Python for Matlab Users Training Course

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 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.

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.

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 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.

This instructor-led live training in Vietnam (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.

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 Vietnam (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 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 Vietnam (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 Vietnam (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 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.

This instructor-led, live training in Vietnam (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 Vietnam (online or onsite) is designed for 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.

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.