Natural Language Processing (NLP) Training in Patras

Ollama is a lightweight platform designed for running large language models locally.

This instructor-led, live training (available online or onsite) targets intermediate-level finance practitioners and IT personnel aiming to implement, customize, and operationalize Ollama-based AI solutions within financial environments.

Upon completing this training, participants will acquire the skills necessary to:

• Deploy and configure Ollama for secure use in financial operations.
• Integrate local LLMs into analytical and reporting workflows.
• Adapt models to finance-specific terminology and tasks.
• Apply security, privacy, and compliance best practices.

Format of the Course

• Interactive lecture and discussion.
• Hands-on financial data exercises.
• Live-lab implementation of finance-focused scenarios.

Course Customization Options

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

Ollama is a lightweight platform for running large language models locally.

This instructor-led, live training (online or onsite) is aimed at intermediate-level healthcare practitioners and IT teams who wish to deploy, customize, and operationalize Ollama-based AI solutions within clinical and administrative environments.

Upon completing this training, participants will be able to:

• Install and configure Ollama for secure use in healthcare settings.
• Integrate local LLMs into clinical workflows and administrative processes.
• Customize models for healthcare-specific terminology and tasks.
• Apply best practices for privacy, security, and regulatory compliance.

Format of the Course

• Interactive lecture and discussion.
• Hands-on demonstrations and guided exercises.
• Practical implementation in a sandboxed healthcare simulation environment.

Course Customization Options

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

Ollama is a platform designed for running large language and multimodal models locally, supporting governance and responsible AI practices.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to implement fairness, transparency, and accountability in Ollama-powered applications.

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

• Apply responsible AI principles in Ollama deployments.
• Implement content filtering and bias mitigation strategies.
• Design governance workflows for AI alignment and auditability.
• Establish monitoring and reporting frameworks for compliance.

Format of the Course

• Interactive lecture and discussion.
• Hands-on governance workflow design labs.
• Case studies and compliance-focused exercises.

Course Customization Options

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

Mistral AI offers a robust suite of open-source and enterprise-grade AI models designed for language processing, multimodal applications, and agentic systems.

This instructor-led live training, available either online or at your location, is tailored for intermediate to advanced professionals aiming to build, deploy, and oversee AI agents utilizing Mistral’s Medium 3, Le Chat Enterprise, and Devstral models.

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

• Comprehending the architecture and functionalities of Mistral Medium 3, Le Chat Enterprise, and Devstral.
• Designing and implementing AI agents that leverage Mistral models for both enterprise and developer scenarios.
• Integrating coding systems, connectors, and enterprise data into agent workflows.
• Optimizing the performance, cost-efficiency, and compliance of Mistral-powered agents.

Course Format

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

Customization Options

• For a customized training version of this course, please get in touch with us to arrange it.

Ollama enables the local execution of large language and multimodal models while facilitating secure deployment strategies.

This instructor-led live training, available online or on-site, targets intermediate professionals seeking to deploy Ollama with robust data privacy and regulatory compliance measures.

Upon completion, participants will be capable of:

• Securely deploying Ollama within containerized and on-premises environments.
• Utilizing differential privacy techniques to protect sensitive data.
• Establishing secure logging, monitoring, and auditing protocols.
• Enforcing data access controls that align with regulatory requirements.

Course Format

• Interactive lectures and discussions.
• Practical labs focused on secure deployment patterns.
• Case studies and hands-on exercises centered on compliance.

Customization Options

• For tailored training arrangements, please contact us.

Claude AI is an advanced language model engineered to facilitate complex analytical, strategic, and organizational challenges.

This instructor-led live training, available either online or onsite, is tailored for project management and planning professionals at the beginner level who aim to utilize Claude AI to enhance project design, documentation, communication, and long-term strategic planning.

Upon successful completion of this training, participants will be equipped to:

• Generate project documentation, including charters, briefs, and scope statements, leveraging Claude AI.
• Analyze risks, constraints, and dependencies utilizing AI-driven reasoning.
• Develop stakeholder communications and reporting outputs customized for diverse audiences.
• Utilize Claude AI to facilitate sprint planning, prioritization, and roadmap refinement.

Course Format

• A combination of instructor-led explanations and guided demonstrations.
• Practical exercises based on real-world project management scenarios.
• Structured activities applying Claude AI in a live working environment.

Customization Options

• Custom scenarios, organization-specific templates, or industry-focused workflows can be incorporated upon request.

Mistral AI is an open AI platform that enables teams to build and integrate conversational assistants into enterprise and customer-facing workflows.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level product managers, full-stack developers, and integration engineers who wish to design, integrate, and productize conversational assistants using Mistral connectors and integrations.

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

• Integrate Mistral conversational models with enterprise and SaaS connectors.
• Implement retrieval-augmented generation (RAG) for grounded responses.
• Design UX patterns for internal and external chat assistants.
• Deploy assistants into product workflows for real-world use cases.

Format of the Course

• Interactive lecture and discussion.
• Hands-on integration exercises.
• Live-lab development of conversational assistants.

Course Customization Options

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

Ollama is a platform designed to run large language models and multimodal applications locally.

This instructor-led live training, available either online or on-site, is tailored for intermediate practitioners looking to master prompt engineering techniques to enhance the quality of Ollama outputs.

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

• Create effective prompts for a variety of use cases.
• Apply strategies such as priming and chain-of-thought structuring.
• Implement prompt templates and manage context effectively.
• Develop multi-stage prompting pipelines for complex workflows.

Course Format

• Interactive lectures and discussions.
• Practical exercises focused on prompt design.
• Hands-on implementation within a live lab environment.

Customization Options

• To arrange a customized training session, please contact us.

Claude AI is a generative AI platform engineered to facilitate complex reasoning, content creation, knowledge retrieval, and the automation of workflows.

This instructor-led live training session, available online or on-site, targets beginner-level professionals looking to implement Claude AI to enhance their customer support and service operations.

Upon successful completion of this programme, participants will be equipped to:

• Leverage Claude to expedite the triage and classification of support queries.
• Generate customer responses and summaries that maintain consistent tone and quality.
• Automate the drafting of tickets and streamline knowledge retrieval procedures.
• Seamlessly integrate Claude into established customer support workflows.

Course Format

• Structured lectures complemented by real-world support scenarios.
• Practical exercises grounded in enterprise service case studies.
• Interactive application of Claude within a simulated support environment.

Customization Options

• For organizations seeking to tailor this course to their specific support workflows, please contact us to discuss customization requirements.

LangGraph serves as a framework designed to construct stateful, multi-agent LLM applications through composable graphs that maintain persistent state and offer precise control over execution processes.

This instructor-led live training, available either online or on-site, targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based legal solutions equipped with robust compliance, traceability, and governance controls.

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

• Designing legal-specific LangGraph workflows that ensure auditability and compliance.
• Integrating legal ontologies and document standards into graph state and processing mechanisms.
• Implementing guardrails, human-in-the-loop approvals, and traceable decision pathways.
• Deploying, monitoring, and maintaining LangGraph services in production environments with effective observability and cost management.

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live laboratory environment.

Course Customization Options

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

Mistral AI offers an open and enterprise-ready AI platform equipped with features designed to facilitate secure, compliant, and responsible AI deployment.

This instructor-led training, available both online and onsite, is tailored for intermediate-level compliance leads, security architects, and legal/operations stakeholders who aim to implement responsible AI practices using Mistral by leveraging privacy, data residency, and enterprise control mechanisms.

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

• Implement privacy-preserving techniques within Mistral deployments.
• Apply data residency strategies to satisfy regulatory requirements.
• Establish enterprise-grade controls, including RBAC, SSO, and audit logs.
• Evaluate vendor and deployment options to ensure compliance alignment.

Format of the Course

• Interactive lecture and discussion.
• Compliance-focused case studies and exercises.
• Hands-on implementation of enterprise AI controls.

Course Customization Options

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

Ollama is a platform designed for running large language and multimodal models locally and at scale.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced engineers looking to scale Ollama deployments in multi-user, high-throughput, and cost-effective environments.

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

• Configure Ollama for multi-user and distributed workloads.
• Optimize GPU and CPU resource allocation.
• Implement strategies for autoscaling, batching, and reducing latency.
• Monitor and optimize infrastructure for enhanced performance and cost efficiency.

Course Format

• Interactive lectures and discussions.
• Hands-on labs for deployment and scaling.
• Practical optimization exercises in live environments.

Course Customization Options

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

The CANN SDK (Compute Architecture for Neural Networks) offers robust deployment and optimization solutions 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 professionals looking to develop, deploy, and optimize vision and language models using the CANN SDK for production environments.

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

• Deploy and optimize CV and NLP models utilizing CANN and AscendCL.
• Leverage CANN tools to convert models and seamlessly 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 scenarios.

Course Format

• Interactive lectures combined with live demonstrations.
• Practical hands-on labs focusing on model deployment and performance profiling.
• Live pipeline design utilizing real-world CV and NLP use cases.

Customization Options

• To request a customized training session for this course, please get in touch with us to arrange details.

Claude AI is a sophisticated language and reasoning engine designed to support structured data operations, analytical workflows, and enhanced business intelligence capabilities.

This instructor-led training session, available either online or at your facility, is tailored for professionals at a beginner to intermediate level who aim to leverage Claude to expedite data analysis, derive actionable insights, and optimize BI processes.

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

• Employ Claude to conduct ad-hoc exploratory data analysis.
• Produce SQL queries, summaries, and data transformations using natural language prompts.
• Utilize Claude to more efficiently design dashboards, KPIs, and analytical views.
• Interpret business data with greater accuracy through structured, AI-assisted reasoning.

Course Format

• Instructor-led demonstrations accompanied by guided discussions.
• Practical exercises utilizing real-world business datasets.
• Practical application of Claude within BI-centric scenarios.

Customization Options

• If you require the course to be aligned with your internal BI tools or workflows, please contact us to arrange a customized version of this training.

LangGraph serves as a framework for constructing stateful, multi-actor LLM applications through composable graphs, enabling persistent state management and precise execution control.

This instructor-led training, available either online or onsite, targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based financial solutions with appropriate governance, observability, and compliance standards.

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

• Designing finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrating financial data standards and ontologies into graph states and tooling.
• Implementing reliability, safety measures, and human-in-the-loop controls for critical processes.
• Deploying, monitoring, and optimizing LangGraph systems for performance, cost efficiency, and service level agreements (SLAs).

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live laboratory environment.

Customization Options

• To request a tailored version of this course, please contact us to make arrangements.

Ollama serves as a platform that allows users to run and fine-tune large language and multimodal models on their own hardware.

This guided, live training session (available online or in-person) is designed for experienced ML engineers, AI researchers, and product developers who want to construct and deploy multimodal applications utilizing Ollama.

Upon completing this training, participants will be capable of:

• Configuring and executing multimodal models via Ollama.
• Combining text, image, and audio inputs for practical applications.
• Creating document analysis and visual question-answering systems.
• Developing multimodal agents that can reason across different data types.

Course Format

• Interactive lectures and discussions.
• Practical exercises using real-world multimodal datasets.
• Live laboratory sessions focused on implementing multimodal pipelines with Ollama.

Customization Options

• To arrange a tailored training session for this course, please get in touch with us.

Mistral models are open-source AI technologies that now extend into multimodal workflows, supporting both language and vision tasks for enterprise and research applications.

This instructor-led, live training (online or onsite) is aimed at intermediate-level ML researchers, applied engineers, and product teams who wish to build multimodal applications with Mistral models, including OCR and document understanding pipelines.

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

• Set up and configure Mistral models for multimodal tasks.
• Implement OCR workflows and integrate them with NLP pipelines.
• Design document understanding applications for enterprise use cases.
• Develop vision-text search and assistive UI functionalities.

Format of the Course

• Interactive lecture and discussion.
• Hands-on coding exercises.
• Live-lab implementation of multimodal pipelines.

Course Customization Options

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

This instructor-led live training in Patras (online or on-site) is tailored for intermediate data scientists and developers seeking to apply NLP techniques using Python in Google Colab.

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

• Comprehend the core concepts of natural language processing.
• Preprocess and clean text data for NLP applications.
• Perform sentiment analysis using the NLTK and SpaCy libraries.
• Manage text data using Google Colab to support scalable and collaborative development.

Advanced Ollama Model Debugging and Evaluation is an intensive course designed to help participants diagnose, test, and measure the behavior of models within local or private Ollama deployments.

This instructor-led live training, available online or on-site, is tailored for advanced AI engineers, ML Ops professionals, and QA specialists who aim to ensure the reliability, accuracy, and operational readiness of Ollama-based models in production environments.

Upon completing this training, participants will be able to:

• Systematically debug Ollama-hosted models and reliably reproduce failure scenarios.
• Design and implement robust evaluation pipelines utilizing both quantitative and qualitative metrics.
• Implement observability solutions (logs, traces, metrics) to monitor model health and detect drift.
• Automate testing, validation, and regression checks integrated into CI/CD pipelines.

Course Format

• Interactive lectures and discussions.
• Hands-on labs and debugging exercises focused on Ollama deployments.
• Case studies, group troubleshooting sessions, and automation workshops.

Customization Options

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

This instructor-led, live training in Patras (online or onsite) is aimed at intermediate-level researchers, analysts, and knowledge workers who want to leverage Claude AI for processing large amounts of data, synthesizing information, and automating research tasks.

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

• Use Claude AI for literature reviews and research synthesis.
• Summarize reports, research papers, and long-form documents.
• Extract key insights and trends from structured and unstructured data.
• Integrate Claude AI into research and knowledge management workflows.

Devstral and Mistral are open-source AI technologies designed for flexible deployment, fine-tuning, and scalable integration.

This instructor-led, live training (available online or onsite) targets intermediate to advanced ML engineers, platform teams, and research engineers who wish to self-host, fine-tune, and govern Mistral and Devstral models in production environments.

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

• Set up and configure self-hosted environments for Mistral and Devstral models.
• Apply fine-tuning techniques to achieve domain-specific performance.
• Implement versioning, monitoring, and lifecycle governance.
• Ensure security, compliance, and responsible usage of open-source models.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises focused on self-hosting and fine-tuning.
• Live-lab implementation of governance and monitoring pipelines.

Course Customization Options

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

LangGraph facilitates stateful, multi-actor workflows driven by LLMs, offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are essential for ensuring compliance, enhancing interoperability, and developing decision-support systems that integrate seamlessly with medical workflows.

This instructor-led live training, available both online and onsite, targets intermediate to advanced-level professionals aiming to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.

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

• Design healthcare-specific LangGraph workflows with a focus on compliance and auditability.
• Integrate LangGraph applications with medical ontologies and standards such as FHIR, SNOMED CT, and ICD.
• Apply best practices for reliability, traceability, and explainability in sensitive environments.
• Deploy, monitor, and validate LangGraph applications in healthcare production settings.

Format of the Course

• Interactive lecture and discussion.
• Hands-on exercises with real-world case studies.
• Implementation practice in a live-lab environment.

Course Customization Options

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

LangGraph serves as a framework designed for constructing stateful, multi-agent LLM applications through composable graphs, featuring persistent state and precise control over execution flows.

This instructor-led live training, available online or onsite, targets advanced AI platform engineers, AI-focused DevOps professionals, and ML architects who aim to optimize, debug, monitor, and manage production-grade LangGraph systems.

Upon completing this training, participants will be capable of:

• Designing and optimizing complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
• Ensuring reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debugging and tracing graph executions, inspecting states, and systematically reproducing production issues.
• Instrumenting graphs with logs, metrics, and traces, deploying them to production, and monitoring SLAs and costs.

Course Format

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

Customization Options

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

This instructor-led, live training in Patras (online or onsite) targets beginner to intermediate content creators, writers, and marketers who wish to leverage Claude AI for content generation, editing, and summarization to enhance blogs, reports, and marketing materials.

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

• Use Claude AI for content brainstorming and idea expansion.
• Enhance writing with AI-assisted editing and proofreading.
• Generate summaries for long-form content and reports.
• Automate marketing copy creation for different platforms.

This instructor-led, live training in Patras (online or onsite) is designed for advanced professionals seeking to fine-tune and customize AI models on Ollama for improved performance and domain-specific applications.

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

• Establish an efficient environment for fine-tuning AI models on Ollama.
• Prepare datasets suitable for supervised fine-tuning and reinforcement learning.
• Optimize AI models to enhance performance, accuracy, and efficiency.
• Deploy customized models within production environments.
• Assess model improvements and guarantee robustness.

Mistral is a family of high-performance large language models, specifically engineered for cost-effective, large-scale production deployment.

This instructor-led live training, available online or onsite, is designed for advanced infrastructure engineers, cloud architects, and MLOps leaders who aim to design, deploy, and optimize Mistral-based architectures to achieve maximum throughput while minimizing costs.

Upon completing this training, participants will be capable of:

• Implementing scalable deployment patterns for Mistral Medium 3.
• Applying batching, quantization, and efficient serving strategies.
• Optimizing inference costs without compromising performance.
• Designing production-ready serving topologies for enterprise workloads.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation within a live laboratory environment.

Customization Options

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

This instructor-led, live training in Patras (online or onsite) is aimed at advanced-level professionals who wish to implement secure and efficient AI-driven workflows using Ollama.

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

• Deploy and configure Ollama for private AI processing.
• Integrate AI models into secure enterprise workflows.
• Optimise AI performance while maintaining data privacy.
• Automate business processes with on-premise AI capabilities.
• Ensure compliance with enterprise security and governance policies.

This instructor-led, live training in Patras (online or onsite) is designed for intermediate-level software developers and AI engineers seeking to integrate Claude AI into their apps, build AI-driven chatbots, and enhance software functionality with AI automation.

Upon completion, participants will be able to:

• Utilize the Claude AI API to embed AI features into applications.
• Create AI-driven chatbots and virtual assistants.
• Boost applications with AI automation and NLP.
• Tune and optimize Claude AI models for various scenarios.

LangGraph is a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving LLMs and tools, making it ideal for automating and personalizing content pipelines.

This instructor-led live training (available online or onsite) is tailored for intermediate-level marketers, content strategists, and automation developers aiming to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

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

• Designing graph-structured content and email workflows that incorporate conditional logic.
• Integrating LLMs, APIs, and data sources to enable automated personalization.
• Managing state, memory, and context across multi-step campaigns.
• Evaluating, monitoring, and optimizing workflow performance and delivery outcomes.

Course Format

• Interactive lectures and group discussions.
• Hands-on labs focused on implementing email workflows and content pipelines.
• Scenario-based exercises covering personalization, segmentation, and branching logic.

Course Customization Options

• For requests regarding customized training for this course, please contact us to arrange details.

Le Chat Enterprise offers a private ChatOps solution that delivers secure, customizable, and governed conversational AI capabilities for organizations, including support for RBAC, SSO, connectors, and enterprise app integrations.

This instructor-led, live training (online or onsite) targets intermediate-level product managers, IT leads, solution engineers, and security/compliance teams who want to deploy, configure, and govern Le Chat Enterprise in enterprise environments.

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

• Set up and configure Le Chat Enterprise for secure deployments.
• Enable RBAC, SSO, and compliance-driven controls.
• Integrate Le Chat with enterprise applications and data stores.
• Design and implement governance and admin playbooks for ChatOps.

Format of the Course

• Interactive lecture and discussion.
• Many 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.

Devstral is an open-source framework designed for building and running coding agents that can interact with codebases, developer tools, and APIs to enhance engineering productivity.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level ML engineers, developer-tooling teams, and SREs who wish to design, implement, and optimize coding agents using Devstral.

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

• Set up and configure Devstral for coding agent development.
• Design agentic workflows for codebase exploration and modification.
• Integrate coding agents with developer tools and APIs.
• Implement best practices for secure and efficient agent deployment.

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 Patras (online or onsite) targets beginner-level professionals who wish to integrate Claude AI into their daily workflows to improve efficiency and automation.

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

• Use Claude AI for automating repetitive tasks and streamlining workflows.
• Enhance personal and team productivity using AI-powered automation.
• Integrate Claude AI with existing business tools and platforms.
• Optimize AI-driven decision-making and task management.

This instructor-led, live training in Patras (online or onsite) is aimed at intermediate-level professionals who wish to deploy, optimise, and integrate LLMs using Ollama.

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

• Set up and deploy LLMs using Ollama.
• Optimise AI models for performance and efficiency.
• Leverage GPU acceleration for improved inference speeds.
• Integrate Ollama into workflows and applications.
• Monitor and maintain AI model performance over time.

LangGraph serves as a framework designed for constructing graph-based LLM workflows that enable branching, tool utilization, memory management, and controlled execution.

This instructor-led, live training session, available both online and onsite, targets intermediate-level engineers and product teams aiming to merge LangGraph’s graph logic with LLM agent loops to create dynamic, context-aware applications such as customer support assistants, decision trees, and information retrieval systems.

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

• Designing graph-based workflows that effectively coordinate LLM agents, tools, and memory.
• Implementing conditional routing, retries, and fallback mechanisms to ensure robust execution.
• Integrating retrieval processes, APIs, and structured outputs into agent loops.
• Evaluating, monitoring, and securing agent behavior to enhance reliability and safety.

Course Format

• Interactive lectures accompanied by facilitated discussions.
• Guided laboratory exercises and code walkthroughs within a sandbox environment.
• Scenario-based design exercises and peer reviews.

Customization Options for the Course

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

This instructor-led, live training in Patras (online or onsite) is designed for intermediate-level data scientists, AI developers, and AI enthusiasts who aim to leverage LLMs for various NLP tasks and to create novel, diverse content for specific applications.

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

• Set up a development environment equipped with LLMs and essential tools.
• Expertly execute NLU and NLI tasks using LLMs.
• Effectively extract, infer, and utilize knowledge graphs.
• Generate and manage dialogues using LLMs for conversational applications.
• Evaluate the quality and diversity of content generated by LLMs and generative AI.
• Apply ethical principles to ensure fairness and responsible use of LLMs.

This instructor-led, live training in Patras (online or onsite) is aimed at intermediate-level professionals who wish to enhance their NLP projects through the effective fine-tuning of pre-trained language models.

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

• Understand the fundamentals of fine-tuning for NLP tasks.
• Fine-tune pre-trained models such as GPT, BERT, and T5 for specific NLP applications.
• Optimize hyperparameters for improved model performance.
• Evaluate and deploy fine-tuned models in real-world scenarios.

This instructor-led, live training (online or in-person) is aimed at data scientists, machine learning engineers, NLP researchers, and AI enthusiasts who wish to understand the inner workings of GPT models, explore the capabilities of GPT-3 and GPT-4, and learn how to leverage these models for their NLP tasks.

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

• Understand the key concepts and principles behind Generative Pre-trained Transformers.
• Comprehend the architecture and training process of GPT models.
• Utilize GPT-3 for tasks such as text generation, completion, and translation.
• Explore the latest advancements in GPT-4 and its potential applications.
• Apply GPT models to their own NLP projects and tasks.

LangGraph serves as a framework designed for constructing graph-structured Large Language Model (LLM) applications that facilitate planning, branching, tool integration, memory management, and controlled execution.

This instructor-led live training, available either online or onsite, is tailored for beginner-level developers, prompt engineers, and data practitioners eager to design and implement reliable, multi-step LLM workflows using LangGraph.

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

• Articulate core LangGraph concepts—such as nodes, edges, and state—and determine appropriate use cases.
• Develop prompt chains that support branching, tool invocation, and memory retention.
• Incorporate retrieval mechanisms and external APIs into graph-based workflows.
• Test, debug, and evaluate LangGraph applications to ensure reliability and safety.

Course Format

• Interactive lectures paired with facilitated discussions.
• Guided laboratory sessions and code walkthroughs conducted within a sandbox environment.
• Scenario-based exercises focused on design, testing, and evaluation.

Customization Options

• To request tailored training for this course, please contact us to make arrangements.

Mistral Medium 3 is a high-performance, multimodal large language model engineered for robust, production-ready deployment within enterprise settings.

This instructor-led training session, available either online or onsite, targets intermediate to advanced AI/ML engineers, platform architects, and MLOps specialists looking to deploy, optimize, and secure Mistral Medium 3 for business applications.

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

• Deploy Mistral Medium 3 via API or by self-hosting.
• Enhance inference performance while managing costs.
• Develop multimodal applications using Mistral Medium 3.
• Apply security and compliance standards suitable for enterprise environments.

Course Format

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

Customization Options

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

This instructor-led live training in Patras (offered online or onsite) is targeted at beginner-level professionals who wish to install, configure, and utilize Ollama for operating AI models on their local machines.

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

• Comprehend the fundamentals of Ollama and its operational capabilities.
• Establish Ollama for executing local AI models.
• Deploy and interact with LLMs using Ollama.
• Optimize performance and resource allocation for AI workloads.
• Explore use cases for local AI deployment across various industries.

Unstructured data is estimated to represent over 90% of all existing data, with a significant portion appearing as text. Sources such as blog posts, tweets, social media platforms, and other digital publications continuously contribute to this expanding volume of information.

This instructor-led, live training focuses on extracting valuable insights and meaning from such data. By leveraging the R programming language alongside Natural Language Processing (NLP) libraries, the course integrates concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically decipher the meaning behind textual data. Data samples can be provided in various languages depending on customer requirements.

Upon completion of this training, participants will be capable of preparing datasets (both large and small) from diverse sources and applying appropriate algorithms to analyze and report on their significance.

Format of the Course

• A blend of lectures and discussions, emphasizing extensive hands-on practice, with occasional assessments to gauge understanding.

Designed for managers, solutions architects, innovation specialists, CTOs, software architects, and anyone eager to understand applied artificial intelligence and its near-term evolutionary trajectory.

Artificial Intelligence (AI) encompasses a suite of technologies designed to create intelligent systems that interpret data and contextual activities to generate "intelligent decisions." For telecom providers, developing applications and services leveraging AI can unlock significant improvements in operations and service delivery, particularly in areas such as maintenance and network optimization.

This course explores the diverse technologies that constitute AI and the skill sets necessary to implement them effectively. We will also examine specific AI applications within the telecommunications industry throughout the program.

Audience

• Network engineers
• Network operations personnel
• Telecom technical managers

Course Format

• A blend of lectures, discussions, and hands-on exercises

This course is designed for developers and data scientists who wish to understand and implement Artificial Intelligence in their application programs. It particularly focuses on Data Analysis, Distributed AI, and Natural Language Processing.

Chatbots are automated software applications designed to mimic human conversation through chat-based interfaces. These tools enable organizations to optimize operational efficiency by offering streamlined and rapid user engagement options.

This instructor-led live training equips participants with the skills necessary to construct chatbots using Python.

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

• Grasping the core principles of chatbot development
• Constructing, testing, deploying, and troubleshooting a variety of chatbots via Python

Target Audience

• Software Developers

Course Format

• A blend of lectures, interactive discussions, exercises, and extensive hands-on practice

Important Note

• For tailored training solutions, please reach out to us for arrangement.

In this instructor-led live training, participants will learn to use Python libraries for NLP by building an application that processes a set of pictures and generates captions.

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

• Design and code DL for NLP using Python libraries.
• Create Python code that reads a substantially huge collection of pictures and generates keywords.
• Create Python Code that generates captions from the detected keywords.

This instructor-led training session investigates NLP techniques in conjunction with the application of AI and Robotics within a business context. Participants will engage in computer-based examples and case study problem-solving exercises using Python.

Ollama is an open-source utility designed to run large language models locally on both consumer and enterprise hardware. By encapsulating model quantization, GPU allocation, and API serving into a single command-line interface, it empowers organizations to host LLMs such as Llama, Mistral, and Qwen independently, thereby eliminating the need to transmit prompts or data to providers like OpenAI, Anthropic, or Google.

This instructor-led live training, available online or onsite, is designed for developers and data scientists looking to leverage spaCy for processing extensive volumes of text to identify patterns and derive meaningful insights.

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

• Install and configure spaCy.
• Grasp spaCy's approach to Natural Language Processing (NLP).
• Extract patterns and gain business insights from large-scale data sources.
• Integrate the spaCy library with existing web and legacy applications.
• Deploy spaCy in live production environments to predict human behaviour.
• Utilise spaCy to pre-process text for Deep Learning.

Format of the Course

• Interactive lecture and discussion.
• Extensive 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 spaCy, please visit: https://spacy.io/

In the realm of Python Machine Learning, the Text Summarization feature is capable of ingesting input text and generating a concise summary. This functionality can be accessed either via the command-line interface or as a dedicated Python API and library. A particularly compelling application is the rapid generation of executive summaries, which proves invaluable for organizations required to analyze vast amounts of textual data prior to compiling reports and presentations.

Through this instructor-led live training, participants will gain the skills to utilize Python for building a straightforward application that automatically produces summaries of input text.

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

• Utilize a command-line tool designed for text summarization.
• Design and implement Text Summarization code utilizing Python libraries.
• Evaluate three distinct Python summarization libraries: sumy 0.7.0, pysummarization 1.0.4, and readless 1.0.17.

Audience

• Developers
• Data Scientists

Format of the course

• A blend of lectures, discussions, exercises, and extensive hands-on practice.

TensorFlow™ is an open-source software library designed for numerical computation using data flow graphs.

SyntaxNet serves as a neural-network-based Natural Language Processing framework for TensorFlow.

Word2Vec is utilized for learning vector representations of words, known as "word embeddings". Word2vec is a highly computationally efficient predictive model for acquiring word embeddings from raw text. It is available in two variants: the Continuous Bag-of-Words model (CBOW) and the Skip-Gram model (refer to chapters 3.1 and 3.2 in Mikolov et al.).

When used together, SyntaxNet and Word2Vec enable users to generate Learned Embedding models from Natural Language input.

Audience

This course is designed for Developers and engineers who plan to work with SyntaxNet and Word2Vec models within their TensorFlow graphs.

After completing this course, delegates will:

• understand TensorFlow’s structure and deployment mechanisms
• be able to perform installation, production environment setup, architecture tasks, and configuration
• be able to assess code quality, perform debugging, and monitoring
• be able to implement advanced production-level tasks such as training models, embedding terms, building graphs, and logging