Natural Language Processing (NLP) Training in Maia

This instructor-led live training in Maia (online or onsite) is designed for intermediate-level AI professionals, business analysts, and technology leaders who want to understand the principles of generative AI and explore LLM applications within business environments. Participants will learn about transformers, prompt engineering, and the ethical considerations involved in deploying these models for real-world solutions.

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

• Grasp the fundamental principles of generative AI and large language models.
• Implement and fine-tune LLMs for specific business applications.
• Apply prompt engineering techniques to achieve optimal model outputs.
• Identify ethical considerations and manage risks associated with LLM deployment.

This instructor-led, live training in Maia (online or on-site) is designed for intermediate NLP practitioners, data scientists, content creators, translators, and global businesses aiming to leverage LLMs for language translation and multilingual content production.

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

• Grasp the fundamentals of cross-lingual learning and translation using LLMs.
• Deploy LLMs to translate content between multiple languages.
• Generate and manage multilingual datasets for training LLMs.
• Formulate strategies to ensure consistency and high quality in translation outcomes.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level content creators, marketers, and educational technologists who wish to harness the power of LLMs for generating high-quality, diverse, and engaging content across various domains.

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

• Understand the capabilities of LLMs and their application in content generation.
• Set up and use LLMs for generating various types of content.
• Apply best practices for prompting and fine-tuning LLMs to produce desired outputs.
• Evaluate the quality of AI-generated content and refine it for specific audiences.
• Explore advanced techniques for creative and multi-modal content generation with LLMs.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level software developers and technical writers who wish to leverage LLMs to streamline their coding workflow and create detailed, comprehensive documentation.

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

• Understand the role of LLMs in automating code generation and software documentation.
• Utilize LLMs to create accurate and efficient code snippets and documentation.
• Integrate LLMs into their software development lifecycle for enhanced productivity.
• Maintain high-quality documentation standards using automated tools.
• Address ethical considerations and best practices for using AI in software development.

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

This instructor-led live training (available online or onsite) is designed for intermediate-level healthcare practitioners and IT teams looking to deploy, customize, and operationalize Ollama-based AI solutions within clinical and administrative settings.

Upon completing this training, participants will be able to:

• Install and configure Ollama for secure use in healthcare environments.
• 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.

Course Format

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

Customization Options

• To request 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 interactions, and agentic applications.

This live, instructor-led training session, available online or onsite, is tailored for professionals at intermediate to advanced levels who aim to construct, deploy, and oversee AI agents utilizing Mistral’s Medium 3, Le Chat Enterprise, and Devstral models.

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

• Comprehend the architecture and capabilities of Mistral Medium 3, Le Chat Enterprise, and Devstral.
• Architect and deploy AI agents leveraging Mistral models for specific enterprise and developer scenarios.
• Seamlessly integrate coding systems, connectors, and enterprise data into agent workflows.
• Refine performance, cost-efficiency, and compliance for agents powered by Mistral.

Course Delivery Format

• Engaging lectures and group discussions.
• Extensive exercises and practical drills.
• Practical implementation within a live-lab environment.

Customization Availability

• Please contact us to discuss arrangements for a customized training experience.

Mistral AI is an open and enterprise-ready AI platform that provides features for secure, compliant, and responsible AI deployment.

This instructor-led, live training (online or onsite) is aimed at intermediate-level compliance leads, security architects, and legal/ops stakeholders who wish to implement responsible AI practices with Mistral by leveraging privacy, data residency, and enterprise control mechanisms.

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

• Implement privacy-preserving techniques in Mistral deployments.
• Apply data residency strategies to meet regulatory requirements.
• Set up enterprise-grade controls such as RBAC, SSO, and audit logs.
• Evaluate vendor and deployment options for 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) targets intermediate to advanced engineers looking to scale Ollama deployments for multi-user, high-throughput, and cost-efficient 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 autoscaling, batching, and latency reduction strategies.
• Monitor and optimize infrastructure for performance and cost efficiency.

Format of the Course

• Interactive lecture and discussion.
• Hands-on deployment and scaling labs.
• 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 utilities for real-time AI applications in computer vision and NLP, particularly on Huawei Ascend hardware.

This instructor-led live training (available online or onsite) is designed for intermediate-level AI professionals seeking to build, deploy, and optimize vision and language models using the CANN SDK for production-grade solutions.

Upon completing this training, participants will be capable of:

• Deploying and optimizing CV and NLP models utilizing CANN and AscendCL.
• Leveraging CANN utilities to convert models and integrate them into active pipelines.
• Enhancing inference performance for tasks such as detection, classification, and sentiment analysis.
• Constructing real-time CV/NLP pipelines tailored for edge or cloud-based deployment environments.

Course Format

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

Customization Options

• For those requiring customized training for this course, please contact us to arrange.

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

This instructor-led training session, available either online or onsite, targets professionals ranging from beginner to intermediate proficiency who aim to utilise Claude to expedite data analysis, derive actionable insights, and streamline BI processes.

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

• Utilise Claude to conduct ad-hoc exploratory data analysis.
• Generate SQL queries, summaries, and data transformations via natural language prompts.
• Leverage Claude to design dashboards, define KPIs, and create analytical views with greater efficiency.
• Interpret business data with improved accuracy through structured AI-assisted reasoning.

Course Format

• Instructor-led demonstrations alongside guided discussions.
• Practical exercises utilising real-world business datasets.
• Application of Claude within BI-focused scenarios.

Customization Options

• If you require the content to be tailored to your internal BI tools or workflows, please contact us to arrange a bespoke version of this course.

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

This instructor-led, live training (available online or onsite) targets intermediate-level ML researchers, applied engineers, and product teams looking to build multimodal applications using Mistral models, including OCR and document comprehension 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 comprehension 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 Maia (online or onsite) is designed for intermediate-level data scientists and developers wishing 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.

Mistral comprises a family of high-performance large language models, meticulously engineered for cost-efficient production deployment at scale.

This instructor-led live training, available either 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 completion of this training, participants will be able to:

• Implement scalable deployment patterns for Mistral Medium 3.
• Apply effective batching, quantization, and serving strategies.
• Optimize inference costs without compromising performance.
• Design production-ready serving topologies tailored for enterprise workloads.

Course Format

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

Course Customization Options

• To request a customized version of this course, please contact us to arrange.

This instructor-led, live training in Maia (online or onsite) is designed for intermediate-level professionals seeking to acquire practical expertise in automating text summarization and content generation using NLG.

Upon completing this training, participants will be capable of:

• Grasping the core principles of NLG for text summarization and content generation.
• Deploying NLG models to condense extensive documents and articles.
• Utilizing pre-trained NLG models, such as GPT, for content creation.
• Applying advanced techniques to fine-tune NLG models for specialized content generation tasks.

Postgres is a sophisticated open-source relational database that serves as a robust foundation for AI-driven systems and data intelligence applications.

This instructor-led live training (available online or onsite) is designed for intermediate-level database professionals and developers who aim to integrate, manage, and optimize AI capabilities directly within Postgres.

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

• Set up and configure Postgres extensions tailored for AI workloads.
• Implement embeddings and perform similarity searches using pgvector.
• Integrate both open-source and proprietary LLMs with Postgres to gain real-time insights.
• Optimize Postgres to efficiently handle AI-driven queries and workflows.

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and practical 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 Maia (online or onsite) is aimed at advanced-level professionals who wish to master AI-driven NLG techniques for chatbot and virtual assistant applications.

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

• Understand the core principles of NLG for conversational AI.
• Leverage deep learning techniques to enhance chatbot dialogue generation.
• Integrate state-of-the-art NLG models like GPT-3 into chatbot frameworks.
• Apply contextual AI for improving conversational coherence and fluidity.

Devstral is an open-source framework engineered to build and operate coding agents capable of interacting with codebases, developer tools, and APIs to boost engineering productivity.

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

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

• Configure and set up Devstral for coding agent development.
• Design agentic workflows tailored for codebase exploration and modification.
• Integrate coding agents seamlessly with developer tools and APIs.
• Apply best practices for secure and efficient agent deployment.

Course Format

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

Customization Options

• For personalized training requests, please contact us to arrange.

LangGraph is a framework designed for composing graph-structured LLM workflows that support branching, tool use, memory, and controllable execution.

This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers and product teams who wish to combine LangGraph’s graph logic with LLM agent loops to build dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.

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

• Design graph-based workflows that coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallbacks for robust execution.
• Integrate retrieval, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and harden agent behavior for reliability and safety.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based design exercises and peer reviews.

Course Customization Options

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

This instructor-led, live training in Maia (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.

Speech recognition and transcription using AI involves converting spoken language into written text through machine learning models and natural language processing systems.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to implement, evaluate, and optimize AI-powered speech-to-text solutions for real-world use cases.

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

• Understand how modern speech recognition models are trained and deployed.
• Evaluate open-source and commercial APIs for speech-to-text transcription.
• Handle multilingual and domain-specific transcription challenges.
• Build simple transcription workflows for different audio sources.

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 Maia (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.

LangGraph is a framework designed for constructing graph-structured LLM applications that support planning, branching, tool use, memory, and controllable execution.

This instructor-led, live training (online or onsite) is aimed at beginner-level developers, prompt engineers, and data practitioners who wish to design and build reliable, multi-step LLM workflows using LangGraph.

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

• Explain core LangGraph concepts (nodes, edges, state) and when to use them.
• Build prompt chains that branch, call tools, and maintain memory.
• Integrate retrieval and external APIs into graph workflows.
• Test, debug, and evaluate LangGraph apps for reliability and safety.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based exercises on design, testing, and evaluation.

Course Customization Options

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

This instructor-led, live training in Maia (online or onsite) is designed for developers at beginner to intermediate levels who wish to utilize Large Language Models for various natural language tasks.

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

• Configure a development environment integrated with a prominent LLM.
• Construct a foundational LLM and fine-tune it using a custom dataset.
• Apply LLMs to various natural language tasks such as text summarization, question answering, and text generation.
• Debug and evaluate LLMs using tools like TensorBoard, PyTorch Lightning, and Hugging Face Datasets.

This instructor-led, live training in Maia (online or onsite) is designed for beginner to intermediate 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.

An exploration of artificial intelligence fundamentals demonstrates how intelligent technology transforms digital strategy, automation, and decision-making processes within enterprise operations. The course examines core concepts including the history of AI, problem-solving frameworks, knowledge representation, reasoning under uncertainty, and machine learning paradigms, alongside aspects of communication, perception, and autonomous action. It equips executives and architects to evaluate AI-driven transformation opportunities, assess emerging technology trends, and implement practical intelligent solutions to enhance business agility.

Artificial intelligence training covers data analysis, distributed artificial intelligence, and natural language processing. The course aims to provide developers and data scientists with the application technologies needed to build large-scale AI systems. Course content includes distributed machine learning, Apache Spark MLlib, and the core principles of MapReduce-based predictions. It also delves into practical methods for recommendation engines, text classification, semantic analysis using Word2Vec, and RNN-LSTM architectures. This course helps professionals deploy artificial intelligence pipelines suitable for production environments, transforming raw data into automated decision-making capabilities.

This instructor-led live training in Maia is designed for 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 using a CLAUDE.md file.
• Scaffold an application and integrate data sources and a CMS.
• Build tests and run quality assurance with subagents.
• Set up automated deployment to Vercel or Cloud Run.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level engineers and architects who wish to use Tencent Hunyuan to deploy large and MoE models with lower latency, stronger throughput, and better cost control.

By the end of this training, participants will be able to: explain Hunyuan production deployment patterns, optimize inference performance, implement batching and quantization strategies, and plan scalable serving operations.

Natural Language Processing converts raw text into actionable intelligence, allowing machines to understand human communication. The course explores fundamental techniques including corpus analysis, sentence structure parsing, text preprocessing pipelines, and dimensionality reduction using SVD and NMF methods. Participants are guided through practical implementations of document clustering, topic modelling, sentiment analysis, named entity recognition, and Latent Dirichlet Allocation in Python. This equips practitioners with the skills to build intelligent text analytics systems for automated content classification and search.