Python Training in Hanoi

Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation through modern SDKs and frameworks, such as LangChain and AutoGen, enabling participants to construct, link, and manage agent workflows effectively.

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

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

• Set up and configure Python environments suitable for agentic systems.
• Leverage popular agent SDKs like LangChain and AutoGen to develop functional agents.
• Integrate tools and APIs to enhance 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 focused on building end-to-end agent workflows.

Course Customization Options

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

This program provides practical engineering methodologies for designing, constructing, testing, and deploying autonomous (agentic) systems using Python. The curriculum encompasses the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and critical production considerations.

This instructor-led, live training is available online or onsite. It targets intermediate to advanced ML engineers, AI developers, and software engineers who aim to build robust, production-ready autonomous agents using Python.

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

• Designing and implementing agent loops and decision-making workflows.
• Integrating external tools and APIs to enhance agent capabilities.
• Implementing short-term and long-term memory architectures for agents.
• Coordinating multi-step orchestrations and ensuring agent composability.
• Applying best practices for safety, access control, and observability in deployed agents.

Course Format

• Interactive lectures and discussions.
• Hands-on labs focused on building agents with Python and popular SDKs.
• Project-based exercises resulting in deployable prototypes.

Course Customization Options

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

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

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

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

• Implement AI algorithms utilizing 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 Hanoi (online or onsite) is designed for intermediate-level Python developers seeking to enhance their development experience with AWS Cloud9.

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

• Configure and set up AWS Cloud9 for Python projects.
• Navigate the AWS Cloud9 IDE interface and utilize its key features.
• Create, debug, and deploy Python applications within AWS Cloud9.
• Work collaboratively with other developers on the AWS Cloud9 platform.
• Connect AWS Cloud9 with additional AWS services to facilitate advanced deployment strategies.

This instructor-led, live training in Hanoi (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 flexible programming language extensively utilized for data manipulation, automation, and analytics. Libraries such as Pandas and Polars offer robust and practical tools for handling large-scale tabular data.

This instructor-led, live training (available online or onsite) targets beginner to intermediate-level professionals who want to leverage Python for daily data analysis, file processing, and process automation using Pandas and Polars.

Upon completing 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.
• Package simple scripts into executables and adhere to best practices for project management.

Course Format

• Interactive coding demonstrations combined with brief lectures.
• Hands-on exercises featuring guided code examples.
• Practical mini-projects designed to automate real-world tasks.

Course Customization Options

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

This intensive, practical course explores advanced Python techniques, engineering best practices, and widely used design patterns to help you create maintainable, testable, and high-performance Python applications. The curriculum focuses on modern tooling, type annotations, concurrency models, architectural patterns, and workflows ready for production deployment.

Delivered as instructor-led live training (available online or onsite), this course is designed for intermediate to advanced Python developers looking to adopt professional standards and patterns suitable for production-grade systems.

Upon completing this training, participants will be able to:

• Utilize Python typing, dataclasses, and type-checking mechanisms to enhance code reliability.
• Leverage design patterns and architectural principles to construct robust application structures.
• Correctly implement concurrency and parallelism using asyncio and multiprocessing.
• Create well-tested codebases utilizing pytest, property-based testing, and CI pipelines.
• Profile, optimize, and secure Python applications for production environments.
• Package, distribute, and deploy Python projects using modern tools and containerization.

Course Format

• Interactive lectures paired with short demonstrations.
• Daily hands-on labs and coding exercises.
• A capstone mini-project that integrates patterns, testing, and deployment strategies.

Customization Options

• For customized training or specific focus areas (data, web, or infrastructure), please contact us to arrange your session.

This live, instructor-led training in Hanoi (online or onsite) targets beginner-level developers and data analysts who want to learn Python programming from scratch using Google Colab.

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

• Understand the core principles of Python programming.
• Implement Python code within the Google Colab environment.
• Use control structures to direct the flow of a Python program.
• Create functions to organize and reuse code effectively.
• Explore and apply fundamental libraries for Python programming.

This live, instructor-led training (available online or onsite) is designed for developers who want to utilize the FARM stack (FastAPI, React, and MongoDB) to build dynamic, high-performance, and scalable web applications.

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

• Set up a development environment integrating FastAPI, React, and MongoDB.
• Comprehend the key concepts, features, and benefits of the FARM stack.
• Learn how to construct REST APIs using FastAPI.
• Learn how to design interactive applications with React.
• Develop, test, and deploy applications (covering both front end and back end) using the FARM stack.

This instructor-led, live training in Hanoi (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 intended for individuals eager to master the Python programming language. The curriculum focuses heavily on Python itself, its core libraries, and the selection of high-quality, useful libraries contributed by the Python community. Python is widely utilized by businesses globally and embraced by scientists around the world, establishing it as one of the most popular programming languages today.

The training can be conducted using the latest Python 3.x version, featuring practical exercises that leverage its full capabilities. It is compatible with any operating system, including all variants of UNIX (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 session.

Note: The training content can be customized to meet specific requirements, provided a prior request is made before the proposed course date.

This instructor-led, live training in Hanoi (online or onsite) is designed for developers who want to master advanced Python programming techniques. The course covers how to leverage this versatile language to solve problems in areas such as distributed applications, data analysis and visualization, UI development, and maintenance scripting.

This course caters to individuals eager to master the Python programming language. The focus lies on Python itself, its core libraries, and the selection of the most valuable tools developed by the Python community. Widely regarded as one of the most popular programming languages globally, Python is extensively utilized by scientists and drives business operations worldwide.

This instructor-led live training in Hanoi is grounded in the best-selling book "Automate the Boring Stuff with Python" by Al Sweigart. Designed for beginners, it introduces fundamental Python programming concepts through practical, hands-on exercises and interactive discussions. The primary goal is to teach learners how to write code that significantly boosts office productivity.

Upon completion of this training, participants will be able to program in Python and apply their new skills to:

• Automate repetitive tasks by writing simple Python scripts.
• Create programs capable of text pattern recognition using "regular expressions".
• Programmatically generate and update Excel spreadsheets.
• Parses PDFs and Word documents.
• Crawl websites and extract information from online sources.
• Develop programs that send email notifications.
• Utilize Python's debugging tools to quickly resolve bugs.
• Programmatically control the mouse and keyboard to perform clicks and typing tasks automatically.

In this instructor-led, live training in Hanoi, participants will explore the most relevant and cutting-edge machine learning techniques in Python while developing a series of demo applications that process image, music, text, and financial data.

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

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

This instructor-led, live training in Hanoi (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 techniques. Utilizing the Python programming language and its extensive ecosystem of libraries, alongside numerous hands-on examples, the curriculum covers essential Machine Learning components. Participants will learn how 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 fundamental Machine Learning tools while steering clear of common pitfalls associated with 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 diverse financial applications, from core trading systems to risk management tools.

Through this instructor-led live training, participants will learn how to leverage Python to create practical solutions for various finance-specific challenges.

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

• Grasp the fundamental concepts of the Python programming language
• Download, install, and configure optimal development tools for building financial applications in Python
• Choose and apply appropriate Python packages and techniques to organize, visualize, and analyze financial data from diverse sources (CSV, Excel, databases, web APIs, etc.)
• Develop applications that address issues such as asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimize Python applications

Audience

• Developers
• Analysts
• Quantitative Analysts (Quants)

Course Format

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

Note

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

This course provides an in-depth exploration of practical Data Science and AI techniques leveraging Python, empowering professionals with the capabilities to analyze data, develop machine learning models, and implement AI-driven solutions within business environments. The curriculum encompasses CRISP-DM workflows, statistical analysis, supervised and unsupervised learning methodologies, deep learning with TensorFlow, natural language processing, big data handling via Spark, and the art of data-driven storytelling. It is ideally suited for beginners aiming to obtain a Python data science certification and acquire career-ready analytics training.

This course empowers developers and data analysts with the essential techniques required to construct machine learning solutions from the ground up using Python. It explores core concepts in supervised learning, including classification and regression, as well as unsupervised methods such as clustering and anomaly detection, alongside advanced neural network structures. Participants will study effective strategies for leveraging scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate practical AI development. The curriculum supports professionals in deploying functional ML models, assessing algorithmic constraints, and executing applied projects designed to address real-world challenges.

Selenium is 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 complements these capabilities with its simplicity and robust integration with testing frameworks such as Pytest, making it an ideal choice for creating scalable and maintainable test automation suites.

This instructor-led live training, available both online and onsite, targets beginner to intermediate testers and developers who want to leverage Selenium with Python to automate web application testing in real-world scenarios.

Upon completing this training, participants will be equipped to:

• Install and configure Selenium alongside 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.
• Troubleshoot common issues and apply best practices to ensure automation stability.

Course Format

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

Course Customization Options

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

This instructor-led live training in Hanoi (online or on-site) 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 Hanoi (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 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 program is tailored for data engineering professionals aiming to develop hands-on capabilities in artificial intelligence, Python programming, and large language models (LLMs). The curriculum emphasizes real-world utility, addressing model implementation, prompt design, and the creation of AI-driven solutions. Participants will engage in progressive exercises that transition from foundational principles to the development of deployable AI workflows.

Training Format

• On-site classroom instruction

• Instructor-guided sessions featuring practical application

• Collaborative discussions and analysis of real-world case studies

• Daily hands-on laboratory exercises

Course Objectives

• Grasp essential AI and machine learning concepts applicable to contemporary systems.

• Enhance Python proficiency for AI development and data management tasks.

• Comprehend the mechanics of large language models and their effective utilization.

• Design and refine prompts to ensure consistent and accurate outputs.

• Construct complete AI solutions leveraging APIs and frameworks.

• Seamlessly integrate artificial intelligence into data engineering pipelines.

This instructor-led live training in Hanoi (online or onsite) targets developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs more easily and quickly.

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

• Set up the necessary development environment for developing APIs with Python and FastAPI.
• Create APIs faster 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 Hanoi (online or onsite) targets data scientists who aim to utilize TensorFlow for analyzing potential fraud data.

By the conclusion 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 Hanoi (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.
• Utilize GNS3 and Python for network programming.

This instructor-led, live training in Hanoi (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 focused on the automated extraction, analysis, and interpretation of valuable information from digital media. Python stands out as a high-level programming language renowned for its readability and clean syntax.

During this instructor-led live training, participants will grasp the fundamentals of Computer Vision by progressively building a series of straightforward Computer Vision applications using Python.

Upon completing this training, participants will be equipped to:

• Grasp the foundational concepts of Computer Vision
• Leverage Python to execute Computer Vision tasks
• Develop custom systems for detecting faces, objects, and motion

Audience

• Python developers keen on exploring Computer Vision

Course Format

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

This practical, hands-on course is tailored for Unix and shell users aiming to boost their automation skills through Python. While shell scripting remains effective for straightforward tasks, Python offers far greater flexibility, readability, and scalability, making it ideal for complex automation, system administration, and DevOps workflows.