Python Training in Uppsala

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

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

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

• Setting up and configuring Python-based environments for agentic systems.
• Leveraging popular agent SDKs like LangChain and AutoGen to build 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 construction.

Course Customization Options

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

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

Delivered as an instructor-led, live training session (available online or onsite), this programme is designed for intermediate to advanced ML engineers, AI developers, and software engineers who aim to build robust, production-grade autonomous agents in Python.

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

• Designing and implementing agent loops and decision-making workflows.
• Integrating external tools and APIs to enhance agent functionality.
• Implementing both short-term and long-term memory architectures for agents.
• Coordinating multi-step orchestrations and enabling agent composability.
• Applying best practices for safety, access control, and observability in deployed agents.

Course Format

• Interactive lectures and discussions.
• Hands-on labs for building agents using Python and popular SDKs.
• Project-based exercises resulting in deployable prototypes.

Customization Options

• To request a tailored training session 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 training, available both online and onsite, is designed for intermediate-level 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.
• Extensive 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 Uppsala (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 session Uppsala (online or onsite) targets advanced data analysts looking to exploit Python's analytical power within Power BI to refine their data interpretation and visualization skills.

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

• Understand the integration of Python into Power BI for analytical purposes.
• Employ Python scripts to manage data loading, cleansing, and preprocessing within Power BI.
• Upgrade data visualization capabilities by crafting bespoke and interactive visuals with Python.
• Gain advanced data analysis skills through Python.

Python is a highly versatile programming language, extensively utilized for data manipulation, automation, and analytics. Libraries such as Pandas and Polars offer robust, practical tools for managing tabular data at scale.

This instructor-led live training (available online or on-site) is designed for professionals at the beginner to intermediate levels who want to apply Python for daily data analysis, file processing, and process automation using Pandas and Polars.

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

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

Course Format

• Interactive coding demonstrations and concise lectures.
• Hands-on exercises with guided code examples.
• Practical mini-projects focused on automating real-world tasks.

Course Customization Options

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

This intensive, hands-on 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 emphasizes 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:

• Leverage 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 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 every day.
• A capstone mini-project that integrates patterns, testing, and deployment.

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 Uppsala (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, offered online or onsite, targets developers who intend to utilize the FARM (FastAPI, React, and MongoDB) stack to create dynamic, high-performance, and scalable web applications.

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

• Set up the necessary development environment integrating FastAPI, React, and MongoDB.
• Understand the key concepts, features, and benefits of the FARM stack.
• Learn how to build REST APIs with FastAPI.
• Learn how to design interactive applications with React.
• Develop, test, and deploy applications (front end and back end) using the FARM stack.

This instructor-led, live training in Uppsala (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 looking to master the Python programming language. The focus lies on the Python language itself, its core libraries, and the selection of the most valuable and effective libraries created by the Python community. Python powers businesses globally and is widely used by scientists around the world, making it one of the most popular programming languages.

Participants will learn using the latest Python version 3.x, with hands-on exercises designed to unlock its full potential. The course is compatible with any operating system, including all variants of UNIX (such as Linux and Mac OS X) as well as Microsoft Windows.

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

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

This instructor-led, live training in Uppsala (online or onsite) is designed for developers seeking 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 intended for individuals aiming to master the Python programming language. It places significant focus on the Python language itself, essential core libraries, and the selection of the most valuable and effective libraries contributed by the Python community. Widely utilized by businesses and scientists globally, Python stands as one of the most prevalent programming languages in the world.

This instructor-led, live training in Uppsala 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 Uppsala, 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 Uppsala (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 the practical skills necessary to apply Machine Learning techniques effectively. By leveraging the Python programming language and its extensive ecosystem of libraries, along with numerous hands-on examples, learners will master the essential components of Machine Learning. The curriculum covers making informed data modeling decisions, interpreting algorithm outputs, and validating results to ensure accuracy.

Our objective is to empower you with the confidence to utilize fundamental Machine Learning tools while helping you steer clear of the common pitfalls associated with Data Science applications.

Python has become immensely popular within the financial sector. Adopted by major investment banks and hedge funds, it is utilized to develop a broad spectrum of financial applications, from core trading systems to risk management platforms.

Through this instructor-led live training, participants will learn how to leverage Python to create practical solutions for specific finance-related challenges.

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

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

Target Audience

• Developers
• Analysts
• Quantitative Analysts (Quants)

Course Format

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

Note

• This training is designed to provide solutions for key problems encountered by finance professionals. If you have a specific topic, tool, or technique you wish to add or explore in greater depth, please contact us to arrange this.

This course explores practical methodologies for Data Science and AI through Python, empowering professionals with the expertise to analyze data, construct machine learning models, and deploy AI-powered solutions within business environments. The curriculum encompasses CRISP-DM workflows, statistical analysis, supervised and unsupervised learning, deep learning with TensorFlow, natural language processing, big data analytics with Spark, and data-driven storytelling. It is ideal for beginners pursuing a Python data science certification and career-focused analytics training.

This course empowers developers and data analysts with the essential techniques required to construct machine learning solutions from the ground up using Python. It explores the fundamental principles of supervised learning, including classification and regression, as well as unsupervised learning methods such as clustering and anomaly detection, alongside advanced neural network structures. Participants will examine proven strategies for utilizing scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate practical AI development. The program supports professionals in deploying effective ML models, assessing algorithm constraints, and delivering applied projects tailored to 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, known for its simplicity and robust integration with testing frameworks such as Pytest, serves as a powerful choice for developing scalable and maintainable test automation suites.

This instructor-led, live training (available online or onsite) targets beginner to intermediate-level testers and developers who want to leverage 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 with Python within a test environment.
• Create robust test automation scripts using Selenium WebDriver and Pytest.
• Utilize the Page Object Model (POM) for maintaining test frameworks.
• Execute tests across multiple browsers via Selenium Grid.
• Integrate automated tests with CI/CD pipelines.
• Resolve common issues and apply best practices to ensure automation stability.

Course Format

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

Course Customization Options

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

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

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

• Set up and configure a Python development environment.
• Compare and contrast the syntax of Matlab and Python.
• Leverage Python to derive insights from diverse datasets.
• Translate existing Matlab applications into Python.
• Integrate Matlab and Python applications.

This instructor-led, live training in Uppsala (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 the right format, from straight numbers to data visualizations.
• Gain valuable insights from data, including trends in performance and problematic areas.

Course Overview

This practical training program is tailored for data engineering professionals looking to develop concrete skills in artificial intelligence, Python, and large language models. The curriculum emphasizes real-world applications, addressing model utilization, prompt engineering, and the creation of AI-driven solutions. Participants will engage in progressive exercises that advance from fundamental concepts to the development of deployable AI workflows.

Training Format

• On-site classroom instruction

• Instructor-led sessions featuring guided practice

• Interactive discussions alongside 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 learn to utilize them effectively

• Design and refine prompts to ensure reliable outputs

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

• Integrate AI capabilities into data engineering pipelines

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

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

• Set up the required development environment for creating APIs with Python and FastAPI.
• Develop APIs faster and with greater ease using the FastAPI library.
• Learn to create data models and schemas based on Pydantic and OpenAPI.
• Connect APIs to databases using SQLAlchemy.
• Implement security and authentication in APIs using FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

This instructor-led, live training in Uppsala (online or onsite) is aimed at 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 Uppsala (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 Uppsala (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 domain focused on the automatic extraction, analysis, and comprehension of valuable insights from digital media. Python stands out as a high-level programming language, renowned for its clean syntax and code readability.

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

Upon completing this training, participants will be able to:

• Grasp the core concepts of Computer Vision
• Utilize Python to execute Computer Vision tasks
• Develop custom systems for face, object, and motion detection

Audience

• Python developers interested in Computer Vision

Course Format

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

This practical course is tailored for Unix and shell users aiming to boost their automation skills through Python. Although shell scripting is still effective for basic tasks, Python offers much more flexibility, readability, and scalability for handling complex automation, system administration, and DevOps workflows.