Computer Vision with Python Training Course

This intensive, practical course delves into advanced Python techniques, engineering best practices, and widely utilized design patterns to help you develop 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-level 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:

• Apply Python typing, dataclasses, and type-checking to enhance code reliability.
• Utilize design patterns and architectural principles to structure robust applications.
• Implement concurrency and parallelism effectively 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 each day.
• Capstone mini-project integrating patterns, testing, and deployment.

Course Customization Options

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

This course delivers practical engineering methodologies for designing, building, testing, and deploying autonomous (agentic) systems using Python. The curriculum covers the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and considerations for production environments.

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

Upon completing this training, participants will be able to:

• Design and implement agent loops and decision-making workflows.
• Integrate external tools and APIs to enhance agent functionality.
• Develop short-term and long-term memory architectures for agents.
• Coordinate multi-step orchestrations and enable agent composability.
• Apply best practices for safety, access control, and observability in deployed agents.

Course Format

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

Customization Options

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

Explores practical methodologies for Data Science and AI leveraging Python. It equips professionals with the capabilities to analyze data, construct machine learning models, and implement AI-driven applications within business settings. The curriculum encompasses CRISP-DM workflows, statistical analysis, supervised and unsupervised learning, deep learning via TensorFlow, natural language processing, big data processing with Spark, and data-driven storytelling. This course is ideal for beginners aiming for a Python data science certification and career-ready 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 onsite, targets intermediate-level Python developers looking to design, implement, and deploy AI solutions using Python.

Upon completing this training, participants will be able 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.

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.

The CANN SDK (Compute Architecture for Neural Networks) delivers robust deployment and optimization capabilities for real-time AI applications in computer vision and natural language processing, particularly on Huawei Ascend hardware.

This instructor-led, live training, available online or onsite, is designed for intermediate-level AI practitioners looking to build, deploy, and optimize vision and language models using the CANN SDK for production scenarios.

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

• Deploy and optimize CV and NLP models leveraging CANN and AscendCL.
• Utilize CANN tools to convert models and integrate them into active pipelines.
• Enhance inference performance for tasks such as detection, classification, and sentiment analysis.
• Construct real-time CV/NLP pipelines tailored for edge or cloud-based deployment.

Course Format

• Interactive lectures combined with live demonstrations.
• Practical labs focused on model deployment and performance profiling.
• Designing live pipelines using real-world CV and NLP use cases.

Customization Options

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

This instructor-led, live training in Serbia (online or onsite) is aimed at intermediate-level AI developers and computer vision engineers who wish to build robust vision systems for autonomous driving applications.

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

• Understand the fundamental concepts of computer vision in autonomous vehicles.
• Implement algorithms for object detection, lane detection, and semantic segmentation.
• Integrate vision systems with other autonomous vehicle subsystems.
• Apply deep learning techniques for advanced perception tasks.
• Evaluate the performance of computer vision models in real-world scenarios.

This instructor-led live training Serbia (available online or on-site) targets advanced professionals who aim to deepen their grasp of computer vision and explore TensorFlow's capabilities for developing sophisticated vision models using Google Colab.

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

• Build and train convolutional neural networks (CNNs) using TensorFlow.
• Leverage Google Colab for scalable and efficient cloud-based model development.
• Implement image preprocessing techniques for computer vision tasks.
• Deploy computer vision models for real-world applications.
• Use transfer learning to enhance the performance of CNN models.
• Visualize and interpret the results of image classification models.

This instructor-led, live training in Serbia (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 in Serbia (online or onsite) is aimed at intermediate-level to advanced-level computer vision engineers, AI developers, and IoT professionals who wish to implement and optimize computer vision models for real-time processing on edge devices.

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

• Understand the fundamentals of Edge AI and its applications in computer vision.
• Deploy optimized deep learning models on edge devices for real-time image and video analysis.
• Use frameworks like TensorFlow Lite, OpenVINO, and NVIDIA Jetson SDK for model deployment.
• Optimize AI models for performance, power efficiency, and low-latency inference.

This instructor-led, live training in Serbia (online or onsite) is designed for beginner-level law enforcement officers who wish to transition from manual facial sketching to utilizing AI tools for developing facial recognition systems.

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

• Understand the core principles of Artificial Intelligence and Machine Learning.
• Learn the basics of digital image processing and its application in facial recognition.
• Develop proficiency in using AI tools and frameworks to build facial recognition models.
• Gain hands-on experience in creating, training, and testing facial recognition systems.
• Understand ethical considerations and best practices in the use of facial recognition technology.

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

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

• Configure the necessary development environment integrating FastAPI, React, and MongoDB.
• Comprehend the key concepts, features, and benefits of the FARM stack.
• Build REST APIs using FastAPI.
• Design interactive applications with React.
• Develop, test, and deploy applications (both front end and back end) using the FARM stack.

This instructor-led live training in Serbia (online or onsite) is intended for developers who want to use FastAPI with Python to build, test, and deploy RESTful APIs with greater speed and ease.

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

• Set up the required development environment to build APIs with Python and FastAPI.
• Create APIs faster and more easily 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 FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

This instructor-led, live training in Serbia (online or onsite) is aimed at beginner-level to intermediate-level researchers and laboratory professionals who wish to process and analyze images related to histological tissues, blood cells, algae, and other biological samples.

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

• Navigate the Fiji interface and utilize ImageJ’s core functions.
• Preprocess and enhance scientific images for better analysis.
• Analyze images quantitatively, including cell counting and area measurement.
• Automate repetitive tasks using macros and plugins.
• Customize workflows for specific image analysis needs in biological research.

This instructor-led, live training in Serbia (online or onsite) targets intermediate-level professionals aiming to utilize Vision Builder AI for the design, implementation, and optimization of automated inspection systems within SMT (Surface-Mount Technology) processes.

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

• Setting up and configuring automated inspections using Vision Builder AI.
• Acquiring and preprocessing high-quality images for analysis.
• Implementing logic-based decision-making for defect detection and process validation.
• Generating inspection reports and optimizing overall system performance.

This instructor-led, live training in Serbia (online or on-site) is designed for intermediate to advanced developers, researchers, and data scientists seeking to implement real-time object detection using YOLOv7.

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

• Understand the fundamental concepts of object detection.
• Install and configure YOLOv7 for object detection tasks.
• Train and test custom object detection models using YOLOv7.
• Integrate YOLOv7 with other computer vision frameworks and tools.
• Troubleshoot common issues related to YOLOv7 implementation.