Python for Data Tasks: Basic & Intermediate with Pandas and Polars Training Course

This intensive, practical course delves into advanced Python methodologies, engineering standards, and widely adopted design patterns to develop scalable, testable, and high-performance applications. The curriculum prioritizes modern development tools, robust typing, concurrency models, architectural strategies, and deployment-ready workflows.

Delivered by instructors in a live format (either online or onsite), this program is designed for intermediate to advanced Python developers looking to integrate professional practices and patterns into production-grade systems.

Upon completion, participants will be equipped to:

• Enhance code reliability by applying Python typing, dataclasses, and type-checking mechanisms.
• Structure robust applications by leveraging design patterns and architectural principles.
• Correctly implement concurrency and parallelism using asyncio and multiprocessing.
• Create well-tested codebases using pytest, property-based testing, and CI pipelines.
• Profile, optimize, and harden Python applications for production environments.
• Package, distribute, and deploy Python projects utilizing modern tools and containers.

Course Format

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

Customization Options

• For customized training or specific focus areas (such as data, web, or infrastructure), please reach out to us to make arrangements.

This course focuses on practical engineering methods for designing, developing, testing, and deploying agentic (autonomous) systems using Python. The curriculum encompasses the agent loop, tool integration, memory and state management, orchestration patterns, safety controls, and key production considerations.

This instructor-led live training, available online or onsite, targets intermediate to advanced ML engineers, AI developers, and software engineers aiming to construct robust, production-ready autonomous agents with Python.

Upon completing this training, participants will be equipped to:

• Design and execute agent loops and 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 best practices for safety, access control, and observability in deployed agents.

Course Format

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

Course Customization Options

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

 This course explores the practical application of Data Science and AI through the use of Python, enabling professionals to analyze data, construct machine learning models, and implement AI-driven solutions within business environments. The curriculum covers CRISP-DM methodologies, statistical analysis, both supervised and unsupervised learning techniques, deep learning using Tensorflow, natural language processing, big data handling with Spark, and data-driven storytelling. It is well-suited for beginners aiming for Python data science certification and comprehensive, career-oriented analytics training.

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 online or on-site) is designed for intermediate-level Python programmers looking to design, implement, and deploy AI solutions using Python.

Upon completion, participants will be equipped to:

• Implement AI algorithms utilizing 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.

Course Format

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

Course Customization Options

• Please contact us to arrange customized training for this course.

This course, Applied AI from Scratch in Python, empowers developers and data analysts to construct machine learning solutions from the ground up using Python. It explores the core tenets of supervised learning, including classification and regression, as well as unsupervised learning techniques such as clustering and anomaly detection, alongside advanced neural network designs. The curriculum features established workflows for utilizing scikit-learn, Apache Spark MLlib, and Jupyter notebooks to facilitate hands-on AI development. This program enables professionals to deploy practical ML models, assess algorithmic constraints, and execute applied projects designed to solve real-world challenges.

This instructor-led, live training in Denmark (online or onsite) is designed for intermediate-level Python developers aiming to improve their Python development capabilities with AWS Cloud9.

After 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.

Course Summary

Tailored for data engineering professionals seeking to enhance their capabilities in artificial intelligence, Python, and large language models, this practical training emphasizes real-world implementation. The curriculum guides learners through model application, prompt engineering, and the development of AI-driven solutions. Through progressive exercises, participants advance from foundational concepts to the creation of ready-to-deploy AI workflows.

Training Delivery

• In-person classroom instruction

• Instructor-guided sessions with structured practice

• Interactive debates and industry case studies

• Daily practical tasks

Learning Goals

• Grasp key AI and machine learning principles applicable to contemporary systems

• Enhance Python proficiency for AI development and data processing

• Comprehend the mechanics of large language models and their effective utilization

• Craft and refine prompts to ensure consistent results

• Develop complete AI solutions leveraging APIs and frameworks

• Embed AI capabilities into data engineering pipelines

This instructor-led, live training in Denmark (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 live, instructor-led training, offered both online and on-site, is tailored for developers aiming to utilize the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications.

By the end of this program, participants will be equipped to:

• Configure a development environment that integrates FastAPI, React, and MongoDB.
• Comprehend the essential concepts, capabilities, and benefits of the FARM stack.
• Develop REST APIs using FastAPI.
• Design interactive user interfaces with React.
• Build, test, and deploy full-stack applications (front-end and back-end) using the FARM stack.

This instructor-led live training in Denmark (available online or on-site) is designed for developers aiming to leverage FastAPI with Python to build, test, and deploy RESTful APIs with improved ease and speed.

By the end of the session, participants will be capable of:

• Establishing the required development environment for creating APIs with Python and FastAPI.
• Accelerating API development using the FastAPI library.
• Gaining proficiency in creating data models and schemas based on Pydantic and OpenAPI.
• Connecting APIs to databases using SQLAlchemy.
• Implementing security and authentication features using FastAPI utilities.
• Building container images and deploying web APIs to cloud servers.

This instructor-led, live training is delivered in Denmark (online or on-site) and is targeted at data scientists who aim to utilize TensorFlow for analyzing potential fraud data.

Upon completion, participants will be equipped to:

• Develop a fraud detection model using Python and TensorFlow.
• Construct linear regression models to effectively predict fraudulent behavior.
• Engineer a comprehensive, end-to-end AI application tailored for fraud data analysis.

This course is designed to equip you with the practical skills necessary to apply Machine Learning methods effectively. By leveraging the Python programming language and its extensive ecosystem of libraries, you will gain hands-on experience through numerous real-world examples. The curriculum focuses on mastering the core components of Machine Learning, making informed data modeling choices, interpreting algorithmic outputs, and rigorously validating results.

Our objective is to empower you to confidently utilize the foundational tools within the Machine Learning toolbox, while steering clear of common pitfalls often encountered in Data Science applications.

This instructor-led live training, delivered in Denmark (online or onsite), is designed for network engineers seeking to maintain, manage, and design computer networks using Python.

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

• Optimize network automation by leveraging Paramiko, Netmiko, Napalm, Telnet, and pyntc with Python.
• Master the concepts of multi-threading and multiprocessing in network automation.
• Utilize GNS3 and Python for network programming projects.

This instructor-led live training in Denmark (available online or onsite) is designed for 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 course is tailored for individuals looking to master the Python programming language. It focuses on core language features and essential standard libraries, alongside a curated selection of the most valuable packages from the wider Python community. As a language that powers businesses and is widely adopted by scientists globally, Python stands as one of the most popular choices in modern software development.