Python for Matlab Users Training Course

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 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.

This is a 5 day introduction to Data Science and Artificial Intelligence (AI).

The course is delivered with examples and exercises using Python

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 Norway (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.

This is a 4-day course that introduces AI and its application using the Python programming language. Participants can opt for an extra day to undertake an AI project upon completion of this course.

This instructor-led live training in Norway (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.

Chatbots are computer programs that automatically simulate human responses via chat interfaces. Chatbots help organizations maximize their operations efficiency by providing easier and faster options for their user interactions.

In this instructor-led, live training, participants will learn how to build chatbots in Python.

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

• Understand the fundamentals of building chatbots
• Build, test, deploy, and troubleshoot various chatbots using Python

Audience

• Developers

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

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

This instructor-led, live training in Norway (online or onsite) is designed for intermediate-level developers who want to leverage CUDA to build Python applications that execute in parallel on NVIDIA GPUs.

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

• Utilizing the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
• Creating, compiling, and launching custom CUDA kernels.
• Managing GPU memory.
• Transforming CPU-based applications into GPU-accelerated applications.

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 Norway (online or onsite) is designed for data scientists and software engineers who wish to use Dask with the Python ecosystem to build, scale, and analyze large datasets.

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

• Configure the necessary environment to begin building big data processing solutions using Dask and Python.
• Explore the features, libraries, tools, and APIs available in Dask.
• Understand how Dask accelerates parallel computing within Python.
• Learn how to scale the Python ecosystem (including Numpy, SciPy, and Pandas) using Dask.
• Optimize the Dask environment to ensure high performance when handling large datasets.

This instructor-led, live training in Norway (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 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 Norway (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 Norway (online or onsite) is aimed at data scientists and developers who wish to use Modin to build and implement parallel computations with Pandas for faster data analysis.

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

• Set up the necessary environment to start developing Pandas workflows at scale with Modin.
• Understand the features, architecture, and advantages of Modin.
• Know the differences between Modin, Dask, and Ray.
• Perform Pandas operations faster with Modin.
• Implement the entire Pandas API and functions.