Python Training in Johannesburg

Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasises practical implementation through modern SDKs and frameworks, such as LangChain and AutoGen, enabling you to build, link, and manage agent workflows effectively.

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

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

• Set up and configure Python-based environments for agentic systems.
• Utilise popular agent SDKs, including LangChain and AutoGen, to develop functional agents.
• Integrate tools and APIs to expand agent capabilities.
• Orchestrate multi-agent workflows and communication patterns.
• Apply industry 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.

Customisation Options

• For bespoke training tailored to your needs, please contact us to arrange a session.

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

This instructor-led, live training (available online or onsite) targets intermediate to advanced-level ML engineers, AI developers, and software engineers who aim to build robust, production-ready autonomous agents using Python.

Upon completion of this training, participants will be 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 focuses on building intelligent systems by leveraging Python’s comprehensive ecosystem of AI and machine learning libraries.

This instructor-led live training, available both online and 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 Johannesburg (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 Johannesburg (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.

Course Format

• Interactive coding demonstrations and short lectures.
• Hands-on exercises with guided code examples.
• Practical mini-projects to automate real-world tasks.

Course Customisation Options

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

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

Delivered as live instructor-led training (available online or onsite), this programme is tailored for intermediate to advanced Python developers aiming to embrace professional practices and patterns essential for production-grade Python systems.

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

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

Format of the Course

• Interactive lectures and concise demonstrations.
• Hands-on labs and coding exercises each day.
• A capstone mini-project that integrates patterns, testing, and deployment.

Course Customisation Options

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

This instructor-led, live training in Johannesburg (online or on-site) targets beginner developers and data analysts who wish to learn Python programming from scratch using Google Colab.

Upon completing this training, participants will be capable of:

• Grasping the core principles of the Python programming language.
• Implementing Python code within the Google Colab environment.
• Applying control structures to direct the flow of a Python program.
• Developing functions to structure and reuse code efficiently.
• Exploring and employing fundamental libraries for Python development.

This instructor-led, live training (online or onsite) 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 necessary development environment that integrates 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 Johannesburg (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 tailored for individuals keen to master the Python programming language. The focus lies on the Python language itself, its core libraries, and the selection of the most effective and useful libraries created by the Python community. Python powers businesses globally and is widely used by scientists worldwide, making it one of the most popular programming languages.

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

Practical exercises make up approximately 70% of the course time, 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 customised to meet specific requirements upon prior request before the proposed course date.

This instructor-led, live training in Johannesburg (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 course is tailored for individuals keen on mastering the Python programming language. The focus lies on the Python language itself, its core libraries, and the strategic selection of the most valuable tools contributed by the Python community. Python is a pivotal language that powers businesses globally and is widely adopted by scientists – making it one of the most sought-after programming languages worldwide.

This instructor-led, live training in Johannesburg is derived from the bestselling book, "Automate the Boring Stuff with Python" by Al Sweigart. Designed for beginners, the course covers fundamental Python programming concepts through practical, hands-on exercises and interactive discussions. The primary goal is to equip learners with the ability to write code that significantly boosts office productivity.

Upon completion of this training, participants will be able to program in Python and leverage this skill to:

• Automate routine tasks by developing simple Python scripts.
• Create programs capable of text pattern recognition using "regular expressions".
• Programmatically generate and update Excel spreadsheets.
• Parses PDFs and Word documents.
• Crawl websites and extract data from online sources.
• Develop programs that dispatch email notifications.
• Utilise Python's debugging tools to swiftly resolve issues.
• Programmatically control the mouse and keyboard to perform clicks and typing actions.

In this instructor-led, live training in Johannesburg, 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 Johannesburg (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.

The objective of this course is to build practical proficiency in applying Machine Learning techniques. Leveraging the Python programming language and its extensive array of libraries, alongside numerous hands-on examples, this course instructs participants on utilising the core components of Machine Learning. You will learn to make informed data modelling decisions, interpret algorithm outputs, and validate results effectively.

Our aim is to equip you with the confidence to understand and apply the fundamental tools within the Machine Learning toolkit, helping you to steer clear of common pitfalls associated with Data Science applications.

Python has become increasingly popular within the financial sector, adopted by major investment banks and hedge funds to create a diverse array of financial applications, from core trading systems to risk management platforms.

In this instructor-led live training, participants will discover how to leverage Python to develop practical solutions for specific finance-related challenges.

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

• Grasp the fundamentals of Python programming.
• Download, install, and manage the optimal development tools for building financial applications in Python.
• Select and employ the most appropriate Python packages and programming techniques to organise, visualise, and analyse financial data from various sources (such as CSV, Excel, databases, and web services).
• Develop applications that address issues related to asset allocation, risk analysis, investment performance, and more.
• Troubleshoot, integrate, deploy, and optimise a Python application.

Audience

• Developers
• Analysts
• Quants

Format of the course

• A blend 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 include or explore further, please contact us to arrange.

Explores practical methodologies for Data Science and AI utilizing Python, empowering professionals with the capabilities to analyse data, construct machine learning models, and implement AI-powered solutions within business environments; Addresses CRISP-DM workflows, statistical analysis, supervised and unsupervised learning, deep learning via Tensorflow, natural language processing, big data processing with Spark, and data-driven storytelling; Perfect for novices pursuing a Python data science certification and comprehensive analytics training to enhance career prospects.

Applied AI from Scratch in Python provides developers and data analysts with the essential techniques required to construct 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 explores proven methodologies for utilising scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate hands-on AI development. This enables professionals to implement practical machine learning 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 the release of Selenium 4, users benefit from enhanced WebDriver APIs, native relative locators, and improved grid support. Python, known for its simplicity and strong integration with testing frameworks such as Pytest, serves as a powerful option for creating scalable and maintainable test automation suites.

This instructor-led live training, available either online or onsite, targets beginner to intermediate testers and developers who wish to utilise Selenium with Python to automate web application testing in real-world scenarios.

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

• Install and configure Selenium alongside Python within 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 with CI/CD pipelines.
• Troubleshoot common issues and apply best practices to ensure automation stability.

Course Format

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

Course Customization Options

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

This instructor-led live training in Johannesburg (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 Johannesburg (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.
• Analyse data from sources such as Excel, CSV, JSON files and databases.
• Clean data to improve its usefulness before analysing it.
• Perform simple statistical analysis.
• Generate reports that present the desired data in just the right format, from straight numbers to data visualisations.
• Gain valuable insight from data, including trends in performance, problematic areas.

Course Overview

This practical training is tailored for professionals with a data engineering background who wish to develop hands-on expertise in artificial intelligence, Python, and large language models. The curriculum centres on real-world applications, encompassing model utilisation, prompt engineering, and the creation of AI-driven solutions. Participants will progress through structured exercises that bridge fundamental concepts with the construction of deployable AI workflows.

Format of Training

• Face-to-face classroom instruction

• Instructor-led sessions featuring guided practice

• Interactive discussions and real-world case studies

• Daily hands-on 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 master their effective application

• Design and refine prompts to ensure reliable outputs

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

• Integrate AI capabilities into data engineering pipelines

This instructor-led, live training in Johannesburg (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs easier and faster.

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 Johannesburg (available online or onsite) is targeted at data scientists who wish to employ 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 analyzing fraud data.

This instructor-led, live training in Johannesburg (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 Johannesburg (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 focused on the automated extraction, analysis, and interpretation of valuable information from digital media. Python, a high-level programming language renowned for its clear syntax and readability, serves as an ideal tool for this purpose.

Through this instructor-led live training, participants will gain a foundational understanding of Computer Vision by developing a series of simple applications using Python.

By the conclusion of this training, participants will be capable of:

• Gaining a solid grasp of Computer Vision fundamentals
• Utilising Python to execute Computer Vision tasks
• Developing custom systems for face, object, and motion detection

Audience

• Python developers interested in exploring 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 bolster their automation capabilities through Python. While shell scripting continues to be effective for straightforward tasks, Python offers substantially more flexibility, readability, and scalability for intricate automation, system administration, and DevOps workflows.