Python Training in Buenos Aires

Python serves as the fundamental language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation through the use of modern SDKs and frameworks, such as LangChain and AutoGen, to build, link, and manage agent workflows.

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

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

• Setting up and configuring Python-based environments for agentic systems.
• Utilizing popular agent SDKs like LangChain and AutoGen to develop functional agents.
• Integrating tools and APIs to enhance agent capabilities.
• Orchestrating multi-agent workflows and communication patterns.
• Applying best practices for debugging, testing, and maintaining agentic codebases.

Format of the Course

• Interactive lecture and discussion.
• Hands-on programming exercises and live demos.
• 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 delivers practical engineering methodologies for designing, constructing, testing, and deploying agentic (autonomous) systems using Python. Key topics include the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production-grade considerations.

Delivered as an instructor-led, live training session (available online or onsite), this program targets intermediate to advanced ML engineers, AI developers, and software engineers looking to build robust, production-ready autonomous agents in Python.

Upon completing this training, participants will be equipped to:

• Design and implement agent loops and decision-making workflows.
• Integrate external tools and APIs to enhance agent capabilities.
• Implement memory architectures for both short-term and long-term state management.
• Coordinate multi-step orchestrations and ensure agent composability.
• Apply 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.

Customization Options

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

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

This instructor-led live training, available either 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 equipped to:

• Develop AI algorithms utilizing Python’s primary AI libraries.
• Apply supervised, unsupervised, and reinforcement learning models.
• Integrate AI solutions seamlessly into existing applications and workflows.
• Assess model performance and optimize for both accuracy and efficiency.

Course Format

• Engaging lectures and interactive discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live laboratory environment.

Customization Options

• To arrange a customized training session for this course, please get in touch with us.

This instructor-led, live training in Buenos Aires (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 Buenos Aires (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 while adhering to best practices for project management.

Format of the Course

• Interactive coding demonstrations and short lectures.
• Hands-on exercises with guided code examples.
• Practical mini-projects designed 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 widely adopted design patterns to help you build maintainable, testable, and high-performance Python applications. It focuses on modern tooling, type hints, concurrency models, architectural patterns, and deployment-ready workflows.

Delivered as an instructor-led, live training session (available online or onsite), this program is designed for intermediate to advanced Python developers who aim to adopt professional practices and patterns for production-grade Python systems.

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

• Utilize Python typing, dataclasses, and type-checking to enhance code reliability.
• Apply design patterns and architectural principles to structure robust applications.
• Effectively implement concurrency and parallelism using asyncio and multiprocessing.
• Develop well-tested code using 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 accompanied by concise demonstrations.
• Practical labs and coding exercises each day.
• A capstone mini-project that integrates patterns, testing, and deployment.

Customization Options

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

This live, instructor-led training in Buenos Aires (available online or on-site) is designed for beginner-level developers and data analysts seeking 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, offered online or onsite, targets developers who want to employ the FARM (FastAPI, React, and MongoDB) stack to construct dynamic, high-performance, and scalable web applications.

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

• Set up the required development environment integrating FastAPI, React, and MongoDB.
• Understand the fundamental 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 Buenos Aires (online or onsite) targets beginner to intermediate, and potentially advanced-level robotics developers who want to learn how to use ROS to program mobile robots with Python.

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

• Configure a development environment that includes ROS, Python, and a mobile robot platform.
• Create and execute ROS nodes, topics, services, and actions using Python.
• Employ ROS tools and utilities to monitor and debug ROS applications.
• Utilize ROS packages and libraries to perform standard tasks for mobile robots.
• Integrate ROS with other frameworks and tools.
• Troubleshoot and debug ROS applications.

This course is tailored for individuals eager to master the Python programming language. The focus lies on the Python language itself, its core libraries, and the selection of the most valuable libraries contributed by the Python community. Python is a powerhouse for businesses and is utilized by scientists globally, making it one of the most widely used programming languages.

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

Practical exercises account for 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 course.

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

This instructor-led, live training in Buenos Aires (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 program is tailored for individuals eager to master the Python programming language. The focus lies on Python itself, its essential libraries, and the curated selection of the most valuable tools created by the Python community. Widely utilized by businesses and scientists globally, Python stands out as one of the most prevalent programming languages today.

This instructor-led, live training in Buenos Aires 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 Buenos Aires, participants will master the most relevant and cutting-edge machine learning techniques in Python while building 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 Buenos Aires (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 along with its extensive library ecosystem and grounded in numerous real-world examples, the curriculum focuses on mastering the essential components of Machine Learning. Participants will learn how to make informed decisions regarding data modeling, interpret algorithm outputs, and validate results effectively.

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

Python has become highly popular in the financial sector. Major investment banks and hedge funds use it to create various financial applications, from core trading systems to risk management tools.

In this instructor-led training, participants will learn to use Python to develop practical applications for solving specific finance problems.

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

• Understand Python programming fundamentals
• Download, install, and configure the best tools for creating financial applications in Python
• Select and use the most suitable Python packages and techniques to organize, visualize, and analyze financial data from multiple sources (CSV, Excel, databases, web, etc.)
• Build applications to address asset allocation, risk analysis, investment performance, and other challenges
• Troubleshoot, integrate, deploy, and optimize Python applications

Audience

• Developers
• Analysts
• Quants

Course Format

• Lectures, discussions, exercises, and extensive hands-on practice

Note

• This training provides solutions to common challenges faced by finance professionals. If you wish to add or elaborate on specific topics, tools, or techniques, please contact us to arrange.

This course provides a practical exploration of Data Science and AI utilizing Python, empowering professionals with the capabilities to analyze data, construct machine learning models, and implement AI-powered applications within business environments. It covers CRISP-DM methodologies, statistical analysis, supervised and unsupervised learning techniques, deep learning with TensorFlow, natural language processing, big data processing with Spark, and data-driven storytelling. It is an ideal choice for beginners pursuing a Python data science certification and seeking career-ready analytics training.

Applied AI from Scratch in Python provides programmers and data analysts with the foundational techniques required to build machine learning solutions from the ground up using Python. The course covers core 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 examines proven methodologies for leveraging scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate hands-on AI development. The program assists professionals in implementing practical ML models, evaluating the limitations of algorithms, and completing applied projects aimed at solving 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 gain access to enhanced WebDriver APIs, native relative locators, and improved grid support. Python complements this by offering simplicity and robust integration with testing frameworks such as Pytest, making it an excellent choice for creating scalable and maintainable test automation suites.

This instructor-led live training, available online or on-site, targets beginner to intermediate testers and developers who want to leverage Selenium and 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.
• Troubleshoot common issues and apply best practices to ensure automation stability.

Course Format

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

Customization Options

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

This instructor-led, live training in Buenos Aires (online or onsite) is designed for Matlab users looking 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 similarities and differences between Matlab and Python syntax.
• Use Python to extract insights from various datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

This instructor-led, live training in Buenos Aires (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.

GitHub Copilot

Course Overview

This practical training is tailored for data engineering professionals aiming to develop applied skills in artificial intelligence, Python, and large language models. The curriculum emphasizes real-world use cases, encompassing model utilization, prompt engineering, and the creation of AI-driven solutions. Participants will engage in a series of progressive exercises, advancing from foundational concepts to the development of deployable AI workflows.

Training Format

• Classroom-based, in-person sessions

• Instructor-led instruction with guided practice

• Interactive discussions and real-world case studies

• Daily hands-on exercises

Course Objectives

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

• Enhance Python proficiency for AI development and data workflows

• Comprehend the mechanics of large language models and their effective application

• Craft and optimize prompts to ensure reliable outputs

• Construct complete AI solutions utilizing APIs and frameworks

• Incorporate AI capabilities into data engineering pipelines

This instructor-led live training in Buenos Aires (online or onsite) is designed for developers who want to use Python with FastAPI 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 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 Buenos Aires (online or onsite) is designed for data scientists who want to utilize 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 Buenos Aires (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 Buenos Aires (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 the automatic extraction, analysis, and interpretation of valuable information from digital media. Python stands out as a high-level programming language renowned for its readable syntax and code clarity.

During this instructor-led live training, attendees will grasp the fundamentals of Computer Vision by developing a series of simple applications using Python.

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

• Grasping the core principles of Computer Vision
• Utilizing Python to execute Computer Vision tasks
• Developing their own systems for face, object, and motion detection

Audience

• Python developers with an interest 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 Python. Although shell scripting is still effective for straightforward tasks, Python offers much more flexibility, clarity, and scalability for complex automation, system administration, and DevOps processes.