Python Training in Taipei

Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation using contemporary SDKs and frameworks like LangChain and AutoGen to construct, link, and manage agent workflows.

This instructor-led, live training (available online or onsite) targets intermediate-level backend, platform, and ML engineers seeking to implement and orchestrate autonomous agents using Python tools and APIs.

Upon completing this training, participants will be able to:

• Set up and configure Python-based environments for agentic systems.
• Leverage popular agent SDKs such as LangChain and AutoGen to build functional agents.
• Integrate tools and APIs to expand agent capabilities.
• Orchestrate multi-agent workflows and communication patterns.
• Apply best practices for debugging, testing, and maintaining agentic codebases.

Course Format

• Interactive lectures and discussions.
• Hands-on programming exercises and live demonstrations.
• Practical projects involving the construction of end-to-end agent workflows.

Course Customization Options

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

This course provides practical engineering techniques for designing, building, testing, and deploying agentic (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 (online or onsite) is aimed at intermediate-level to advanced-level ML engineers, AI developers, and software engineers who wish 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 workflows.
• Integrate external tools and APIs to extend agent capabilities.
• Implement short-term and long-term memory architectures for agents.
• Coordinate multi-step orchestrations and agent composability.
• Apply safety, access control, and observability best practices for deployed agents.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs building agents with Python and popular SDKs.
• Project-based exercises that produce deployable prototypes.

Course Customization Options

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

Artificial Intelligence with Python involves building intelligent systems by leveraging Python’s comprehensive ecosystem of AI and machine learning libraries.

This instructor-led live training, available online or onsite, is designed for intermediate-level Python programmers who aim to design, implement, and deploy AI solutions using Python.

Upon completing this training, participants will be capable of:

• Implementing AI algorithms using Python’s core AI libraries.
• Working with supervised, unsupervised, and reinforcement learning models.
• Integrating AI solutions into existing applications and workflows.
• Evaluating model performance and optimizing for accuracy and efficiency.

Course Format

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

Course Customization Options

• To request customized training for this course, please contact us to make arrangements.

This instructor-led, live training in Taipei (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 Taipei (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 used for data manipulation, automation, and analytics. Libraries like Pandas and Polars provide powerful, practical tools for working with tabular data at scale.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish 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:

• Leverage 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.
• Package simple scripts into executables and adhere to best practices for projects.

Format of the Course

• Interactive coding demonstrations and short 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 intensive, hands-on course explores advanced Python techniques, engineering best practices, and commonly utilized design patterns to help you build maintainable, testable, and high-performance Python applications. The curriculum emphasizes modern tooling, type hinting, concurrency models, architectural patterns, and deployment-ready workflows.

Delivered as instructor-led, live training (available online or onsite), this program targets intermediate to advanced Python developers seeking to adopt professional practices and patterns for production-grade Python systems.

Upon completion of this training, participants will be capable of:

• Applying Python typing, dataclasses, and type-checking to enhance code reliability.
• Utilizing design patterns and architectural principles to structure robust applications.
• Correctly implementing concurrency and parallelism using asyncio and multiprocessing.
• Constructing well-tested code through pytest, property-based testing, and CI pipelines.
• Profiling, optimizing, and hardening Python applications for production environments.
• Packaging, distributing, and deploying Python projects using modern tools and containerization.

Course Format

• Interactive lectures complemented by short demonstrations.
• Hands-on labs and coding exercises conducted daily.
• A capstone mini-project that integrates patterns, testing, and deployment strategies.

Customization Options

• To request customized training or specific focus areas (such as data, web, or infrastructure), please contact us to make arrangements.

This instructor-led live training in Taipei (online or onsite) targets beginner-level developers and data analysts interested in learning Python programming from scratch using Google Colab.

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

• Grasp the fundamentals of the Python programming language.
• Write and implement Python code within the Google Colab environment.
• Apply control structures to manage program execution flow.
• Develop functions to organize and reuse code efficiently.
• Explore and utilize essential Python libraries.

This instructor-led live training (online or onsite) is designed for 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 Taipei (online or onsite) targets 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.

Upon completing this training, participants will be able to:

• Establish a development environment that includes ROS, Python, and a mobile robot platform.
• Create and execute ROS nodes, topics, services, and actions using Python.
• Leverage ROS tools and utilities to monitor and debug ROS applications.
• Utilize ROS packages and libraries to accomplish common tasks for mobile robots.
• Integrate ROS with other frameworks and tools.
• Perform troubleshooting and debugging of ROS applications.

This course is tailored for individuals aiming to master the Python programming language. The curriculum emphasizes the Python language itself, its core libraries, and the selection of the most valuable libraries developed by the Python community. Widely used by businesses and scientists globally, Python stands out as one of the most popular programming languages.

The course is delivered using the latest Python 3.x version, leveraging practical exercises to harness its full potential. It can be conducted on any operating system, including various UNIX flavors (such as Linux and macOS) as well as Microsoft Windows.

Practical exercises make up approximately 70% of the course duration, while the remaining 30% consists of demonstrations and presentations. Participants are encouraged to engage in discussions and ask questions throughout the training.

Note: The training content can be customized to meet specific requirements, provided requests are made in advance of the scheduled course date.

This instructor-led, live training in Taipei (online or onsite) is designed for developers who want to master 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 eager to master the Python programming language. The curriculum emphasizes proficiency in Python itself, its core libraries, and the selection of the most valuable and efficient libraries contributed by the Python community. Python is a cornerstone for businesses and is widely adopted by scientists globally, establishing itself as one of the most prominent programming languages in use today.

This instructor-led, live training in Taipei is based on the popular book, "Automate the Boring Stuff with Python" by Al Sweigart. Aimed at beginners, the course 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 Taipei, participants will master the most current and advanced machine learning techniques in Python by developing a series of demonstration applications that process image, music, text, and financial data.

Upon completing this training, participants will be capable of:

• Implementing machine learning algorithms and techniques to address complex problems.
• Applying deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
• Maximizing the potential of Python algorithms.
• Utilizing libraries and packages such as NumPy and Theano.

This instructor-led, live training in Taipei (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.

This course is designed to equip participants with practical proficiency in applying Machine Learning methodologies. Leveraging the Python programming language alongside its extensive ecosystem of libraries, and supported by numerous real-world examples, the curriculum covers the essential components of Machine Learning. Learners will acquire the ability to make informed data modeling decisions, interpret algorithmic outputs, and effectively validate results.

Our objective is to empower you with the confidence to utilize core Machine Learning tools while helping you avoid the frequent pitfalls associated with Data Science applications.

Python has surged in popularity within the financial sector, becoming a staple for leading investment banks and hedge funds. It is widely utilized to construct a diverse array of financial solutions, from core trading platforms to sophisticated risk management systems.

Through this instructor-led live training, participants will learn how to leverage Python to develop practical applications that address specific challenges in the finance industry.

Upon completion of this training, participants will be able to:

• Grasp the core fundamentals of Python programming
• Download, install, and maintain optimal development tools for building financial applications in Python
• Select and employ the most effective Python packages and programming techniques to organize, visualize, and analyze financial data from diverse sources (CSV, Excel, databases, web, etc.)
• Develop applications to solve issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimize Python applications

Audience

• Developers
• Analysts
• Quants

Course Format

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

Note

• This training focuses on providing solutions for key problems encountered by finance professionals. If you have a specific topic, tool, or technique you wish to add or explore in greater depth, please contact us to arrange accordingly.

This course delves into practical methodologies for Data Science and AI utilizing Python. It empowers professionals with the essential skills to explore data, construct machine learning models, and deploy AI-driven applications within business environments. The curriculum covers CRISP-DM workflows, statistical analysis, supervised and unsupervised learning, deep learning with TensorFlow, natural language processing, big data with Spark, and data-driven storytelling. It is ideal for beginners seeking a Python data science certification and career-ready analytics training.

Applied AI from Scratch in Python provides programmers and data analysts with the essential techniques required to construct machine learning solutions from the ground up using Python. The course covers the fundamental principles of supervised learning, including classification and regression, as well as unsupervised learning methods such as clustering and anomaly detection, alongside advanced neural network architectures. It explores proven strategies for utilizing scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate practical AI development. This helps professionals implement functional ML models, assess algorithmic constraints, and complete applied projects designed to solve real-world problems.

Selenium is an open-source framework designed for automating web application testing across various browsers. With the release of Selenium 4, users benefit from enhanced WebDriver APIs, native relative locators, and improved grid support. Python, known for its simplicity, offers robust integration with testing frameworks like Pytest, making it an excellent choice for building scalable and maintainable test automation suites.

This instructor-led live training, available both online and onsite, is tailored for testers and developers at the beginner to intermediate level who aim to utilize Selenium with Python to automate web application testing in real-world scenarios.

Upon completion of this training, participants will be capable of:

• Installing and configuring Selenium with Python within a test environment.
• Developing robust test automation scripts using Selenium WebDriver and Pytest.
• Implementing the Page Object Model (POM) to create maintainable test frameworks.
• Executing tests across multiple browsers via Selenium Grid.
• Integrating automated tests into CI/CD pipelines.
• Troubleshooting common issues and applying best practices for automation stability.

Course Format

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

Course Customization Options

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

This instructor-led, live training in Taipei (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 Taipei (online or onsite) is aimed at individuals who wish to learn just enough Python to start 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 insights from data, including trends in performance, and problematic areas.

Course Overview

This practical training is tailored for professionals with a data engineering background who aim to develop hands-on expertise in artificial intelligence, Python, and large language models. The curriculum emphasizes real-world applications, encompassing model utilization, prompt engineering, and the development of AI-driven solutions. Participants will engage in progressive exercises that advance from foundational concepts to the creation of deployable AI workflows.

Training Format

• In-person classroom instruction

• Instructor-led sessions featuring guided practice

• Interactive discussions and real-world case studies

• Daily hands-on exercises

Course Objectives

• Grasp core AI and machine learning concepts pertinent to contemporary applications

• Enhance Python proficiency for AI development and data workflows

• Comprehend the mechanics of large language models and learn to utilize them effectively

• Design and optimize prompts to ensure reliable outputs

• Construct end-to-end AI solutions utilizing APIs and frameworks

• Integrate AI capabilities into data engineering pipelines

This instructor-led live training in Taipei (online or onsite) is tailored for developers who wish to utilize FastAPI with Python to build, test, and deploy RESTful APIs with greater ease and speed.

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

• Configure the necessary development environment for creating APIs with Python and FastAPI.
• Develop APIs more quickly and effortlessly using the FastAPI library.
• Learn to create data models and schemas based on Pydantic and OpenAPI standards.
• Integrate APIs with databases using SQLAlchemy.
• Implement security measures and authentication within APIs using FastAPI tools.
• Construct container images and deploy web APIs to cloud servers.

This instructor-led, live training in Taipei (online or onsite) is designed for data scientists who wish to utilize TensorFlow for analyzing potential fraud data.

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

• Create a fraud detection model using 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 Taipei (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.

This instructor-led, live training in Taipei (online or onsite) is aimed at business professionals and data analysts with intermediate Python skills who wish to apply Python to automate workflows, analyze business data, and generate dynamic Excel-based reports.

Computer Vision is a discipline dedicated to automatically extracting, analyzing, and interpreting valuable information from digital media. Python, a high-level programming language, is renowned for its clear syntax and high code readability.

Through this instructor-led live training, participants will master the fundamentals of Computer Vision by building a series of simple Computer Vision applications using Python.

Upon completing this training, participants will be able to:

• Grasp the core concepts of Computer Vision
• Leverage Python to execute Computer Vision tasks
• Develop custom systems for face, object, and motion detection

Audience

• Python programmers seeking to specialize in Computer Vision

Course Format

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

This practical course is tailored for Unix and shell users aiming to boost their automation capabilities through Python. Although shell scripting remains effective for straightforward tasks, Python offers substantially enhanced flexibility, readability, and scalability for complex automation, system administration, and DevOps workflows.