Praktyczne szkolenia Sztuczna inteligencja, Szkolenia AI, Szkolenia Artificial Intelligence, Szkolenia Synthetic Intelligence.
Szkolenie Artificial Intelligence jest dostępne jako "szkolenie stacjonarne" lub "szkolenie online na żywo".
Szkolenie stacjonarne może odbywać się lokalnie w siedzibie klienta w Toruń lub w ośrodkach szkoleniowych NobleProg w Toruń. Zdalne szkolenie online odbywa się za pomocą interaktywnego, zdalnego pulpitu.
NobleProg -- Twój lokalny dostawca szkoleń.
Toruń
Sale szkoleniowe NobleProg, Bydgoska 1, Toruń, poland, 87-100
Sale szkoleniowe NobleProg w Toruniu znajdują się w biurze Coworking Toruń przy ulicy Bydgoskiej 1
Building AI Solutions on the Edge focuses on the step-by-step creation and deployment of AI models on edge devices. This course includes practical projects and real-world applications, providing participants with hands-on experience in developing and implementing AI solutions directly on edge hardware.This instructor-led, live training (online or onsite) is aimed at intermediate-level developers, data scientists, and tech enthusiasts who wish to gain practical skills in deploying AI models on edge devices for various applications.By the end of this training, participants will be able to:
Understand the principles of Edge AI and its benefits.
Set up and configure the edge computing environment.
Develop, train, and optimize AI models for edge deployment.
Implement practical AI solutions on edge devices.
Evaluate and improve the performance of edge-deployed models.
Address ethical and security considerations in Edge AI applications.
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.
Edge AI for IoT Applications focuses on the integration of Edge AI with IoT systems, enabling real-time data processing and decision-making directly on IoT devices. This course covers the foundational concepts, tools, and techniques required to implement Edge AI in IoT environments.This instructor-led, live training (online or onsite) is aimed at intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI for enhancing IoT applications with intelligent data processing and analytics capabilities.By the end of this training, participants will be able to:
Understand the fundamentals of Edge AI and its application in IoT.
Set up and configure Edge AI environments for IoT devices.
Develop and deploy AI models on edge devices for IoT applications.
Implement real-time data processing and decision-making in IoT systems.
Integrate Edge AI with various IoT protocols and platforms.
Address ethical considerations and best practices in Edge AI for IoT.
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.
Edge AI is the deployment and operation of AI models directly on edge devices, such as smartphones, IoT devices, and sensors, enabling real-time data processing and decision-making.This instructor-led, live training (online or onsite) is aimed at intermediate-level developers and IT professionals who wish to gain a comprehensive understanding of Edge AI from concept to practical implementation, including setup and deployment.By the end of this training, participants will be able to:
Understand the fundamental concepts of Edge AI.
Set up and configure Edge AI environments.
Develop, train, and optimize Edge AI models.
Deploy and manage Edge AI applications.
Integrate Edge AI with existing systems and workflows.
Address ethical considerations and best practices in Edge AI implementation.
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.
Edge AI is the deployment and operation of AI models directly on edge devices, such as smartphones, IoT devices, and sensors, enabling real-time data processing and decision-making.This instructor-led, live training (online or onsite) is aimed at beginner-level developers and IT professionals who wish to understand the fundamentals of Edge AI and its introductory applications.By the end of this training, participants will be able to:
Understand the basic concepts and architecture of Edge AI.
Set up and configure Edge AI environments.
Develop and deploy simple Edge AI applications.
Identify and understand the use cases and benefits of Edge AI.
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.
Multimodal AI opens up new possibilities for content creation across various media.This instructor-led, live training (online or onsite) is aimed at intermediate-level content creators, digital artists and media professionals who wish to learn how multimodal AI can be applied to various forms of content creation.By the end of this training, participants will be able to:
Use AI tools to enhance music and video production.
Generate unique visual art and designs with AI.
Create interactive multimedia experiences.
Understand the impact of AI on the creative industries.
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.
Multimodal AI is key to building advanced robotic systems that can interact with their environment in complex ways.This instructor-led, live training (online or onsite) is aimed at advanced-level robotics engineers and AI researchers who wish to utilize Multimodal AI for integrating various sensory data to create more autonomous and efficient robots that can see, hear, and touch.By the end of this training, participants will be able to:
Implement multimodal sensing in robotic systems.
Develop AI algorithms for sensor fusion and decision-making.
Create robots that can perform complex tasks in dynamic environments.
Address challenges in real-time data processing and actuation.
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.
Multimodal AI is revolutionizing user experience by enabling more natural interactions with technology.This instructor-led, live training (online or onsite) is aimed at intermediate-level UX/UI designers and front-end developers who wish to utilize Multimodal AI to design and implement user interfaces that can understand and process various forms of input.By the end of this training, participants will be able to:
Design multimodal interfaces that improve user engagement.
Integrate voice and visual recognition into web and mobile applications.
Utilize multimodal data to create adaptive and responsive UIs.
Understand the ethical considerations of user data collection and processing.
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.
Multimodal AI is an innovative field that combines information from various sensory inputs to create systems that understand and interact with the world in a more human-like manner.This instructor-led, live training (online or onsite) is aimed at intermediate-level AI researchers, data scientists, and machine learning engineers who wish to create intelligent systems that can process and interpret multimodal data.By the end of this training, participants will be able to:
Understand the principles of multimodal AI and its applications.
Implement data fusion techniques to combine different types of data.
Build and train models that can process visual, textual, and auditory information.
Evaluate the performance of multimodal AI systems.
Address ethical and privacy concerns related to multimodal data.
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.
AI Coding Assistants are tools designed to improve the efficiency and creativity of software developers.This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level software developers who wish to integrate AI coding assistants into their development workflow.By the end of this training, participants will be able to:
Understand the role and capabilities of AI coding assistants in software development.
Utilize various AI coding assistant tools to automate routine coding tasks.
Integrate AI coding assistants into their software development lifecycle.
Enhance their productivity and focus on more complex and creative programming tasks.
Address ethical considerations and responsible use of AI in software development.
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.
AI-Augmented Software Engineering (AIASE) is the application of artificial intelligence to enhance and automate tasks within the software engineering process.This instructor-led, live training (online or onsite) is aimed at intermediate-level software professionals who wish to leverage AI and machine learning to improve efficiency and innovation in software development.By the end of this training, participants will be able to:
Understand the role of AI and machine learning in automating software development tasks.
Implement AI tools to generate code, tests, and documentation.
Apply AI techniques for code optimization, quality assurance, and debugging.
Integrate AI into the DevOps and CI/CD pipelines for improved deployment strategies.
Address ethical considerations and challenges in AI-augmented software engineering.
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.
AI TRiSM is an emerging field that addresses the need for trustworthiness, risk management, and security in AI systems.This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level IT professionals who wish to understand and implement AI TRiSM in their organizations.By the end of this training, participants will be able to:
Grasp the key concepts and importance of AI trust, risk, and security management.
Identify and mitigate risks associated with AI systems.
Implement security best practices for AI.
Understand regulatory compliance and ethical considerations for AI.
Develop strategies for effective AI governance and management.
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.
Intelligent driving is a type of driving that uses AI and multi-sensor information fusion to provide guidance and feedback to drivers who want to drive safely and efficiently in complex and dynamic environments.This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level developers and architects who wish to learn the fundamentals of intelligent driving and how to apply them to real-world scenarios.By the end of this training, participants will be able to:
Explain the basic concepts and principles of AI and how it can be applied to driving.
Understand the architecture and components of intelligent driving systems.
Create and visualize a composite driving model from different design disciplines.
Communicate and annotate issues and feedback within the model.
Perform clash detection and resolution between driving scenarios.
Simulate and control driving schedules and costs.
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.
Artificial Intelligence (AI) is a branch of computer science that focuses on the development of intelligent machines capable of performing tasks that typically require human intelligence and it aims to simulate human-like cognitive processes.
This instructor-led, live training (online or onsite) is aimed at professionals who wish to learn and understand the concept of AI and how to use it effectively and responsibly.
By the end of this training, participants will be able to:
Learn the concept of Artificial Intelligence (AI).
Understand the limits and dangers of AI and use it responsibly.
Know how to effectively use AI in real-world scenarios.
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.
Bing AI is Microsoft's integration of artificial intelligence into its search engine, Bing. This course provides an introduction to Bing AI and how it leverages AI technologies to enhance search results and user experiences. Participants will gain insights into the various AI-powered features and functionalities available in Bing, including Bing AI Chatbot.
This instructor-led, live training (online or onsite) is aimed at digital marketers, content creators, and developers who wish to understand the impact of AI on search engines, explore the capabilities of Bing AI, and learn about chatbot technologies and their applications.
By the end of this training, participants will be able to:
Understand the principles and benefits of Bing AI.
Identify the AI-powered features within Bing and their applications.
Utilize Bing AI to enhance search results and user experiences.
Evaluate the potential of AI in search engine optimization (SEO) and content creation.
Explore chatbot technologies and their applications, including Bing AI Chatbot.
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.
IBM Cloud Pak for Data is a multi-cloud software platform for collecting, organizing and analyzing data for use in AI.
This instructor-led, live training (online or onsite) is aimed at data scientists who wish to use IBM Cloud Pak to prepare data for use in AI solutions.
By the end of this training, participants will be able to:
Install and configure Cloud Pak for Data.
Unify the collection, organization and analysis of data.
Integrate Cloud Pak for Data with a variety of services to solve common business problems.
Implement workflows for collaborating with team members on the development of an AI solution.
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.
AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. The course will use C# or Python as the programming language.
Audience Profile
Software engineers concerned with building, managing and deploying AI solutions that leverage Azure Cognitive Services, Azure Cognitive Search, and Microsoft Bot Framework. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and conversational AI solutions on Azure.
Kurs ten został stworzony dla menadżerów, architektów, analityków biznesowych i systemowych, menedżerów oprogramowania oraz wszystkich zainteresowanych przeglądem stosowania sztucznej inteligencji i prognozą dla jej rozwoju.
This course uses a practical approach to teaching OptaPlanner. It provides participants with the tools needed to perform the basic functions of this tool.
Intelligent Process Automation, or IPA, refers to the use of Artificial Intelligence (AI), robotics and integration with third-party services to extend the power of RPA.
This instructor-led, live training (online or onsite) is aimed at technical persons who wish to set up or extend an RPA system with more intelligent capabilities.
By the end of this training, participants will be able to:
Install and configure UiPath IPA.
Enable robots to manage other robots.
Apply computer vision to locate screen objects with accuracy.
Enable robots that can detect language patterns and carry out sentiment analysis on unstructured content.
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.
To learn more about UiPath IPA, please visit: https://www.UiPath.com/rpa/intelligent-process-automation
Software testing is the process of evaluating the validity of a software application's functionality. Integrating artificial intelligence into the software testing environment enables the process to be AI driven, speeding up authoring, execution, and maintenance of tests.
This instructor-led, live training (online or onsite) is aimed at software testers who wish to have an AI driven software testing environment.
By the end of this training, participants will be able to:
Automate unit test generation and parameterization with AI.
Apply machine learning learning in a real world use-case.
Automate the generation and maintenance of API tests with AI.
Use machine learning methods to self-heal the execution of Selenium tests.
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.
AI (Artificial Intelligence) is intelligence for machines to accomplish specific tasks by recognizing patterns in data. AI enables users to growth hack the success of digital marketing campaigns.
This instructor-led, live training (online or onsite) is aimed at marketers who wish to use AI to improve improve digital marketing strategies through valuable customer insights.
By the end of this training, participants will be able to:
Leverage AI software to improve the way brands connect to users.
Use chatbots to optimize the user-experience.
Increase productivity and revenue through the automation of tasks.
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.
Robotics is an area in artificial intelligence (AI) that deals with the programming and designing of intelligent and efficient machines.
This instructor-led, live training (online or onsite) is aimed at engineers who wish to program and create robots through basic AI methods.
By the end of this training, participants will be able to:
Implement filters (Kalman and particle) to enable the robot to locate moving objects in its environment.
Implement search algorithms and motion planning.
Implement PID controls to regulate a robot's movement within an environment.
Implement SLAM algorithms to enable a robot to map out an unknown environment.
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.
Artificial Intelligence (AI) is the simulation of human intelligence in machines that are programmed to think and act like humans. It covers a variety of technologies, such as machine learning and deep learning, and is used for various business and corporate applications to solve organizational challenges and needs.
This instructor-led, live training (online or onsite) is aimed at managers and business leaders who wish to learn about the fundamentals of artificial intelligence and manage AI projects for their organization.
By the end of this training, participants will be able to understand AI at a technical level and strategize using their organization’s data and resources to successfully manage AI projects.
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.
Robotics and Artificial Intelligence (AI) are powerful tools for the development of safety systems in nuclear facilities.
In this instructor-led, live training (online or onsite), participants will learn the different technologies, frameworks and techniques for programming different types of robots to be used in the field of nuclear technology and environmental systems.
The 4-week course is held 5 days a week. Each day is 4-hours long and consists of lectures, discussions, and hands-on robot development in a live lab environment. Participants will complete various real-world projects applicable to their work in order to practice their acquired knowledge.
The target hardware for this course will be simulated in 3D through simulation software. The code will then be loaded onto physical hardware (Arduino or other) for final deployment testing. The ROS (Robot Operating System) open-source framework, C++ and Python will be used for programming the robots.
By the end of this training, participants will be able to:
Understand the key concepts used in robotic technologies.
Understand and manage the interaction between software and hardware in a robotic system.
Understand and implement the software components that underpin robotics.
Build and operate a simulated mechanical robot that can see, sense, process, navigate, and interact with humans through voice.
Understand the necessary elements of artificial intelligence (machine learning, deep learning, etc.) applicable to building a smart robot.
Implement filters (Kalman and Particle) to enable the robot to locate moving objects in its environment.
Implement search algorithms and motion planning.
Implement PID controls to regulate a robot's movement within an environment.
Implement SLAM algorithms to enable a robot to map out an unknown environment.
Test and troubleshoot a robot in realistic scenarios.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
About the Hardware
Hardware kits will be confirmed by the instructor before the training. Kits will more-or-less contain the following components:
Arduino board
Motor controller
Distance sensor
Bluetooth slave
Prototyping board and cables
USB cable
Vehicle kit
Participants will need to provision their own hardware.
Course Customization Options
To customize any part of this course (programming language, robot model, microcontroller, etc.) please contact us to arrange.
Robotics and Artificial Intelligence (AI) are powerful tools for the development of safety systems in nuclear facilities.
In this instructor-led, live training (online or onsite), participants will learn the different technologies, frameworks and techniques for programming different types of robots to be used in the field of nuclear technology and environmental systems.
The 6-week course is held 5 days a week. Each day is 4-hours long and consists of lectures, discussions, and hands-on robot development in a live lab environment. Participants will complete various real-world projects applicable to their work in order to practice their acquired knowledge.
The target hardware for this course will be simulated in 3D through simulation software. The ROS (Robot Operating System) open-source framework, C++ and Python will be used for programming the robots.
By the end of this training, participants will be able to:
Understand the key concepts used in robotic technologies.
Understand and manage the interaction between software and hardware in a robotic system.
Understand and implement the software components that underpin robotics.
Build and operate a simulated mechanical robot that can see, sense, process, navigate, and interact with humans through voice.
Understand the necessary elements of artificial intelligence (machine learning, deep learning, etc.) applicable to building a smart robot.
Implement filters (Kalman and Particle) to enable the robot to locate moving objects in its environment.
Implement search algorithms and motion planning.
Implement PID controls to regulate a robot's movement within an environment.
Implement SLAM algorithms to enable a robot to map out an unknown environment.
Extend a robot's ability to perform complex tasks through Deep Learning.
Test and troubleshoot a robot in realistic scenarios.
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 customize any part of this course (programming language, robot model, etc.) please contact us to arrange.
This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them. The course is designed as a blended learning experience that combines instructor-led training with online materials on the Microsoft Learn platform (https://azure.com/learn). The hands-on exercises in the course are based on Learn modules, and students are encouraged to use the content on Learn as reference materials to reinforce what they learn in the class and to explore topics in more depth.
Szkolenie jest wprowadzeniem do wdrożenia sieci neuronowych w życiu codziennym wykorzystując oprogramowanie R-project.
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Opinie uczestników (25)
Trener pokazał, że ma dobrą wiedzę w temacie.
Marino - EQUS - The University of Queensland
Szkolenie - Machine Learning with Python – 2 Days
Przetłumaczone przez sztuczną inteligencję
przykłady i ćwiczenia
Kamil
Szkolenie - Introduction to Data Science and AI using Python
Interesująca wiedza
Gabriel - MINDEF
Szkolenie - Machine Learning with Python – 4 Days
Przetłumaczone przez sztuczną inteligencję
Wszystkie przedstawione informacje
Jose Victor - si
Szkolenie - Artificial Intelligence (AI) for Managers
Przetłumaczone przez sztuczną inteligencję
Świetny kontakt z uczestnikami, wiedza praktyczna co bardzo się ceni. Dostosowanie toku / tempa. Duuuży plus, mega pozytywny instruktor, aż szkoda że szkolenie trwało tylko 2 dni.
Marcin Mikielewicz - TECNOBIT SLU
Szkolenie - Introduction Deep Learning & Réseaux de neurones pour l’ingénieur
All the examples used and the lecturing style was on point even for a begginer i was able to understand and the training was so patient and always willing to go extra mile when in need of assistance.
Mathipa Chepape - Vodacom
Szkolenie - Big Data Business Intelligence for Telecom and Communication Service Providers
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Department of Jobs, Regions, and Precincts
Szkolenie - Artificial Neural Networks, Machine Learning, Deep Thinking
It felt like we were going through directly relevant information at a good pace (i.e. no filler material)
Maggie Webb - Department of Jobs, Regions, and Precincts
Szkolenie - Introduction to the use of neural networks
The way of transferring knowledge and the knowledge of the trainer.
Jakub Rękas - Bitcomp Sp. z o.o.
Szkolenie - Machine Learning on iOS
The training definitely backfilled some of the gaps in my knowledge left by reading the OptaPlanner userguide.
It gave me a good broad understanding of how to approach using OptaPlanner in our projects going forward.
Terry Strachan - Exel Computer Systems plc
Szkolenie - OptaPlanner in Practice
Tematyka DL nie jest mi obca, udało się poznac kilka optymalizacyjnych smaczków.
Marcin Staśko - LG Energy Solution Wrocław Sp. z o.o.
Szkolenie - Understanding Deep Neural Networks
That it was applying real company data.
Trainer had a very good approach by making trainees participate and compete
Jimena Esquivel - Zakład Usługowy Hakoman Andrzej Cybulski
Szkolenie - Applied AI from Scratch in Python
The enthusiasm to the topic. The examples he made an he explained it very well. Sympatic. A little to detailed for beginners. For managers, it could be more abstract in fewer days. But it was designed to fit and we had a good alignment in advance.
Benedikt Chiandetti - HDI Deutschland Bancassurance Kundenservice GmbH
Szkolenie - Machine Learning Concepts for Entrepreneurs and Managers
Convolution filter
Francesco Ferrara
Szkolenie - Introduction to Machine Learning
Ćwiczenia praktyczne.
Adam Borowski - NetWorkS! Sp. z o.o.
Szkolenie - AI Awareness for Telecom
Proste przykłady do teorii pozwalające na zobrazowanie zagadnienia
- EduBroker Sp. z o.o.
Szkolenie - Machine Learning for Banking (with Python)
The exercises.
Elena Velkova - CEED Bulgaria
Szkolenie - Predictive Modelling with R
Good detail on what R is used for and how to start using it right away
Hoss Shenassa - Trimac Management Services LP
Szkolenie - Introduction to R with Time Series Analysis
The content, as I found it very interesting and think it would help me in my final year at University.
Krishan - NBrown Group
Szkolenie - From Data to Decision with Big Data and Predictive Analytics
dużo ćwiczeń, które bezpośrednio mogę wykorzystać w mojej pracy
Alior Bank S.A.
Szkolenie - Sieci Neuronowe w R
This is one of the best hands-on with exercises programming courses I have ever taken.
Laura Kahn
Szkolenie - Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
Trener bardzo zrozumiale wytłumaczył trudne i zaawansowane tematy.
Leszek K
Szkolenie - Artificial Intelligence Overview
I liked the opportunities to ask questions and get more in depth explanations of the theory.
Sharon Ruane
Szkolenie - Neural Networks Fundamentals using TensorFlow as Example
The trainer was so knowledgeable and included areas I was interested in.
Mohamed Salama
Szkolenie - Data Mining & Machine Learning with R
I did like the exercises.
Office for National Statistics
Szkolenie - Natural Language Processing with Python
