Artificial Intelligence (AI) for Managers - Plan Szkolenia

LangChain is an open-source framework designed to facilitate the development of applications using large language models (LLMs).

This instructor-led, live training (online or onsite) is aimed at intermediate-level developers and software engineers who wish to build AI-powered applications using the LangChain framework.

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

• Understand the fundamentals of LangChain and its components.
• Integrate LangChain with large language models (LLMs) like GPT-4.
• Build modular AI applications using LangChain.
• Troubleshoot common issues in LangChain 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.

LangChain is an open-source framework that simplifies the integration of large language models (LLMs) into applications.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level developers and software engineers who wish to learn the core concepts and architecture of LangChain and gain the practical skills for building AI-powered applications.

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

• Grasp the fundamental principles of LangChain.
• Set up and configure the LangChain environment.
• Understand the architecture and how LangChain interacts with large language models (LLMs).
• Develop simple applications using LangChain.

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.

Szkolenie na żywo prowadzone przez instruktora (na miejscu lub zdalnie) jest przeznaczone dla programistów i specjalistów IT na wszystkich poziomach umiejętności, którzy chcą zautomatyzować zadania i procesy za pomocą sztucznej inteligencji bez pisania obszernego kodu.

Pod koniec tego szkolenia uczestnicy będą mogli

• Projektować i wdrażać złożone przepływy pracy przy użyciu wizualnego interfejsu programowania n8n.
• Zintegrować możliwości AI z przepływami pracy przy użyciu LangChain.
• Tworzyć niestandardowe chatboty i wirtualnych asystentów dla różnych przypadków użycia.
• Przeprowadzać zaawansowaną analizę i przetwarzanie danych za pomocą agentów AI.

Small Language Models (SLMs) are a cutting-edge subset of AI that enables efficient language processing on devices with limited computational resources.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level data scientists and developers who wish to implement and leverage Small Language Models in various applications.

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

• Understand the architecture and functionality of Small Language Models.
• Implement SLMs for tasks such as text generation and sentiment analysis.
• Optimize and fine-tune SLMs for specific use cases.
• Deploy SLMs in resource-constrained environments.
• Evaluate and interpret the performance of SLMs 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.

Small Language Models (SLMs) are a cutting-edge subset of AI that enables efficient language processing on devices with limited computational resources.

This instructor-led, live training (online or onsite) is aimed at intermediate-level data scientists and machine learning engineers who wish to create and apply small language models tailored for specific domains such as legal, medical, and technical fields.

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

• Understand the importance and application of domain-specific language models.
• Curate and preprocess specialized datasets for model training.
• Train and fine-tune language models for domain-specific applications.
• Evaluate and benchmark models using domain-relevant metrics.
• Deploy domain-specific language models 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.

Small Language Models (SLMs) are compact yet powerful tools for enabling sophisticated human-AI interactions in various applications, including conversational AI and customer service bots.

This instructor-led, live training (online or onsite) is aimed at intermediate-level data scientists, machine learning and AI researchers who wish to create engaging and efficient AI-powered conversational experiences with small language models.

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

• Understand the fundamentals of conversational AI and the role of SLMs.
• Design and implement user-centric AI interactions.
• Develop and train SLMs for interactive applications.
• Evaluate and improve the effectiveness of human-AI communication using appropriate metrics.
• Deploy scalable and ethical AI-driven conversational interfaces 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.

Small Language Models (SLMs) are efficient alternatives to larger models, offering comparable performance with significantly reduced computational and energy requirements.

This instructor-led, live training (online or onsite) is aimed at advanced-level machine learning engineers and AI researchers who wish to develop energy-efficient AI solutions with small language models that are both powerful and environmentally friendly.

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

• Understand the impact of AI on energy consumption and the environment.
• Apply model compression and optimization techniques to reduce the size and energy usage of AI models.
• Utilize energy-efficient hardware and software frameworks for AI deployment.
• Implement best practices for sustainable AI development.
• Advocate for and contribute to sustainable practices in the AI industry.

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.

Small Language Models (SLMs) are efficient and versatile AI tools that can be implemented on a variety of devices, from smartphones to IoT devices, enabling intelligent on-device applications.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT professionals who wish to deploy small language models directly onto devices with limited processing capabilities, opening up possibilities for innovative applications in various sectors.

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

• Understand the challenges and solutions for implementing AI on compact hardware.
• Optimize and compress AI models for efficient on-device deployment.
• Utilize modern AI frameworks and tools for on-device model implementation.
• Design and develop real-time AI applications for mobile and IoT devices.
• Evaluate and ensure the security and privacy of on-device AI systems.

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 prowadzone przez instruktora szkolenie na żywo w Polsce (na miejscu lub zdalnie) jest przeznaczone dla średnio zaawansowanych technologów edukacyjnych, projektantów instrukcji i programistów AI w edukacji, którzy chcą zintegrować Small Language Models (SLMs) z platformami edukacyjnymi w celu usprawnienia procesów nauczania i uczenia się.

Pod koniec tego szkolenia uczestnicy będą mogli

• Zrozumieć rolę SLM w technologii edukacyjnej.
• Projektować doświadczenia edukacyjne oparte na sztucznej inteligencji przy użyciu SLM.
• Wdrażać SLM w różnych środowiskach edukacyjnych.
• Ocenić skuteczność SLM w efektach uczenia się.

To prowadzone przez instruktora szkolenie na żywo w Polsce (na miejscu lub zdalnie) jest przeznaczone dla średniozaawansowanych urbanistów, administratorów miast i twórców rozwiązań inteligentnego miasta, którzy chcą wdrożyć Small Language Models (SLMs) w projektach inteligentnego miasta w celu poprawy życia w mieście.

Pod koniec tego szkolenia uczestnicy będą w stanie

• Zrozumieć zastosowanie SLM w inteligentnych miastach.
• Zintegrować SLM z zestawami danych miejskich w celu usprawnienia procesu decyzyjnego.
• Opracować strategie wdrażania SLM w miejskich systemach zarządzania.
• Ocenić wpływ SLM na planowanie urbanistyczne i inteligentne rozwiązania miejskie.

Szkolenie na żywo prowadzone przez instruktora (na miejscu lub zdalnie) jest przeznaczone dla początkujących i średnio zaawansowanych programistów, którzy chcą korzystać z dużych modeli językowych do różnych zadań związanych z językiem naturalnym.

Po zakończeniu tego szkolenia uczestnicy będą w stanie

Skonfigurowanie środowiska programistycznego zawierającego popularny program LLM. Utwórz podstawowy mechanizm LLM i dostosuj go do niestandardowego zestawu danych. Wykorzystanie LLM do różnych zadań związanych z językiem naturalnym, takich jak podsumowywanie tekstu, odpowiadanie na pytania, generowanie tekstu i inne. Debugowanie i ocena LLM przy użyciu narzędzi takich jak TensorBoard, PyTorch Lightning i Hugging Face Datasets.

To prowadzone przez instruktora szkolenie na żywo (online lub na miejscu) jest przeznaczone dla średnio zaawansowanych programistów, którzy chcą dowiedzieć się, jak korzystać z generatywnej sztucznej inteligencji z LLM do różnych zadań i dziedzin.

Po zakończeniu tego szkolenia uczestnicy będą w stanie

Wyjaśnij, czym jest generatywna sztuczna inteligencja i jak działa. Opisać architekturę transformatora, która zasila mechanizmy LLM. Wykorzystanie empirycznych praw skalowania do optymalizacji mechanizmów LLM pod kątem różnych zadań i ograniczeń. Zastosuj najnowocześniejsze narzędzia i metody do trenowania, dostrajania i wdrażania mechanizmów LLM. Omówienie szans i zagrożeń związanych z generatywną sztuczną inteligencją dla społeczeństwa i biznesu.

Large language models (LLMs) are AI models that can process and generate large amounts of natural language data, such as text, speech, and audio. LLMs can learn the patterns and structure of their input training data and then generate new data that has similar characteristics. LLMs can also perform various natural language processing (NLP) tasks, such as natural language understanding (NLU), natural language inference (NLI), knowledge graph construction and completion, commonsense reasoning, dialogue generation and management, and multimodal generation and understanding.

This instructor-led, live training (online or onsite) is aimed at intermediate-level data scientists, AI developers, and AI enthusiasts who wish to use LLMs to perform various NLP tasks and create novel and diverse content for different purposes.

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

• Establish a development environment with LLMs and essential tools.
• Expertly perform NLU and NLI tasks with LLMs.
• Extract, infer, and utilize knowledge graphs effectively.
• Generate and manage dialogues using LLMs for conversational applications.
• Evaluate content quality and diversity generated by LLMs and generative AI.
• Apply ethical principles, ensuring fairness and responsible use of LLMs.

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.

Google Gemini AI is a cutting-edge large language model that offers advanced AI capabilities, such as natural language understanding, text generation, and semantic search, enabling developers to create more intuitive and responsive AI-driven applications.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to integrate AI functionalities into their applications using Google Gemini AI.

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

• Understand the fundamentals of large language models.
• Set up and use Google Gemini AI for various AI tasks.
• Implement text-to-text and image-to-text transformations.
• Build basic AI-driven applications.
• Explore advanced features and customization options in Google Gemini 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.

Google Gemini AI is a versatile tool designed to revolutionize customer service interactions by leveraging advanced machine learning algorithms. It enhances real-time communication across various platforms such as live chat, email support, and social media engagement. By automating routine tasks and providing actionable insights from customer data, Google Gemini AI significantly improves the overall customer experience and operational efficiency.

This instructor-led, live training (online or onsite) is aimed at intermediate-level customer service professionals who wish to implement Google Gemini AI in their customer service operations.

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

• Understand the impact of AI on customer service.
• Set up Google Gemini AI to automate and personalize customer interactions.
• Utilize text-to-text and image-to-text transformations to improve service efficiency.
• Develop AI-driven strategies for real-time customer feedback analysis.
• Explore advanced features to create a seamless customer service experience.

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.