and highly useful libraries created by the Python community. Python is a driving force in business and is widely utilized by scientists globally, making it one of the most popular programming languages.

This training course will assist participants in preparing for web application development using Python programming, along with data analytics. Effective data visualization serves as a valuable tool for top management in making informed decisions.

The objective of this course is to equip participants with a foundational proficiency in applying Machine Learning techniques in real-world scenarios. Using the Python programming language and its diverse libraries, along with numerous practical examples, the course instructs students on how to utilize key components of Machine Learning, make informed data modeling decisions, interpret algorithm outputs, and validate results.

Our aim is to provide you with the skills necessary to confidently understand and use the essential tools from the Machine Learning toolkit, while also helping you avoid common pitfalls in Data Science applications.

This instructor-led, live training in Hsinchu 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.

In this instructor-led, live training in Hsinchu, 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.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.

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

• Set up a development environment that includes Python, Pandas, and NumPy.
• Create a data analysis application using Pandas and NumPy.
• Perform advanced data wrangling, sorting, and filtering operations.
• Conduct aggregate operations and analyze time series data.
• Visualize data using Matplotlib and other visualization libraries.
• Debug and optimize their data analysis code.

The objective of this course is to equip participants with a comprehensive proficiency in applying Machine Learning methods in real-world scenarios. By utilizing the Python programming language and its diverse libraries, and through a range of practical examples, the course instructs students on how to effectively use the key components of Machine Learning, make informed data modeling decisions, interpret algorithm outputs, and validate results.

Our aim is to provide you with the skills necessary to confidently understand and utilize the most essential tools from the Machine Learning toolkit, while also helping you avoid common pitfalls in Data Science applications.

Python has become an immensely popular programming language in the financial sector, adopted by major investment banks and hedge funds. It is used to develop a broad spectrum of financial applications, from core trading systems to risk management solutions.

In this instructor-led, live training, participants will learn how to use Python to create practical applications that address various finance-related challenges.

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

• Understand the basics of the Python programming language
• Download, install, and maintain the best development tools for building financial applications in Python
• Select and use the most appropriate Python packages and techniques to organize, visualize, and analyze financial data from diverse sources (CSV, Excel, databases, web, etc.)
• Develop applications that tackle issues 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 extensive hands-on practice

Note

• This training is designed to provide solutions for some of the key challenges faced by finance professionals. However, if you have a specific topic, tool, or technique that you would like to add or explore further, please contact us to arrange.

This is a five-day introductory course on Data Science and Artificial Intelligence (AI).

The course includes examples and exercises that are conducted using Python.

This is a four-day course designed to introduce artificial intelligence and its applications using the Python programming language. Participants have the option to extend their learning with an extra day dedicated to working on an AI project upon completing the course.

Selenium is an open-source framework designed for automating the testing of web applications across various browsers. With the release of Selenium 4, it now offers enhanced WebDriver APIs, native relative locators, and improved grid support. Python stands out as a powerful choice for test automation due to its simplicity and robust integration with frameworks like Pytest, enabling the development of scalable and maintainable test automation suites.

This instructor-led, live training (available both online and on-site) is tailored for beginner to intermediate testers and developers who are interested in using Selenium with Python to automate web application testing in real-world scenarios.

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

• Install and configure Selenium with Python in a test environment.
• Develop robust test automation scripts using Selenium WebDriver and Pytest.
• Implement Page Object Model (POM) for creating maintainable test frameworks.
• Execute tests across multiple browsers using Selenium Grid.
• Integrate automated tests into CI/CD pipelines.
• Troubleshoot common issues and apply best practices to ensure automation stability.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

In this instructor-led, live training in Hsinchu (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.

This instructor-led, live training in Hsinchu (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.

This instructor-led, live training in Hsinchu (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.

In this instructor-led, live training, participants will delve into advanced Python programming techniques, learning how to leverage this versatile language to address challenges in areas such as distributed applications, data analysis and visualization, user interface (UI) development, and maintenance scripting.

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and hands-on practice.
• Practical implementation in a live-lab environment.

Course Customization Options

• If you have specific sections or topics you'd like to add, remove, or customize within this course, please contact us to discuss your requirements.

This instructor-led, live training in Hsinchu (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.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at data scientists and software engineers who wish to use Dask with the Python ecosystem to build, scale, and analyze large datasets.

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

• Set up the environment to start building big data processing with Dask and Python.
• Explore the features, libraries, tools, and APIs available in Dask.
• Understand how Dask accelerates parallel computing in Python.
• Learn how to scale the Python ecosystem (Numpy, SciPy, and Pandas) using Dask.
• Optimize the Dask environment to maintain high performance in handling large datasets.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.

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

• Employ algorithms to buy and sell securities at specialized increments rapidly.
• Reduce costs associated with trade using algorithmic trading.
• Automatically monitor stock prices and place trades.

ChatBots are computer programs designed to automatically simulate human responses through chat interfaces. These programs help organizations enhance their operational efficiency by offering users faster and more convenient interaction options.

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

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

• Grasp the core principles of building chatbots
• Construct, test, deploy, and troubleshoot various chatbots using Python

Audience

• Developers

Format of the course

• A combination of lectures, discussions, exercises, and extensive hands-on practice

Note

• For a customized training session for this course, please contact us to arrange.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at intermediate-level developers who wish to use CUDA to build Python applications that run in parallel on NVIDIA GPUs.

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

• Use the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
• Create, compile and launch custom CUDA kernels.
• Manage GPU memory.
• Convert a CPU based application into a GPU-accelerated application.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs easier and faster.

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

• Set up the necessary development environment to develop APIs with Python and FastAPI.
• Create APIs quicker and easier using the FastAPI library.
• Learn how to create data models and schemas based on Pydantic and OpenAPI.
• Connect APIs to a database using SQLAlchemy.
• Implement security and authentication in APIs using the FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at data scientists who wish to use TensorFlow to analyze potential fraud data.

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

• Create a fraud detection model in Python and TensorFlow.
• Build linear regressions and linear regression models to predict fraud.
• Develop an end-to-end AI application for analyzing fraud data.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at network engineers who wish to maintain, manage, and design computer networks with Python.

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

• Optimize and leverage Paramiko, Netmiko, Napalm, Telnet, and pyntc for network automation with Python.
• Master multi-threading and multiprocessing in network automation.
• Use GNS3 and Python for network programming.

In this instructor-led, live training in Hsinchu, participants will learn how to use Python to produce high-quality natural language text by building their own NLG system from scratch. Case studies will also be examined and the relevant concepts will be applied to live lab projects for generating content.

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

• Use NLG to automatically generate content for various industries, from journalism, to real estate, to weather and sports reporting.
• Select and organize source content, plan sentences, and prepare a system for automatic generation of original content.
• Understand the NLG pipeline and apply the right techniques at each stage.
• Understand the architecture of a Natural Language Generation (NLG) system.
• Implement the most suitable algorithms and models for analysis and ordering.
• Pull data from publicly available data sources as well as curated databases to use as material for generated text.
• Replace manual and laborious writing processes with computer-generated, automated content creation.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at penetration testers who wish to penetrate test networks in Kali Linux using Python.

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

• Create Python programs to seek network vulnerabilities.
• Explore and use Kali web shells and shellcode in exploits.
• Apply various Kali tools for penetration testing.
• Exploit systems with Python.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at developers who wish to use Python as the server-side language to create a web application. Various techniques and frameworks will be explored to arrive at the most suitable one for a given problem.

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

• Install and configure Python packages and frameworks.
• Set up the appropriate development environment to optimize the coding process.
• Write the code needed to enable common functionality expected by end users of an application (forms, database queries, calculations, etc.)
• Select from a number of popular frameworks such as Django and Flask to automate redundant tasks and reduce development time.

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

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

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

• Grasp the fundamentals of Python programming
• Apply Python to financial applications, including implementing mathematical techniques, stochastic processes, and statistical methods
• Develop financial algorithms using high-performance Python

Audience

• Developers
• Quantitative analysts

Format of the course

• A combination of lectures, discussions, exercises, and extensive hands-on practice

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

In this instructor-led, live training, participants will learn the fundamentals of Computer Vision as they work through the creation of several simple Computer Vision applications using Python.

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

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

Audience

• Python programmers interested in Computer Vision

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

This course provides an introduction to the Python programming language. Upon completing this class, students will be able to write sophisticated Python programs that address a broad range of topics. The curriculum covers essential components of the language, working with a professional Integrated Development Environment (IDE), control flow structures, string manipulation, input/output operations, collections, classes, modules, and regular expressions. The course is enriched with numerous hands-on labs, solutions, and code examples.

After completing the course, students will be able to demonstrate their knowledge and understanding of Python security principles.

This instructor-led, live training (online or onsite) is designed for developers and data scientists who want to use spaCy to process large volumes of text to uncover patterns and gain insights.

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

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

Format of the Course

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

Course Customization Options

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

Tableau is a powerful tool for business intelligence and data visualization. Python, a widely used programming language, supports a broad range of statistical and machine learning techniques. When Tableau's robust data visualization capabilities are combined with Python's advanced machine learning features, developers can quickly build sophisticated data analytics applications tailored to various business needs.

In this instructor-led, live training, participants will learn how to integrate Tableau and Python to perform advanced analytics. The integration of Tableau and Python is achieved through the TabPy API.

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

• Integrate Tableau and Python using the TabPy API
• Leverage the combined power of Tableau and Python to analyze complex business scenarios with minimal Python code

Audience

• Developers
• Data scientists

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

In Python Machine Learning, the Text Summarization feature can read input text and generate a concise summary. This functionality is accessible both from the command line and as a Python API or library. One of its exciting applications is the rapid creation of executive summaries, which is especially beneficial for organizations that need to review large volumes of text data before producing reports and presentations.

During this instructor-led, live training, participants will learn how to use Python to create a simple application that automatically generates summaries of input text.

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

• Utilize a command-line tool for summarizing text.
• Design and develop Text Summarization code using Python libraries.
• Evaluate three Python summarization libraries: sumy 0.7.0, pysummarization 1.0.4, readless 1.0.17

Audience

• Developers
• Data Scientists

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

This instructor-led, live training in Hsinchu (online or onsite) is aimed at data scientists and developers who wish to use Modin to build and implement parallel computations with Pandas for faster data analysis.

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

• Set up the necessary environment to start developing Pandas workflows at scale with Modin.
• Understand the features, architecture, and advantages of Modin.
• Know the differences between Modin, Dask, and Ray.
• Perform Pandas operations faster with Modin.
• Implement the entire Pandas API and functions.