Python Training in Oslo

Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation using modern SDKs and frameworks such as LangChain and AutoGen to build, connect, 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 want to implement and orchestrate autonomous agents using Python tooling and APIs.

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

• Set up and configure Python-based environments for agentic systems.
• Use popular agent SDKs like LangChain and AutoGen to create functional agents.
• Integrate tools and APIs to extend agent capabilities.
• Orchestrate multi-agent workflows and communication patterns.
• Apply best practices for debugging, testing, and maintaining agentic codebases.

Format of the Course

• Interactive lecture and discussion.
• Hands-on programming exercises and live demos.
• Practical projects building end-to-end agent workflows.

Course Customization Options

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

This course imparts practical engineering techniques for designing, building, 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 considerations.

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

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

• Designing and implementing the agent loop and decision-making workflows.
• Integrating external tools and APIs to expand agent capabilities.
• Implementing short-term and long-term memory architectures for agents.
• Coordinating multi-step orchestrations and agent composability.
• Applying safety, access control, and observability best practices for deployed agents.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs building agents with Python and popular SDKs.
• Project-based exercises that produce deployable prototypes.

Course Customization Options

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

Artificial Intelligence with Python involves building intelligent systems by leveraging Python’s comprehensive ecosystem of AI and machine learning libraries.

This instructor-led live training, available online or on-site, is designed for intermediate-level Python programmers who want to design, implement, and deploy AI solutions using Python.

Upon completing 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 Oslo (online or onsite) is targeted at intermediate-level Python developers aiming to improve their Python development experience using AWS Cloud9.

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

• Setting up and configuring AWS Cloud9 for Python development.
• Understanding the AWS Cloud9 IDE interface and its features.
• Writing, debugging, and deploying Python applications in AWS Cloud9.
• Collaborating with other developers using the AWS Cloud9 platform.
• Integrating AWS Cloud9 with other AWS services for advanced deployments.

This instructor-led, live training in Oslo (online or on-site) targets advanced data analysts who want to utilize Python's data analysis features within Power BI, boosting their ability to analyze and visualize data effectively.

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

• Understanding how to integrate Python into Power BI for analytical tasks.
• Employing Python scripts to load, cleanse, and preprocess data directly within the Power BI environment.
• Expanding data visualization options by developing custom, interactive visuals with Python.
• Gaining advanced data analysis competencies through Python.

Python is a flexible 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 professionals aiming to leverage Python for daily data analysis, file processing, and process automation using Pandas and Polars.

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

• Use 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.

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 rigorous, practical course delves into advanced Python methodologies, engineering standards, and widely adopted design patterns, empowering you to develop maintainable, testable, and high-performance Python applications. The curriculum highlights contemporary tooling, type hints, concurrency frameworks, architectural approaches, and workflows ready for production deployment.

This instructor-led, live training session (available online or on-site) targets intermediate to advanced Python developers aiming to integrate professional practices and patterns into their production-grade Python systems.

Upon completing this training, participants will be equipped to:

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

Course Format

• Interactive lectures complemented by concise demonstrations.
• Daily hands-on labs and coding exercises.
• A capstone mini-project that integrates patterns, testing, and deployment strategies.

Customization Options

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

This instructor-led live training, conducted Oslo (either online or onsite), is designed for beginner-level developers and data analysts seeking to learn Python programming from scratch using Google Colab.

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

• Grasp the foundational concepts of the Python programming language.
• Deploy Python code within the Google Colab environment.
• Apply control structures to effectively manage the execution flow of a Python program.
• Develop functions to streamline and reuse code efficiently.
• Discover and employ fundamental libraries essential for Python programming.

This instructor-led live training (available online or onsite) is intended for developers who want to utilize the FARM stack (FastAPI, React, and MongoDB) to construct dynamic, high-performance, and scalable web applications.

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

• Setting up the required development environment that integrates FastAPI, React, and MongoDB.
• Understanding the fundamental concepts, features, and benefits of the FARM stack.
• Learning how to construct REST APIs using FastAPI.
• Learning how to design interactive applications with React.
• Developing, testing, and deploying applications (both front-end and back-end) using the FARM stack.

This instructor-led, live training in Oslo (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 program is tailored for individuals eager to master the Python programming language. The curriculum focuses heavily on the Python language itself, its core libraries, and the selection of the most valuable and effective libraries contributed by the Python community. Python is a cornerstone for businesses and a favorite among scientists worldwide, ranking among the most popular programming languages globally.

The course utilizes the latest Python version 3.x, incorporating hands-on exercises to leverage its full capabilities. It is compatible with any operating system, including all variations of UNIX (such as Linux and Mac OS X) as well as Microsoft Windows.

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

Note: The training content can be customized to meet specific requirements, provided the request is made in advance of the scheduled course date.

This instructor-led, live training in Oslo (online or onsite) is designed for developers who want 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 aiming to master the Python programming language. The curriculum focuses heavily on Python itself, its essential libraries, and the careful selection of the most valuable tools developed by the Python community. Python is a cornerstone for businesses and is widely utilized by scientists globally, cementing its status as one of the most popular programming languages.

This instructor-led, live training in Oslo 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.

During this instructor-led, live training in Oslo, participants will master the most relevant and cutting-edge machine learning techniques in Python by developing a series 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 solve complex problems.
• Apply deep learning and semi-supervised learning approaches 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 Oslo (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.

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

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

This course aims to equip participants with practical proficiency in applying Machine Learning techniques. Utilizing the Python programming language and its extensive ecosystem of libraries, alongside numerous hands-on examples, the curriculum covers the essential components of Machine Learning. It guides learners through making informed data modeling decisions, interpreting algorithm outputs, and validating results effectively.

Our objective is to provide you with the confidence to master the fundamental tools of the Machine Learning toolbox, while helping you steer clear of common pitfalls encountered in Data Science applications.

Python has surged in popularity within the financial sector, widely adopted by major investment banks and hedge funds to develop a diverse array of financial applications. These range from essential trading systems to sophisticated risk management platforms.

Through this instructor-led live training, participants will acquire the skills needed to utilize Python for developing practical applications that address specific financial challenges.

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

• Grasping the core principles of the Python programming language
• Downloading, installing, and managing optimal development tools for building financial applications in Python
• Choosing and employing the most effective Python packages and programming techniques to organize, visualize, and analyze financial data from diverse sources (such as CSV, Excel, databases, and web interfaces)
• Creating applications that resolve issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshooting, integrating, deploying, and optimizing Python applications

Audience

• Developers
• Analysts
• Quants

Format of the course

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

Note

• This training focuses on providing solutions for key challenges faced by finance professionals. If there are specific topics, tools, or techniques you wish to include or explore in greater depth, please contact us to arrange it.

Explores practical methodologies for Data Science and AI leveraging Python, empowering professionals to analyze data, develop machine learning models, and implement AI-driven solutions within business environments. The curriculum encompasses CRISP-DM workflows, statistical analysis, supervised and unsupervised learning techniques, deep learning with TensorFlow, natural language processing, big data handling via Spark, and data-driven storytelling. This course is well-suited for beginners pursuing a Python data science certification and aiming for career-ready analytics training.

The course Applied AI from Scratch in Python empowers programmers and data analysts with the foundational techniques required to build machine learning solutions from the ground up using Python. It 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. The curriculum examines proven methodologies for utilizing scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate practical AI development. Participants will learn to implement functional ML models, assess algorithmic limitations, and complete applied projects designed for solving real-world problems.

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 stands out as a powerful choice for developing scalable and maintainable test automation suites due to its simplicity and robust integration with testing frameworks such as Pytest.

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

Upon completing this training, participants will be capable of:

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

Course Format

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

Customization Options

• For a customized training session on this course, please contact us to make arrangements.

This instructor-led, live training in Oslo (online or onsite) 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 obtain insights from various datasets.
• Convert existing Matlab applications to Python.
• Integrate Matlab and Python applications.

This instructor-led, live training in Oslo (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.

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

Upon completing this training, participants will be able to:

• Use algorithms to rapidly buy and sell securities at specialized increments.
• Lower the costs associated with trading through the use of algorithmic trading.
• Automatically monitor stock prices and execute trades.

Course Overview

This practical training program is tailored for data engineering professionals aiming to develop robust skills in artificial intelligence, Python, and large language models. The curriculum emphasizes real-world applications, focusing on model utilization, prompt engineering, and the creation of AI-driven solutions. Through a series of progressive exercises, participants will advance from foundational concepts to constructing deployable AI workflows.

Training Format

• In-person classroom instruction

• Instructor-led sessions featuring guided practice

• Interactive discussions and 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 learn to utilize them effectively

• 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 Oslo (online or onsite) is designed for developers who want to use FastAPI with Python to build, test, and deploy RESTful APIs with greater ease and speed.

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 Oslo (online or on-site) targets data scientists who intend 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 Oslo (online or onsite) targets network engineers who wish to maintain, manage, and design computer networks using Python.

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

• Optimize and 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 Oslo (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 Oslo (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.

Computer Vision focuses on the automated extraction, analysis, and interpretation of valuable information from digital media. Python, recognized for its clear syntax and high readability, serves as an ideal high-level programming language for this domain.

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

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

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

Audience

• Python developers seeking to expand into 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 boost their automation skills by utilizing Python. Although shell scripting is still effective for basic tasks, Python offers substantially more flexibility, readability, and scalability for complex automation, system administration, and DevOps workflows.

Tableau serves as a prominent business intelligence and data visualization platform, while Python is a versatile programming language that supports a broad spectrum of statistical and machine learning techniques. By leveraging Tableau's robust data visualization capabilities alongside Python's advanced machine learning functions, developers can swiftly construct sophisticated data analytics applications tailored to diverse business needs.

Through this instructor-led live training, attendees will discover how to effectively merge Tableau and Python to perform high-level analytics. The integration between these two tools is achieved via the TabPy API.

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

• Integrating Tableau and Python using the TabPy API
• Utilizing the combined power of Tableau and Python to analyze intricate 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