Natural Language Processing (NLP) Training in Radom

This instructor-led live training in Radom equips finance practitioners and IT personnel with the skills to implement Ollama locally. Participants learn to deploy, configure, and integrate large language models into secure financial workflows, applying best practices for compliance and automation.

This live training in Radom helps healthcare practitioners and IT teams deploy Ollama for local LLMs. Learn to integrate AI into clinical workflows, customize models for specific tasks, and ensure strict data privacy and regulatory compliance within secure healthcare environments.

This instructor-led, live training in Radom helps beginners apply Claude AI to customer support and service operations. Participants will learn to automate triage, draft tone-consistent responses, and integrate AI into existing workflows using practical, hands-on exercises.

This live Claude AI training in Radom helps professionals use the tool for data analysis and BI tasks. It covers exploratory data analysis, SQL generation, and dashboard design through natural language prompting, aiming to streamline workflows and improve insight extraction from business data.

This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level data scientists and developers who wish to apply NLP techniques using Python in Google Colab.

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

• Understand the core concepts of natural language processing.
• Preprocess and clean text data for NLP tasks.
• Perform sentiment analysis using NLTK and SpaCy libraries.
• Work with text data using Google Colab for scalable and collaborative development.

This instructor-led, live training in Radom (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.

This instructor-led, live training in Radom (online or onsite) is aimed at beginner-level to intermediate-level content creators, writers, and marketers who want 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 Radom (online or onsite) is aimed at advanced-level professionals who wish to fine-tune and customize AI models on Ollama for enhanced performance and domain-specific applications.

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

• Set up an efficient environment for fine-tuning AI models on Ollama.
• Prepare datasets for supervised fine-tuning and reinforcement learning.
• Optimize AI models for performance, accuracy, and efficiency.
• Deploy customized models in production environments.
• Evaluate model improvements and ensure robustness.

This instructor-led, live training in Radom (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.
• Optimize 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 Radom (online or onsite) is aimed at intermediate-level software developers and AI engineers who wish to integrate Claude AI into their applications, build AI-powered chatbots, and enhance software functionality with AI-driven automation.

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

• Use the Claude AI API to integrate AI into applications.
• Develop AI-driven chatbots and virtual assistants.
• Enhance applications with AI-powered automation and NLP.
• Optimize and fine-tune Claude AI models for different use cases.

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

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

• Set up and deploy LLMs using Ollama.
• Optimize 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.

This instructor-led, live training in Radom (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.

This instructor-led, live training in Radom (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 in Radom (online or onsite) is aimed at beginner-level professionals who wish to install, configure, and use Ollama for running AI models on their local machines.

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

• Understand the fundamentals of Ollama and its capabilities.
• Set up Ollama for running local AI models.
• Deploy and interact with LLMs using Ollama.
• Optimize performance and resource usage for AI workloads.
• Explore use cases for local AI deployment in various industries.

A two-day course for developers who already use AI coding tools such as Cursor, Claude Code or Copilot. It covers delegating complete tasks to agents, building the personalisation stack (Rules, AGENTS.md, Skills, MCP, Agents), connecting and building MCP servers, running agents in parallel, and a structured agentic workflow. The material is tool-agnostic. It follows the Foundations course.

A two-day introduction to AI-assisted software development for people new to these tools, including those with little or no coding experience. It covers how the tools work, how to direct them with prompts, and how to apply them to common tasks: building a small project from scratch, working in an existing codebase, and reviewing the results. The material is tool-agnostic and applies to Cursor, Claude Code, Copilot and similar tools. It precedes the Agentic AI Development: Advanced Workflows course.

This 2-step training programme is designed for software delivery teams that want to integrate AI-assisted engineering workflows into their day-to-day activities using Claude Code.

This course Radom provides comprehensive artificial intelligence training spanning data analysis, distributed machine learning, and natural language processing, designed to help developers build large-scale intelligent systems. It offers an in-depth exploration of practical methodologies for Spark MLlib, recommendation engines, Word2Vec-based semantic analysis, and RNN-LSTM architectures. By enabling professionals to transform raw data into automated decision-making pipelines suitable for production deployment, the course comprehensively enhances the core capabilities required for building sophisticated intelligent systems

This instructor-led, live training in Radom (online or onsite) is aimed at senior leaders and executives who wish to harness Claude as a strategic business assistant to enhance decision-making, accelerate planning and build competitive advantage through AI-augmented leadership.

Claude Code is not a code-completion tool — it is a terminal-native development agent that reads your codebase, plans multi-step changes, runs tests, and drives tasks from a single instruction to a working result. This one-day workshop gives participants structured, hands-on experience: configuring Claude Code for real projects, writing delegations that produce reviewable results, using CLAUDE.md as a persistent project memory, and connecting internal tools via the Model Context Protocol.

This instructor-led, live training in Radom is aimed at intermediate-level developers who wish to take a project from idea to a deployed, production-ready application using Claude Code.

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

• Configure Claude Code and guide it effectively with a CLAUDE.md.
• Scaffold an application and integrate data and a CMS.
• Build tests and run QA with subagents.
• Set up automated deployment to Vercel or Cloud Run.

Ollama is an open-source tool for running large language models locally on consumer and enterprise hardware. It abstracts model quantization, GPU allocation, and API serving into a single command-line interface, enabling organizations to self-host LLMs like Llama, Mistral, and Qwen without sending prompts or data to OpenAI, Anthropic, or Google.