Python Training in Natal

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 construct, link, and manage agent workflows.

Delivered as an instructor-led live training (available online or on-site), this program targets intermediate backend engineers, platform engineers, and ML engineers looking to implement and orchestrate autonomous agents using Python tooling and APIs.

Upon completing this training, participants will be able to:

• Set up and configure Python-based environments tailored for agentic systems.
• Leverage popular agent SDKs like LangChain and AutoGen to build 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.

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 covers 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 aimed at intermediate-level to advanced-level ML engineers, AI developers, and software engineers who wish 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 creating intelligent systems by leveraging Python’s comprehensive ecosystem of AI and machine learning libraries.

This instructor-led, live training (available online or onsite) is designed for intermediate-level Python programmers who aim 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 Natal (online or onsite) is designed for intermediate-level Python developers seeking to enhance their Python development experience with AWS Cloud9.

Upon completion 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 features.
• Write, debug, and deploy Python applications within AWS Cloud9.
• Collaborate effectively with other developers using the AWS Cloud9 platform.
• Integrate AWS Cloud9 with other AWS services for advanced deployment scenarios.

This instructor-led, live training in Natal (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:

• 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 intensive, practical course explores advanced Python techniques, engineering best practices, and widely adopted design patterns to help you build maintainable, testable, and high-performance Python applications. The curriculum highlights modern tooling, type hinting, concurrency models, architectural patterns, and deployment-ready workflows.

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

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

• Apply Python typing, dataclasses, and type-checking to enhance code reliability.
• Utilize design patterns and architectural principles to structure robust applications.
• Correctly implement concurrency and parallelism using asyncio and multiprocessing.
• Develop well-tested code through pytest, property-based testing, and CI pipelines.
• Profile, optimize, and harden Python applications for production environments.
• Package, distribute, and deploy Python projects using modern tools and containers.

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 areas (data, web, or infrastructure), please contact us to arrange it.

This instructor-led, live training in Natal (online or onsite) is designed for beginner-level developers and data analysts who wish to learn Python programming from scratch using Google Colab.

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

• Grasp the fundamentals of the Python programming language.
• Write and implement Python code within the Google Colab environment.
• Apply control structures to manage program execution flow.
• Develop functions to structure and reuse code efficiently.
• Explore and utilize essential libraries for Python development.

This instructor-led live training, offered online or onsite, is designed for developers seeking 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 the requisite development environment for FastAPI, React, and MongoDB.
• Understand the fundamental concepts, features, and benefits of the FARM stack.
• Learn to create REST APIs using FastAPI.
• Acquire skills in designing interactive applications with React.
• Develop, test, and deploy applications (both frontend and backend) using the FARM stack.

This instructor-led, live training in Natal (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 focus lies on Python 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 widely used by scientists globally, making it one of the most popular programming languages.

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

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

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

This instructor-led, live training in Natal (online or onsite) is designed for developers seeking to master advanced Python programming techniques. The course 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 focus lies on mastering the Python language itself, its core libraries, and identifying the most valuable and effective libraries contributed by the Python community. Python powers businesses globally and is widely utilized by scientists around the world, cementing its status as one of the most popular programming languages.

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

Upon completing this training, participants will master Python programming and apply these skills to:

• Automate routine tasks by developing simple Python scripts.
• Create programs that perform text pattern recognition using "regular expressions".
• Generate and update Excel spreadsheets programmatically.
• Parse PDF and Word documents.
• Crawl websites and extract information from online sources.
• Develop programs that automatically send email notifications.
• Leverage Python's debugging tools to quickly identify and resolve bugs.
• Control the mouse and keyboard programmatically to execute clicks and typing actions.

In this instructor-led, live training in Natal, participants will learn the most relevant and cutting-edge machine learning techniques in Python as they build 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 Natal (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 develop practical proficiency in applying Machine Learning techniques. By leveraging Python and its extensive ecosystem of libraries, along with numerous hands-on examples, participants will learn to utilize the core components of Machine Learning, make informed decisions regarding data modeling, interpret algorithm outputs, and validate results effectively.

We strive to equip you with the confidence to master the fundamental tools in the Machine Learning toolkit and help you steer clear of common pitfalls associated with Data Science applications.

Python has become a highly favored programming language within the financial sector. Utilized by major investment banks and hedge funds, it powers a diverse array of financial applications, from core trading systems to risk management solutions.

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

Upon completing 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 effective Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (such as CSV, Excel, databases, and web APIs)
• Develop applications that resolve issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimize Python applications

Audience

• Developers
• Analysts
• Quants

Course Format

• 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 it.

This course delves into practical methodologies for Data Science and AI utilizing Python, empowering professionals with the expertise to analyze data, develop machine learning models, and implement AI-driven solutions within business environments. It encompasses 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 an ideal choice for beginners aiming for a Python data science certification and seeking career-ready analytics training.

Practical AI Development from the Ground Up in Python empowers developers and data analysts with essential techniques for constructing machine learning solutions entirely from scratch using Python. The course covers fundamental concepts such as supervised learning (classification and regression), unsupervised learning (clustering and anomaly detection), and complex neural network architectures. It explores effective strategies for leveraging scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate hands-on AI development. Participants will learn to deploy functional ML models, assess algorithm constraints, and execute 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 this by offering 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 both online and on-site, is tailored for testers and developers at beginner to intermediate levels who want to leverage Selenium with Python to automate web application testing in real-world scenarios.

Upon completing this training, participants will be capable of:

• Installing and configuring Selenium with Python within a test environment.
• Developing robust test automation scripts using Selenium WebDriver and Pytest.
• Implementing the Page Object Model (POM) to create maintainable test frameworks.
• Executing tests across multiple browsers via Selenium Grid.
• Integrating automated tests into CI/CD pipelines.
• Troubleshooting common issues and applying best practices to ensure automation stability.

Course Format

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

Course Customization Options

• For requests regarding customized training for this course, please reach out to us to make arrangements.

This instructor-led, live training in Natal (online or onsite) 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 Natal (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.

In this instructor-led, live training, participants will 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.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• If you wish to add, remove or customize any section or topic within this course, please contact us to arrange.

This instructor-led live training in Natal (online or on-site) is designed for data scientists and software engineers who aim to utilize Dask with the Python ecosystem to construct, scale, and analyze large datasets.

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

• Configure the environment to start building big data processing with Dask and Python.
• Explore the features, libraries, tools, and APIs available in Dask.
• Understand how Dask accelerates parallel computing in Python.
• Learn how to scale the Python ecosystem (Numpy, SciPy, and Pandas) using Dask.
• Optimize the Dask environment to maintain high performance in handling large datasets.

This instructor-led live training in Natal (online or onsite) targets business analysts who wish to automate trading using algorithmic trading, Python, and R.

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

• Utilize algorithms to rapidly buy and sell securities at specialized increments.
• Decrease costs associated with trading by leveraging algorithmic trading techniques.
• Automatically monitor stock prices and execute trades.

Course Overview

This practical training program is tailored for data engineering professionals aiming to develop hands-on expertise in artificial intelligence, Python, and large language models. Emphasizing real-world applications, the curriculum covers model utilization, prompt engineering, and the creation of AI-driven solutions. Participants will engage in step-by-step exercises that progress from foundational concepts to the development of deployable AI workflows.

Training Format

• In-person classroom instruction

• Instructor-led sessions featuring guided practice

• Interactive discussions and analysis of real-world case studies

• Daily practical exercises

Course Objectives

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

• Enhance Python proficiency for AI development and data processing

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

• Craft and refine prompts to ensure consistent and accurate outputs

• Develop complete AI solutions utilizing APIs and frameworks

• Seamlessly integrate AI capabilities into data engineering pipelines

This instructor-led live training in Natal (online or onsite) is designed for developers who want to use FastAPI with Python to build, test, and deploy RESTful APIs more quickly and easily.

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 Natal (online or onsite) targets data scientists who wish 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 Natal (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 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 Natal (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.

This instructor-led live training in Natal (online or onsite) is designed for penetration testers who wish to perform network penetration tests on Kali Linux using Python.

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

• Create Python programs to identify network vulnerabilities.
• Explore and use Kali web shells and shellcode in exploits.
• Apply various Kali tools for penetration testing.
• Exploit systems with Python.

Python is a high-level programming language renowned for its clear syntax and code readability.

In this instructor-led, live training, participants will learn how to use Python for quantitative finance.

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

• Understand the fundamentals of Python programming
• Use Python for financial applications including implementing mathematical techniques, stochastics, and statistics
• Implement financial algorithms using performance Python

Audience

• Developers
• Quantitative analysts

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Computer Vision is a domain focused on automatically extracting, analyzing, and comprehending valuable information from digital media. Python, a high-level programming language, is renowned for its clear syntax and code readability.

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

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

• Comprehend the basics of Computer Vision
• Utilize Python to execute Computer Vision tasks
• Develop their own systems for face, object, and motion detection

Audience

• Python programmers interested in Computer Vision

Course Format

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

This course serves as an extension of the one-day introduction to Python, specifically 'Python and Data Visualization,' which took place on February 11th.

The curriculum is tailored for individuals aiming to master the Python programming language. The focus lies on the core aspects of Python, essential libraries, and the selection of the most valuable tools developed by the Python community. Python is a cornerstone for businesses globally and is widely used by scientists, making it one of the most popular programming languages in the world.

This practical course is tailored for Unix and shell users aiming to boost their automation skills by leveraging Python. Although shell scripting is effective for straightforward tasks, Python offers superior flexibility, readability, and scalability for handling complex automation, system administration, and DevOps workflows.

Tableau is a business intelligence and data visualization tool. Python is a widely used programming language which provides support for a wide variety of statistical and machine learning techniques. Tableau's data visualization power and Python's machine learning capabilities, when combined, help developers rapidly build advanced data analytics applications for various business use cases.

In this instructor-led, live training, participants will learn how to combine Tableau and Python to carry out advanced analytics. Integration of Tableau and Python will be done via the TabPy API.

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

• Integrate Tableau and Python using TabPy API
• Use the integration of Tableau and Python to analyze complex business scenarios with few lines of Python code

Audience

• Developers
• Data scientists

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice