Python Training in Busan

Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation by leveraging modern SDKs and frameworks, such as LangChain and AutoGen, to build, connect, and manage complex agent workflows.

This instructor-led, live training (available online or onsite) is designed for intermediate-level backend, platform, and ML engineers looking to implement and orchestrate autonomous agents using Python-based tooling and APIs.

Upon completing this training, participants will be equipped to:

• Establish and configure Python environments tailored for agentic systems.
• Utilize prominent agent SDKs, including LangChain and AutoGen, to develop functional agents.
• Integrate tools and APIs to expand agent capabilities.
• Orchestrate multi-agent workflows and establish 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 focused on building end-to-end agent workflows.

Course Customization Options

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

This course provides practical engineering techniques for designing, building, testing, and deploying agentic (autonomous) systems using Python. It explores key topics such as the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production considerations.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced-level ML engineers, AI developers, and software engineers who want 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 the creation of intelligent systems leveraging Python’s vast ecosystem of AI and machine learning libraries.

This instructor-led live training, available both online and onsite, targets intermediate-level Python programmers who want to design, implement, and deploy 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.
• Lots 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.

This instructor-led, live training in Busan (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 Busan (online or onsite) is designed for 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 using Python scripts.
• Package simple scripts into executables and adhere to project best practices.

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 covers advanced Python techniques, engineering best practices, and commonly used design patterns to 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 (online or onsite) is aimed at intermediate-level 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:

• Apply Python typing, dataclasses, and type-checking to increase code reliability.
• Use design patterns and architecture principles to structure robust applications.
• Implement concurrency and parallelism correctly using asyncio and multiprocessing.
• Build well-tested code with pytest, property-based testing, and CI pipelines.
• Profile, optimize, and harden Python applications for production.
• Package, distribute, and deploy Python projects using modern tools and containers.

Format of the Course

• Interactive lectures and short demos.
• Hands-on labs and coding exercises each day.
• Capstone mini-project integrating patterns, testing, and deployment.

Course Customization Options

• To request a customized training or focus area (data, web, or infra), please contact us to arrange.

This instructor-led live training in Busan (online or onsite) is designed for 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:

• Grasp the fundamental concepts of the Python programming language.
• Write and execute Python code within the Google Colab environment.
• Apply control structures to manage program flow effectively.
• Develop functions to organize and reuse code efficiently.
• Explore and utilize essential libraries for Python development.

This instructor-led, live training (available online or onsite) targets developers who intend to use the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications.

By the conclusion 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 Busan (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. The curriculum focuses on the Python language itself, its core libraries, and the selection of the most effective and valuable libraries contributed by the Python community. Python powers businesses globally and is widely utilized by scientists around the world, making it one of the most popular programming languages today.

The course can be delivered using the latest Python 3.x version, featuring practical exercises that leverage its full capabilities. It is compatible with any operating system, including all UNIX variants (such as Linux and Mac OS X) as well as Microsoft Windows.

Approximately 70% of the course time is dedicated to practical exercises, while the remaining 30% covers demonstrations and presentations. Participants are encouraged to engage in discussions and ask questions throughout the course.

Note: The training content can be customized to meet specific requirements upon prior request before the proposed course date.

This instructor-led, live training in Busan (online or onsite) is designed for developers seeking to master advanced Python programming techniques. It covers how to leverage this versatile language to address challenges in areas such as distributed applications, data analysis and visualization, UI development, and maintenance scripting.

This course is tailored for individuals eager to master the Python programming language. The curriculum focuses on the Python language itself, its core libraries, and the selection of the most valuable tools developed by the vibrant Python community. Python powers businesses globally and is widely adopted by scientists, establishing itself as one of the most popular programming languages in the world.

This instructor-led, live training in Busan is grounded in the widely recognized book, "Automate the Boring Stuff with Python" by Al Sweigart. Designed for beginners, the course introduces core Python programming concepts through interactive discussions and practical, hands-on exercises. The primary goal is to teach participants how to write code that significantly enhances office productivity.

Upon completing this training, participants will be equipped with Python programming skills to apply in the following areas:

• Automating routine tasks by developing simple Python scripts.
• Creating programs capable of text pattern recognition using "regular expressions".
• Programmatically generating and modifying Excel spreadsheets.
• Extracting and processing data from PDFs and Word documents.
• Crawling websites to gather information from online sources.
• Developing programs that automatically send email notifications.
• Utilizing Python's debugging tools to efficiently identify and fix bugs.
• Controlling the mouse and keyboard programmatically to automate clicking and typing actions.

In this instructor-led, live training session Busan, participants will explore the most relevant and cutting-edge machine learning techniques in Python by building a series of demonstration applications that utilize image, music, text, and financial data.

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

• Implement machine learning algorithms and techniques to solve complex problems.
• Apply deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
• Maximize the potential of Python algorithms.
• Utilize libraries and packages such as NumPy and Theano.

This instructor-led, live training in Busan (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 aims to equip participants with practical proficiency in applying Machine Learning methods. Utilizing the Python programming language and its extensive ecosystem of libraries, alongside numerous hands-on examples, the curriculum covers the essential components of Machine Learning. Participants will learn to make informed decisions about data modeling, interpret algorithmic outputs, and validate results effectively.

Our objective is to empower you with the confidence to master and apply the fundamental tools of the Machine Learning toolkit, while helping you avoid common pitfalls encountered in Data Science applications.

Python has become a highly popular programming language within the financial sector. It is widely adopted by major investment banks and hedge funds to develop a diverse array of financial applications, from core trading systems to sophisticated risk management platforms.

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

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

• Grasp the fundamental concepts of the Python programming language
• Download, install, and maintain the optimal development tools for building financial applications in Python
• Choose and employ the most appropriate Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web APIs, etc.)
• Develop applications that solve problems related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimize Python applications

Audience

• Developers
• Analysts
• Quants

Format of the course

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

Note

• This training focuses on providing solutions for key challenges faced by finance professionals. If there is a specific topic, tool, or technique you wish to include or explore in greater depth, please contact us to arrange.

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

This course provides programmers and data analysts with the foundational techniques required to build machine learning solutions from the ground up using Python. It covers the core principles of supervised learning (classification and regression), unsupervised learning (clustering and anomaly detection), and advanced neural network architectures. Participants will examine proven methods for utilizing scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate hands-on AI development. The program empowers professionals to implement practical ML models, assess algorithm limitations, and complete applied projects aimed at solving real-world problems.

Selenium serves as an open-source framework designed for automating web application testing across various browsers. With the release of Selenium 4, users gain access to enhanced WebDriver APIs, native relative locators, and improved Grid support. Python is chosen for its simplicity and robust integration with testing frameworks such as Pytest, making it an excellent choice for building scalable and maintainable test automation suites.

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

Upon completing this training, participants will be able to:

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

Format of the Course

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

Course Customization Options

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

This instructor-led live training in Busan (online or onsite) is designed for Matlab users who wish to explore 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 Busan (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.

Course Overview

This practical training program is tailored for data engineering professionals aiming to acquire actionable expertise in artificial intelligence, Python, and large language models. The curriculum emphasizes real-world implementation, addressing model utilization, prompt engineering, and the creation of AI-driven solutions. Participants will engage in a series of progressive exercises that transition from fundamental principles to the development of deployable AI workflows.

Training Format

• On-site classroom instruction

• Instructor-guided sessions with practical practice

• Interactive discussions and real-world case studies

• Daily hands-on exercises

Course Objectives

• Comprehend core AI and machine learning concepts applicable to contemporary solutions

• Enhance Python proficiency for AI development and data processing

• Gain insight into the functionality of large language models and effective usage strategies

• Design and refine prompts to ensure consistent and reliable outputs

• Construct comprehensive AI solutions using APIs and frameworks

• Seamlessly integrate AI capabilities into data engineering pipelines

This instructor-led live training in Busan (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 (online or onsite) is designed for data scientists who want 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 Busan (online or onsite) is designed for network engineers who wish to maintain, manage, and design computer networks using Python.

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

• Optimize and utilize Paramiko, Netmiko, Napalm, Telnet, and pyntc for network automation with Python.
• Master multi-threading and multiprocessing techniques in network automation.
• Apply GNS3 and Python for network programming tasks.

This instructor-led live training in Busan (available online or onsite) targets 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 meaningful data from digital media. Python stands out as a high-level programming language, renowned for its clear syntax and code readability.

In this instructor-led live training, participants will explore the fundamentals of Computer Vision by working through the development of several simple Computer Vision applications using Python.

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

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

Audience

• Python developers interested 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 skills through the power of Python. While shell scripting is still effective for straightforward tasks, Python offers much greater flexibility, clarity, and scalability for complex automation, system administration, and DevOps workflows.