Python Training in Maia

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

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

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

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

Course Format

• Interactive lectures and discussions.
• Hands-on programming exercises and live demonstrations.
• Practical projects focusing on end-to-end agent workflow creation.

Course Customization Options

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

This course provides practical engineering methodologies for designing, constructing, testing, and deploying autonomous (agentic) systems using Python. It explores the agent lifecycle, tool integrations, memory and state management, orchestration patterns, safety controls, and critical production considerations.

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

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

• Design and implement the agent loop alongside decision-making workflows.
• Integrate external tools and APIs to expand agent capabilities.
• Develop short-term and long-term memory architectures for agents.
• 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 involving the construction of agents with Python and popular SDKs.
• Project-based exercises that result in deployable prototypes.

Course Customization Options

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

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 Python programmers who aim to design, implement, and deploy AI solutions using Python.

Upon completion 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.
• Ample exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

This instructor-led, live training in Maia (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 Maia (online or in-person) is targeted 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-used design patterns to help you build maintainable, testable, and high-performance Python applications. The curriculum focuses on 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 who aim 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.
• Leverage design patterns and architectural principles to structure robust applications.
• Correctly implement concurrency and parallelism using asyncio and multiprocessing.
• Write well-tested code using 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 short demonstrations.
• Hands-on labs and coding exercises each day.
• A capstone mini-project integrating patterns, testing, and deployment.

Course Customization Options

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

This instructor-led, live training in Maia (online or in-person) is intended for beginner-level developers and data analysts who want 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 in Maia (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.

Designed for individuals keen on mastering the Python programming language, this course focuses primarily on Python itself, its core libraries, and the most valuable tools developed by the Python community. Python is a cornerstone for businesses globally and is widely adopted by scientists, making it one of the most popular programming languages today.

The training is delivered using the latest Python 3.x version, incorporating practical exercises to fully leverage its capabilities. It is compatible with any operating system, including various UNIX distributions (such as Linux and Mac OS X) as well as Microsoft Windows.

Approximately 70% of the course is dedicated to practical exercises, while the remaining 30% consists of demonstrations and presentations. Participants are encouraged to engage in discussions and ask questions throughout the session.

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

This instructor-led, live training in Maia (online or onsite) is designed for developers looking to master advanced Python programming techniques. The course covers 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 tailored for individuals looking to master the Python programming language. The focus lies on the Python language itself, its core libraries, and the curation of the most valuable tools developed by the Python community. Python powers businesses worldwide and is a favourite among scientists, cementing its status as one of the most popular programming languages in use today.

This instructor-led, live training in Maia 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 Maia, attendees will master the most pertinent and state-of-the-art machine learning techniques in Python while developing a range of demo applications that handle image, music, text, and financial data.

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

• Implement machine learning algorithms and techniques 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.
• Utilize libraries and packages such as NumPy and Theano.

This course is designed to equip participants with practical proficiency in applying Machine Learning techniques. By leveraging the Python programming language and its extensive library ecosystem, and through numerous hands-on examples, the curriculum covers the essential components of Machine Learning. Participants will learn to make informed data modelling decisions, interpret algorithmic outputs, and validate results effectively.

Our objective is to empower you with the confidence to utilise the core tools of the Machine Learning toolkit while avoiding the common pitfalls associated with Data Science applications.

Python has established itself as a highly popular programming language within the financial sector. Widely adopted by major investment banks and hedge funds, it is utilized to develop a diverse array of financial applications, spanning from core trading systems to comprehensive risk management solutions.

During this instructor-led live training, participants will learn how to leverage Python to create practical applications that address specific challenges in the finance industry.

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

• Grasp the fundamental concepts of the Python programming language
• Download, install, and maintain the most effective development tools for building financial applications using Python
• Choose and employ the most appropriate Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (such as CSV, Excel, databases, and web interfaces)
• Develop applications that solve problems related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimize Python applications

Audience

• Developers
• Analysts
• Quantitative Analysts (Quants)

Format of the course

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

Note

• This training is designed to provide solutions for some of the key challenges faced by finance professionals. However, if you have a specific topic, tool, or technique you wish to include or elaborate on, please contact us to make arrangements.

Explores practical methodologies for Data Science and Artificial Intelligence (AI) using Python. This course empowers professionals with the expertise to analyse data, develop machine learning models, and implement AI-driven solutions within business environments. Topics include 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 particularly suitable for beginners looking to obtain a Python data science certification and gain career-focused analytics training.

Applied AI from Scratch in Python empowers programmers and data analysts with the essential techniques required to build machine learning solutions from the ground up using Python. The course covers the core principles of supervised learning (classification and regression), unsupervised learning (clustering and anomaly detection), and advanced neural network architectures. It examines proven methodologies for utilizing scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate hands-on AI development. Participants will learn to implement practical ML models, assess algorithm limitations, and complete applied projects designed for real-world problem-solving.

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 with its 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 online or onsite) is tailored for testers and developers at beginner to intermediate levels who aim to utilize 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 within a test environment.
• Create robust test automation scripts using Selenium WebDriver and Pytest.
• Implement the Page Object Model (POM) to build 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 ensuring automation stability.

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within 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 Maia (online or on-site) is aimed at 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 derive insights from various datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

This instructor-led, live training in Maia (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 master advanced Python programming techniques, including how to leverage this versatile language to address challenges in areas such as distributed applications, data analysis and visualization, UI programming, and maintenance scripting.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical sessions.
• Hands-on implementation within 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 Maia (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.

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

• Employ algorithms to buy and sell securities at specialized increments rapidly.
• Reduce costs associated with trade using algorithmic trading.
• Automatically monitor stock prices and place trades.

Course Overview

This practical training is tailored for data engineering professionals seeking to develop hands-on expertise in artificial intelligence, Python, and large language models. Emphasising real-world application, the course covers model utilisation, prompt engineering, and the creation of AI-driven solutions. Participants will progress through structured exercises, advancing from foundational concepts to the development of deployable AI workflows.

Training Format

• In-person classroom-based learning

• Instructor-led sessions featuring guided practice

• Interactive discussions supported by real-world case studies

• Daily practical exercises

Course Objectives

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

• Enhance Python proficiency for AI development and data workflows

• Comprehend the mechanics of large language models and effective usage strategies

• Design and refine prompts to ensure consistent and reliable outputs

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

• Integrate AI capabilities into data engineering pipelines

This instructor-led, live training in Maia (online or onsite) is designed for data scientists who wish to utilise TensorFlow to analyse 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 analysing fraud data.

This instructor-led live training in Maia (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 utilize Paramiko, Netmiko, Napalm, Telnet, and pyntc for network automation with Python.
• Master multi-threading and multiprocessing techniques in network automation.
• Apply GNS3 and Python for network programming.

This instructor-led, live training in Maia (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 Maia (online or onsite) is aimed at penetration testers who wish to penetrate test networks in Kali Linux using Python.

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

• Create Python programs to seek 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 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 clean syntax and high readability.

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:

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

Audience

• Python programmers keen on exploring 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 capabilities through the use of Python. Although shell scripting is still effective for basic tasks, Python offers significantly better flexibility, readability, and scalability for handling complex automation, system administration, and DevOps workflows.

Tableau is a leading business intelligence and data visualization platform. Python is a versatile programming language that supports a broad spectrum of statistical and machine learning techniques. By harnessing Tableau's powerful visualization capabilities alongside Python's advanced machine learning functionalities, developers can rapidly construct sophisticated data analytics applications tailored to diverse business requirements.

During this instructor-led live training, participants will learn how to seamlessly integrate Tableau and Python to perform advanced analytics. This integration is facilitated through the TabPy API.

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

• Integrate Tableau and Python using the TabPy API
• Leverage the combined power of Tableau and Python to analyze complex business scenarios with minimal Python code

Audience

• Developers
• Data scientists

Format of the course

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