Python Training in Merida

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

Offered as an instructor-led live training session, available either online or on-site, this program targets intermediate backend engineers, platform engineers, and ML engineers who aim to implement and orchestrate autonomous agents using Python tooling and APIs.

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

• Establish and configure Python environments tailored for agentic systems.
• Utilize prominent agent SDKs such as LangChain and AutoGen to develop 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 focused on building end-to-end agent workflows.

Course Customization Options

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

This course delivers practical engineering methodologies for designing, constructing, testing, and deploying autonomous (agentic) systems using Python. Key topics include the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production-ready considerations.

This instructor-led live training, available online or on-site, targets intermediate to advanced ML engineers, AI developers, and software engineers looking to build robust, production-ready autonomous agents with Python.

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

• Design and implement the agent loop and decision-making workflows.
• Integrate external tools and APIs to enhance 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.

Course Format

• Interactive lectures and discussions.
• Hands-on labs for 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.

Artificial Intelligence with Python involves creating intelligent systems by leveraging Python's robust 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 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 Merida (available online or onsite) is designed for intermediate-level Python developers who want to enhance their 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.
• Navigate the AWS Cloud9 IDE interface and utilize its key features.
• Write, debug, and deploy Python applications within AWS Cloud9.
• Collaborate effectively with other developers via the AWS Cloud9 platform.
• Integrate AWS Cloud9 with other AWS services to facilitate advanced deployments.

This instructor-led, live training in Merida (online or onsite) targets expert-level data analysts who aim 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:

• Understand how to integrate Python into Power BI for data analysis purposes.
• Employ Python scripts to load, clean, and preprocess data directly within the Power BI environment.
• Expand data visualization potential by developing custom and interactive visualizations using Python.
• Develop advanced data analysis skills through the use of 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:

• Use Python to read, transform, and write CSV and Excel files.
• Perform common data cleaning and transformation tasks with Pandas and Polars.
• Automate repetitive data processes with Python scripts.
• Package simple scripts into executables and follow 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 rigorous, 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 highlights modern tooling, type hinting, concurrency models, architectural patterns, and deployment-ready workflows.

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

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

• Apply Python typing, dataclasses, and type-checking to enhance code reliability.
• Utilize design patterns and architecture principles to structure robust applications.
• Correctly implement concurrency and parallelism using asyncio and multiprocessing.
• Create 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 and concise demonstrations.
• Hands-on labs and coding exercises every day.
• A capstone mini-project that integrates patterns, testing, and deployment.

Course Customization Options

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

This instructor-led, live training in Merida (online or on-site) is designed for beginner 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:

• Understand the basics of the Python programming language.
• Implement Python code in the 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 on-site, targets 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 required development environment integrating 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 Merida (online or onsite) is designed for robotics developers at beginner to intermediate levels, potentially extending to advanced practitioners who wish to learn how to program mobile robots using ROS and Python.

By the conclusion 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.
• Troubleshoot and debug ROS applications.

This course is designed for individuals interested in learning the Python programming language. It emphasizes the core Python language, its essential libraries, and the selection of the most valuable libraries developed by the Python community. Python powers businesses and is widely used by scientists globally, making it one of the most popular programming languages today.

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

Practical exercises make up approximately 70% of the course time, with the remaining 30% dedicated to demonstrations and presentations. Participants are encouraged to ask questions and engage in discussions throughout the session.

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

This instructor-led, live training in Merida (online or onsite) is designed for developers looking 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 intended for individuals eager to master the Python programming language. The focus lies on Python itself, its core libraries, and the strategic selection of the most valuable libraries contributed by the Python community. Python powers businesses worldwide and is extensively used by scientists; it stands as one of the most popular programming languages in existence.

This instructor-led, live training in Merida is rooted in the widely acclaimed book, "Automate the Boring Stuff with Python" by Al Sweigart. Designed for beginners, the course explores fundamental Python programming concepts through engaging discussions and practical, hands-on exercises. The primary goal is to teach participants how to write code that significantly boosts office productivity.

Upon completing this training, participants will be able to program in Python and leverage this new skill for:

• Automating repetitive tasks by creating simple Python programs.
• Developing programs capable of recognizing text patterns using "regular expressions".
• Programmatically generating and updating Excel spreadsheets.
• Parsing PDFs and Word documents.
• Crawling websites and extracting information from online sources.
• Creating programs that send out email notifications.
• Utilizing Python's debugging tools to quickly resolve bugs.
• Programmatically controlling the mouse and keyboard to click and type on your behalf.

During this instructor-led, live training in Merida, participants will learn the most relevant and cutting-edge machine learning techniques in Python by building a series of demo applications that involve 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 Merida (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 build practical competence in applying Machine Learning techniques. By leveraging the Python programming language and its diverse ecosystem of libraries, alongside numerous hands-on examples, participants will learn to utilize key Machine Learning components, make informed data modeling decisions, interpret algorithm outputs, and validate results effectively.

Our objective is to equip you with the confidence to master fundamental Machine Learning tools and help you steer clear of common pitfalls in Data Science projects.

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

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

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

• Grasp the fundamentals of the Python programming language
• Download, install, and maintain the best development tools for creating financial applications in Python
• Select and utilize the most appropriate Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
• Build applications that solve problems related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimize a Python application

Audience

• Developers
• Analysts
• Quants

Format of the course

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

Note

• This training aims to provide solutions for some of the key problems faced by finance professionals. However, if you have a particular topic, tool, or technique that you wish to append or elaborate further on, please contact us to arrange.

Explores practical methods for applying Data Science and AI with Python, equipping professionals with the expertise to analyze data, develop machine learning models, and implement AI-powered applications in business environments. The course covers CRISP-DM workflows, statistical analysis, supervised and unsupervised learning, deep learning with Tensorflow, natural language processing, big data processing with Spark, and data-driven storytelling. It is ideal for beginners seeking a Python data science certification and career-focused analytics training.

The Applied AI from Scratch in Python course provides programmers and data analysts with the fundamental skills required to build machine learning solutions from the ground up using Python. The curriculum covers 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 leveraging scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate hands-on AI development. This course empowers professionals to implement practical ML models, assess algorithmic limitations, and execute applied projects designed for real-world problem solving.

Selenium is an open-source framework designed for automating web application testing across various browsers. With 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 developing scalable and maintainable test automation suites.

This instructor-led, live training (available online or 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 able to:

• Install and configure Selenium with Python in a test 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 for stable automation.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and hands-on practice.
• Practical implementation within a live-lab environment.

Customization Options

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

This instructor-led, live training in Merida (online or on-site) 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 extract insights from various datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

This instructor-led, live training in Merida (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 hands-on expertise in artificial intelligence, Python, and large language models. The curriculum emphasizes real-world applications, including model utilization, prompt engineering, and the creation of AI-driven solutions. Participants will engage in a series of progressive exercises that advance from foundational concepts to the development of deployable AI workflows.

Training Format

• In-person classroom instruction

• Instructor-led sessions featuring guided practice

• Interactive discussions complemented by real-world case studies

• Daily hands-on exercises

Course Objectives

• Gain a solid understanding of core AI and machine learning concepts applicable to modern systems

• Enhance Python proficiency for AI development and data workflows

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

• Design and optimize prompts to ensure consistent and reliable outputs

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

• Integrate AI capabilities into existing data engineering pipelines

This instructor-led, live training in Merida (online or in-person) is designed for developers who want to utilize FastAPI with Python to build, test, and deploy RESTful APIs more efficiently and quickly.

Upon completing this training, participants will be able to:

• Configure the necessary development environment for building APIs with Python and FastAPI.
• Develop APIs more quickly and easily using the FastAPI library.
• Understand how to create data models and schemas based on Pydantic and OpenAPI.
• Connect APIs to databases using SQLAlchemy.
• Implement security and authentication features in APIs using FastAPI tools.
• Create container images and deploy web APIs to cloud servers.

This instructor-led live training in Merida (online or onsite) is designed for data scientists interested in using TensorFlow to analyze potential fraud data.

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

• Develop a fraud detection model using Python and TensorFlow.
• Build linear regression models to predict fraud.
• Create an end-to-end AI application for analyzing fraud data.

This live, instructor-led training in Merida (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.
• Employ GNS3 and Python for network programming.

This instructor-led live training in Merida (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.

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

In this instructor-led live training, participants will grasp the fundamentals of Computer Vision by guiding them through the development of a series of straightforward Computer Vision applications using Python.

Upon completing this training, participants will be capable of:

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

Audience

• Python programmers interested in Computer Vision

Format of the course

• 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 using Python. While shell scripting is still effective for basic tasks, Python offers much greater flexibility, clarity, and scalability for complex automation, system administration, and DevOps workflows.