Online Python Training in Kenya

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 build, connect, and manage agent workflows effectively.

Delivered as an instructor-led live training (available online or on-site), 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 able to:

• Set up and configure Python-based environments tailored for agentic systems.
• Utilise popular agent SDKs, including LangChain and AutoGen, to develop functional agents.
• Integrate tools and APIs to enhance 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 a customized training version of this course, please contact us to arrange.

This course imparts practical engineering techniques for designing, building, testing, and deploying autonomous agentic systems using Python. It explores the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production readiness.

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

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

• Design and implement the agent loop along with decision-making workflows.
• Integrate external tools and APIs to expand 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 focused on 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 make arrangements.

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

Delivered through an instructor-led live training format, available either online or onsite, this program is designed for intermediate Python developers who aim to design, implement, and deploy AI solutions.

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

• Develop AI algorithms utilizing Python’s core AI libraries.
• Utilize supervised, unsupervised, and reinforcement learning models.
• Seamlessly integrate AI solutions into current applications and workflows.
• Assess model performance and optimize them for both accuracy and efficiency.

Course Format

• Engaging lectures and interactive discussions.
• Ample opportunities for exercises and practical application.
• Hands-on implementation within a live-lab environment.

Customization Options

• For those interested in a customized training version of this course, please get in touch with us to make arrangements.

This instructor-led, live training in Kenya (online or onsite) targets intermediate Python developers seeking to improve their development experience with AWS Cloud9.

By the conclusion 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 Kenya (online or onsite) targets 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 highly adaptable programming language extensively utilized for data manipulation, automation, and analytics. Libraries such as Pandas and Polars offer robust, practical tools for handling large-scale tabular data.

This instructor-led, live training (available online or onsite) targets beginner to intermediate-level professionals eager to apply Python for daily data analysis, file processing, and process automation using Pandas and Polars.

Upon completing this training, participants will be able to:

• Utilize Python to read, transform, and write CSV and Excel files.
• Execute standard data cleaning and transformation tasks with Pandas and Polars.
• Automate repetitive data processes using Python scripts.
• Package simple scripts into executables and adhere to project best practices.

Course Format

• Interactive coding demonstrations alongside concise lectures.
• Practical exercises featuring guided code examples.
• Practical mini-projects designed to automate real-world tasks.

Course Customization Options

• For customized training requests, please reach out to us to arrange.

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

Offered as instructor-led live training (available online or on-site), this program is tailored 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 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 with pytest, property-based testing, and CI pipelines.
• Profile, optimize, and secure Python applications for production environments.
• Package, distribute, and deploy Python projects using contemporary tools and containers.

Course Format

• Interactive lectures complemented by short demonstrations.
• Hands-on labs and coding exercises every day.
• A capstone mini-project integrating patterns, testing, and deployment.

Course Customization Options

• To request a customized training session or focus area (data, web, or infrastructure), please contact us to arrange.

This instructor-led live training in Kenya (online or onsite) is aimed at beginner-level 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 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, available online or onsite, targets developers who wish to utilize 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 Kenya (online or onsite) is designed for beginner to intermediate robotics developers, and potentially advanced-level professionals, 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.
• Troubleshooting and debugging ROS applications.

This course is tailored for individuals eager to master the Python programming language. The curriculum focuses heavily on Python itself, its core libraries, and the selection of the most valuable libraries cultivated by the Python community. Python powers businesses globally and is utilized by scientists worldwide, establishing itself as one of the most popular programming languages.

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

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

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

This instructor-led, live training in Kenya (online or on-site) is designed for developers eager to master advanced Python programming techniques. The course covers applying this versatile language to solve challenges in distributed applications, data analysis and visualization, UI programming, and maintenance scripting.

This course is tailored for individuals eager to master the Python programming language. The curriculum focuses on the Python language itself, its core libraries, and the careful selection of the most valuable tools created by the Python community. Python is a globally renowned programming language, powering businesses and utilized by scientists worldwide.

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

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

• Automate routine tasks by writing simple Python scripts.
• Create programs that perform text pattern recognition using "regular expressions".
• Programmatically generate and update Excel spreadsheets.
• Parse PDF and Word documents.
• Crawl websites and extract data from online sources.
• Develop programs that send email notifications.
• Utilize Python's debugging tools to quickly identify and fix bugs.
• Programmatically control the mouse and keyboard to click and type on your behalf.

In this instructor-led, live training session, participants will master the most relevant and cutting-edge machine learning techniques in Python by developing a series of demonstration applications that handle image, music, text, and financial data.

Upon completing this training, participants will be able to:

• Implement machine learning algorithms and techniques to solve complex problems.
• Apply deep learning and semi-supervised learning 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 instructor-led, live training in Kenya (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.

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

• Set up a development environment that includes Python, Pandas, and NumPy.
• Create a data analysis application using Pandas and NumPy.
• Perform advanced data wrangling, sorting, and filtering operations.
• Conduct aggregate operations and analyze time series data.
• Visualize data using Matplotlib and other visualization libraries.
• Debug and optimize their data analysis code.

This course is designed to equip participants with practical proficiency in applying Machine Learning methodologies. Utilizing the Python programming language alongside its extensive ecosystem of libraries, and grounded in numerous real-world examples, the curriculum covers the essential components of Machine Learning. It guides learners through making informed data modeling decisions, interpreting algorithmic outputs, and validating results effectively.

Our primary objective is to empower you with the confidence to master and utilize core Machine Learning tools while helping you sidestep the frequent challenges encountered in Data Science applications.

Python has become increasingly popular within the financial sector. It is widely adopted by major investment banks and hedge funds to develop 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 create practical solutions for various financial challenges.

Upon completing this training, participants will be able to:

• Grasp the fundamental concepts of the Python programming language
• Download, install, and manage the most effective development tools for building financial applications in Python
• Choose and apply appropriate Python packages and programming techniques to organize, visualize, and analyze financial data from diverse sources such as CSV files, Excel spreadsheets, databases, and web interfaces
• Develop applications that address issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimize Python applications

Audience

• Developers
• Analysts
• Quants

Format of the course

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

Note

• While this training focuses on providing solutions to key challenges faced by finance professionals, if you have specific topics, tools, or techniques you wish to explore in greater depth, please contact us to arrange customized content.

This course provides a comprehensive exploration of practical Data Science and Artificial Intelligence techniques using Python. It empowers professionals with the essential skills to investigate data, construct machine learning models, and implement AI-driven solutions within business environments. The curriculum covers CRISP-DM methodologies, statistical analysis, supervised and unsupervised learning, deep learning with TensorFlow, natural language processing, big data processing with Spark, and data-driven storytelling. It is ideally suited for beginners pursuing a Python data science certification and those seeking career-ready analytics training.

Applied AI from Scratch in Python empowers software developers and data analysts with essential techniques for constructing machine learning solutions from the ground up using Python. The course covers fundamental concepts such as supervised learning (classification and regression), unsupervised learning (clustering and anomaly detection), and advanced neural network structures. It explores effective strategies for utilizing scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate practical AI development. Participants will learn to deploy functional ML models, assess algorithm constraints, and execute applied projects aimed at solving 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 have access to enhanced WebDriver APIs, native relative locators, and improved grid support. Python complements this by offering simplicity and robust integration with testing frameworks such as Pytest, making it an excellent choice for creating scalable and maintainable test automation suites.

This instructor-led live training, available online or on-site, targets beginner to intermediate testers and developers who want to leverage Selenium with Python to automate web application testing in practical, real-world scenarios.

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

• Install and configure Selenium with Python within a test environment.
• Develop robust test automation scripts using Selenium WebDriver and Pytest.
• Utilize 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 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 customized training for this course, please contact us to arrange.

This instructor-led, live training in Kenya (online or onsite) is designed for Matlab users who wish to explore or transition to Python for data analytics and visualization.

Upon completing this training, participants will be able to:

• Install and set up a Python development environment.
• Comprehend the differences and similarities between Matlab and Python syntax.
• Utilise Python to extract insights from diverse datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

This instructor-led, live training in Kenya (online or on-site) is aimed at individuals who wish to learn just enough Python to start 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.

Course Overview

This practical training programme is tailored for data engineering professionals looking to develop hands-on competencies in artificial intelligence, Python, and large language models. The curriculum emphasizes real-world application, addressing model utilization, prompt engineering, and the construction of AI-driven solutions. Attendees will engage in a series of progressive exercises that transition from foundational principles to the creation of deployable AI workflows.

Training Format

• In-person classroom instruction

• Instructor-led sessions incorporating guided practice

• Interactive discussions complemented by real-world case studies

• Daily practical exercises

Course Objectives

• Grasp core artificial intelligence and machine learning concepts pertinent to contemporary applications

• Enhance Python proficiency for AI development and data workflow management

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

• Design and refine prompts to ensure consistent and reliable outputs

• Develop end-to-end AI solutions leveraging APIs and frameworks

• Integrate AI capabilities into data engineering pipelines

This instructor-led, live training in Kenya (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 Kenya (online or onsite) is tailored for data scientists who aim 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 Kenya (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 Kenya (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 entails the automatic extraction, analysis, and interpretation of valuable insights from digital media. Python stands out as a high-level programming language renowned for its straightforward syntax and code readability.

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

Upon completing this training, participants will be capable of:

• Grasping the foundational concepts of Computer Vision
• Utilizing Python to execute Computer Vision tasks
• Developing custom systems for face, object, and motion detection

Target Audience

• Python developers interested in exploring Computer Vision

Course Format

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

This practical course is designed for Unix and shell users looking to enhance their automation capabilities by leveraging Python. While shell scripting remains powerful for simple tasks, Python provides significantly greater flexibility, readability, and scalability for complex automation, system administration, and DevOps workflows.