Large Language Models (LLMs) Training in India

This instructor-led, live training in India (online or onsite) is tailored for senior management professionals eager to grasp the fundamentals of LLMs, explore their potential impact on business operations, and assess practical applications of AI tools such as ChatGPT, Microsoft Copilot, or Grok for real-world tasks including content creation, data summarization, and strategic decision support.

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

• Comprehend the nature of LLMs and the operational mechanics of tools like ChatGPT and Copilot.
• Employ effective prompting techniques to derive practical and reliable outcomes from LLMs.
• Evaluate tangible use cases such as drafting emails, summarizing documents, and automating productivity workflows.
• Identify potential investment opportunities and strategic avenues for AI adoption within their organizations.

This instructor-led, live training session (online or onsite) is designed for senior management teams eager to grasp the strategic value of LLMs and enterprise-grade AI tools. Participants will discover how to seamlessly integrate these technologies into high-level workflows, craft effective prompts, and assess opportunities for enhanced productivity and return on investment (ROI) via AI adoption.

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

• Comprehend the functioning of LLMs and the application of tools like ChatGPT and Copilot.
• Leverage prompt-based interactions to automate and expedite tasks.
• Deploy AI tools in real-world scenarios, including drafting emails, summarizing reports, and reviewing agreements.
• Assess the strategic advantages, limitations, and licensing factors associated with adopting LLMs.

This guided, live training in India (online or onsite) is intended for AI researchers, data scientists, and developers at an intermediate to advanced level who aim to comprehend, customize, and deploy Meta AI's Large Language Models for diverse NLP applications.

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

• Comprehend the architecture and workings of Meta AI's Large Language Models.
• Set up and customize Meta AI LLMs for particular use cases.
• Create LLM-based applications like text summarizers, chatbots, and sentiment analysis tools.
• Efficiently optimize and deploy large language models.

This instructor-led, live training in India (online or onsite) is designed for intermediate-level AI professionals, business analysts, and technology leaders eager to grasp the fundamentals of generative AI and its business applications. Participants will explore transformers, prompt engineering, and the ethical aspects of deploying these models for practical solutions.

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

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

This instructor-led, live training in India (online or onsite) is aimed at intermediate-level AI professionals and ethicists, data scientists and engineers, and policy makers and stakeholders who wish to understand and navigate the ethical landscape of LLMs.

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

• Identify ethical issues and challenges associated with LLMs.
• Apply ethical frameworks and principles to LLM deployment.
• Assess the societal impact of LLMs and mitigate potential risks.
• Develop strategies for responsible AI development and usage.

This instructor-led, live training in India (online or onsite) targets intermediate-level NLP practitioners, data scientists, content creators, translators, and global businesses interested in utilizing LLMs for language translation and multilingual content development.

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

• Understand the fundamental concepts of cross-lingual learning and translation with LLMs.
• Implement LLMs for translating content between different languages.
• Create and manage multilingual datasets for training LLMs.
• Develop strategies to maintain consistency and quality in translation.

This instructor-led, live training in India (online or on-site) is tailored for intermediate-level financial analysts, data scientists, and investment professionals who wish to leverage LLMs for financial market analysis and prediction.

Upon completing this training, participants will be able to:

• Grasp the application of LLMs in financial market analysis.
• Utilise LLMs to analyse financial news, reports, and data to generate market insights.
• Construct predictive models for stock prices, market trends, and economic indicators.
• Integrate insights derived from LLMs into investment decision-making frameworks.

This live, instructor-led training in India (online or on-site) is designed for intermediate-level environmental scientists, researchers, data analysts, and policy makers or advocates who intend to utilize LLMs for environmental modeling and analysis.

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

• Comprehend the application of LLMs in environmental science.
• Use LLMs to analyze and model environmental data.
• Interpret LLM outputs for environmental impact assessments.
• Communicate findings effectively to inform policy and conservation efforts.

This instructor-led, live training in India (online or onsite) targets intermediate-level VR and AR developers, game designers, and AI engineers who aim to incorporate LLMs into VR and AR applications to create more engaging and responsive environments.

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

• Understand the role of LLMs in creating immersive VR and AR experiences.
• Develop VR and AR applications that utilize LLMs for interactive dialogues and content creation.
• Integrate LLMs with VR and AR development tools for enhanced user engagement.
• Apply best practices for designing AI-driven narratives and interactions in virtual spaces.

This instructor-led, live training in India (online or onsite) targets intermediate-level data scientists, machine learning engineers, and software developers who wish to apply Large Language Models (LLMs) to multimodal data for advanced AI applications.

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

• Comprehend the fundamental principles of multimodal learning with LLMs.
• Implement LLMs to process and analyse text, image, and audio data.
• Develop applications that capitalise on the strengths of multimodal data integration.
• Evaluate the performance of multimodal LLM systems.

This instructor-led, live training in India (online or onsite) is designed for intermediate-level cybersecurity experts and data scientists who wish to leverage LLMs to enhance cybersecurity measures and threat intelligence.

Upon completing this training, participants will be able to:

• Grasp the significance of LLMs within the cybersecurity landscape.
• Deploy LLMs for effective threat detection and analysis.
• Apply LLMs to automate security tasks and manage responses.
• Seamlessly integrate LLMs into current security frameworks.

This instructor-led, live training in India (online or onsite) targets intermediate-level data scientists and business analysts who wish to utilize large language models (LLMs) to forecast trends and behaviours in various industries.

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

• Understand the fundamentals of LLMs and their role in predictive analytics.
• Implement LLMs to analyze and forecast data in various industries.
• Evaluate the effectiveness of predictive models using LLMs.
• Integrate LLMs with existing data processing pipelines.

This instructor-led, live training in India (online or onsite) is aimed at intermediate-level data scientists who wish to gain a comprehensive understanding and practical skills in both Large Language Models (LLMs) and Reinforcement Learning (RL).

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

• Understand the components and functionality of transformer models.
• Optimize and fine-tune LLMs for specific tasks and applications.
• Understand the core principles and methodologies of reinforcement learning.
• Learn how reinforcement learning techniques can enhance the performance of LLMs.

This instructor-led live training in India (online or onsite) targets intermediate-level content creators, marketers, and educational technologists aiming to harness 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 India (online or onsite) is designed for educators, EdTech professionals, and researchers with diverse experience levels who aim to leverage LLMs to create personalized educational experiences.

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

• Grasp the architecture and capabilities of LLMs.
• Identify opportunities for personalization in educational content using LLMs.
• Design adaptive learning platforms that utilize LLMs for content personalization.
• Implement LLM-driven strategies to enhance student engagement and learning outcomes.
• Evaluate the effectiveness of LLMs in educational settings and make data-driven decisions for

This instructor-led, live training in India (online or onsite) is designed for intermediate-level ML practitioners and AI developers who wish to fine-tune and deploy open-weight models like LLaMA, Mistral, and Qwen for specific business or internal applications.

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

• Grasp the ecosystem and key distinctions among open-source LLMs.
• Prepare datasets and fine-tuning configurations for models like LLaMA, Mistral, and Qwen.
• Execute fine-tuning pipelines using Hugging Face Transformers and PEFT.
• Evaluate, save, and deploy fine-tuned models in secure environments.

This instructor-led, live training in India (online or onsite) is designed for beginner to intermediate software developers and data scientists who aim to integrate LLMs into speech recognition and synthesis systems.

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

• Grasp the role of LLMs in speech technologies.
• Implement LLMs to achieve accurate speech recognition and natural-sounding speech synthesis.
• Integrate LLMs with speech recognition engines and speech synthesizers.
• Evaluate and enhance the performance of speech systems using LLMs.
• Keep up with current trends and future directions in speech technologies.

This instructor-led live training in India (online or onsite) is designed for customer support and IT professionals at beginner to intermediate levels who aim to implement LLMs to develop responsive and intelligent customer support chatbots.

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

• Grasp the fundamentals and architecture of Large Language Models (LLMs).
• Design and integrate LLMs into customer support systems.
• Improve the responsiveness and user experience of chatbots.
• Address ethical considerations and ensure compliance with industry standards.
• Deploy and maintain an LLM-based chatbot for real-world applications.

This instructor-led, live training in India (available online or on-site) is designed for intermediate-level data scientists and AI engineers who wish to fine-tune large language models more affordably and efficiently using techniques like LoRA, Adapter Tuning, and Prefix Tuning.

Upon completing this training, participants will be able to:

• Understand the theoretical underpinnings of parameter-efficient fine-tuning approaches.
• Implement LoRA, Adapter Tuning, and Prefix Tuning using the Hugging Face PEFT library.
• Analyze the performance and cost trade-offs of PEFT methods compared to full fine-tuning.
• Deploy and scale fine-tuned LLMs with reduced compute and storage requirements.

This instructor-led, live training in India (online or onsite) is tailored for intermediate to advanced machine learning engineers, AI developers, and data scientists who wish to learn how to use QLoRA to efficiently fine-tune large models for specific tasks and custom implementations.

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

• Comprehend the theory behind QLoRA and quantization techniques for LLMs.
• Apply QLoRA to fine-tune large language models for domain-specific applications.
• Enhance fine-tuning performance on limited computational resources through quantization.
• Efficiently deploy and evaluate fine-tuned models in real-world applications.

This instructor-led, live training session in India (available online or onsite) is designed for intermediate-level data and marketing professionals seeking to apply LLMs for analyzing and interpreting public sentiment from various text sources such as social media posts, product reviews, and customer feedback.

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

• Comprehend the core principles of sentiment analysis and its application via LLMs.
• Preprocess and prepare datasets specifically for sentiment analysis tasks.
• Train and fine-tune LLMs to accurately capture and reflect sentiment within text.
• Conduct real-time sentiment analysis on social media and other textual data sources.
• Integrate insights derived from sentiment analysis into business strategies and decision-making frameworks.

This instructor-led, live training in India (online or onsite) is designed for intermediate-level software developers and technical writers who aim to harness LLMs to streamline their coding workflow and produce detailed, comprehensive documentation.

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

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

This instructor-led live training, available in online or onsite formats, is tailored for intermediate-level business professionals and data analysts keen on leveraging LLMs to extract actionable business insights.

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

• Understand the fundamentals and applications of LLMs in the context of business intelligence.
• Apply LLMs to analyze large datasets and extract meaningful insights.
• Integrate LLM-driven analytics into strategic business decision-making processes.
• Evaluate the ethical considerations and best practices for using LLMs in business.
• Anticipate future trends in AI and prepare for the evolving landscape of business intelligence.

This instructor-led, live training in India (online or onsite) is designed for intermediate to advanced developers and data scientists who aim to master LlamaIndex for developing cutting-edge LLM-powered applications.

By the conclusion of this training, participants will be capable of:

• Setting up and configuring LlamaIndex for use with LLMs.
• Indexing and querying custom datasets using LlamaIndex to enhance LLM functionality.
• Designing and developing sophisticated applications that utilize LlamaIndex and LLMs.
• Understanding and applying best practices for working with LLMs and LlamaIndex.
• Navigating the ethical considerations involved in deploying LLM-powered applications.

This instructor-led live training in India (online or onsite) targets intermediate-level AI researchers, machine learning professionals, and data scientists who wish to use LlamaIndex to enhance AI model capabilities, making them more accurate and reliable for various applications.

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

• Understand the principles and components of LlamaIndex.
• Ingest and structure data for use with LLMs.
• Implement context augmentation to improve AI model performance.
• Integrate LlamaIndex into existing AI systems and workflows.

This instructor-led, live training in India (online or onsite) is designed for intermediate-level professionals who aim to utilise the power of prompt engineering and few-shot learning to optimise LLM performance for real-world applications.

Upon completing this training, participants will be capable of:

• Grasping the core principles of prompt engineering and few-shot learning.
• Crafting effective prompts suited for various NLP tasks.
• Utilising few-shot techniques to adapt LLMs with minimal data requirements.
• Optimising LLM performance for practical, everyday applications.

This instructor-led, live training (available online or onsite) is designed for advanced-level engineers, AI specialists, and localization leads who wish to implement large language model (LLM) systems for automated translation, quality evaluation, and enterprise governance.

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

• Build enterprise-grade LLM localization pipelines integrating open and proprietary models.
• Implement automated QA workflows and quality metrics for translation consistency.
• Establish governance and approval frameworks for multilingual content production.
• Deploy scalable, auditable LLM-based localization systems in secure environments.

AI for SQL involves the application of artificial intelligence and large language models (LLMs) to automate, optimize, and enhance the generation, execution, and interpretation of SQL queries within enterprise data environments.

This instructor-led live training, available online or onsite, targets intermediate-level data engineers and technical leads who aim to integrate AI capabilities into SQL workflows to facilitate natural language querying, intelligent optimization, and automated data analysis.

Upon completing this training, participants will be able to:

• Integrate LLMs such as GPT, DeepSeek, LLaMA, Qwen, and Mistral into SQL environments.
• Construct natural-language-to-SQL pipelines to enable conversational data access.
• Implement AI-driven query optimization and error detection mechanisms.
• Design secure, auditable AI-SQL workflows suitable for enterprise use.

Course Format

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

Course Customization Options

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

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

This instructor-led live training, available online or onsite, targets intermediate to advanced professionals seeking to design, implement, and manage finance solutions based on LangGraph, ensuring proper governance, observability, and compliance.

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

• Develop finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrate financial data standards and ontologies into graph states and tooling.
• Implement reliability, safety, and human-in-the-loop controls for critical operations.
• Deploy, monitor, and optimize LangGraph systems to enhance performance, manage costs, and meet SLAs.

Course Format

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

Customization Options

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

Vertex AI empowers developers with robust tools to construct multimodal LLM workflows that seamlessly unite text, audio, and image data within a unified pipeline. Leveraging extended context window capabilities and configurable Gemini API parameters, it facilitates the creation of sophisticated applications focused on strategic planning, complex reasoning, and cross-modal intelligence.

This instructor-led live training, available both online and onsite, is tailored for intermediate to advanced practitioners eager to design, develop, and fine-tune multimodal AI workflows on the Vertex AI platform.

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

• Utilize Gemini models effectively for handling diverse multimodal inputs and outputs.
• Construct long-context workflows to tackle intricate reasoning tasks.
• Architect pipelines that successfully integrate text, audio, and image analysis.
• Optimize Gemini API parameters to enhance performance while maintaining cost efficiency.

Course Format

• Engaging lectures and interactive discussions.
• Practical hands-on labs focused on multimodal workflows.
• Project-based exercises designed for real-world multimodal use cases.

Customization Options

• For organizations seeking a tailored training experience, please reach out to us to discuss custom arrangements.

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

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based healthcare solutions while addressing 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 (FHIR, SNOMED CT, 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.

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI developers and localization engineers who wish to design scalable, automated translation pipelines using both proprietary and open-source LLMs.

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

• Design and deploy translation workflows using modern LLM frameworks and APIs.
• Integrate open-source and commercial models into scalable translation systems.
• Optimize translation quality through fine-tuning, prompt engineering, and automation.
• Implement cost-efficient and compliant translation infrastructure for enterprise environments.

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

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

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

• Design and optimize complex LangGraph topologies to enhance speed, reduce costs, and ensure scalability.
• Engineer reliability by implementing retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debug and trace graph executions, inspect state data, and systematically reproduce production issues.
• Instrument graphs with logs, metrics, and traces; deploy to production environments; and monitor SLAs and costs.

Course Format

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

Customization Options

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

This instructor-led, live training in India (online or onsite) is designed for intermediate-level developers who wish to learn how to leverage generative AI with LLMs for various tasks and domains.

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

• Articulate the concept of generative AI and understand its operational mechanisms.
• Detail the transformer architecture that underpins LLMs.
• Leverage empirical scaling laws to optimize LLMs for specific tasks and constraints.
• Utilize cutting-edge tools and methodologies to train, fine-tune, and deploy LLMs.
• Evaluate the opportunities and risks associated with generative AI in societal and business contexts.

Large language models (LLMs) and autonomous agent frameworks such as AutoGen and CrewAI are transforming how DevOps teams automate processes like change monitoring, test creation, and alert triage by emulating human-like collaboration and decision-making capabilities.

This instructor-led live training, available either online or onsite, is designed for advanced-level engineers seeking to architect and implement DevOps automation workflows driven by large language models (LLMs) and multi-agent systems.

Upon completing this training, participants will be equipped to:

• Embed LLM-driven agents into CI/CD pipelines for intelligent automation.
• Leverage agents to automate test generation, commit analysis, and change summaries.
• Orchestrate multiple agents to triage alerts, formulate responses, and offer DevOps recommendations.
• Construct secure and maintainable agent-enabled workflows using open-source frameworks.

Course Format

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

Course Customization Options

• To arrange a customized training session for this course, please contact us to coordinate the details.

Postgres, a sophisticated open-source relational database, serves as a robust foundation for building AI-powered systems and data intelligence applications.

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

Upon completing this course, participants will be equipped 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 derive real-time insights.
• Optimize Postgres performance for AI-driven queries and workflows.

Course Format

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

Customization Options

• For customized training arrangements, please reach out to us.

This instructor-led, live training in India (online or onsite) targets intermediate to advanced AI developers, architects, and product managers who wish to identify and mitigate risks associated with LLM-powered applications, including prompt injection, data leakage, and unfiltered output, while incorporating security controls like input validation, human-in-the-loop oversight, and output guardrails.

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

• Understand the core vulnerabilities of LLM-based systems.
• Apply secure design principles to LLM app architecture.
• Use tools such as Guardrails AI and LangChain for validation, filtering, and safety.
• Integrate techniques like sandboxing, red teaming, and human-in-the-loop review into production-grade pipelines.

This instructor-led live training in India (online or onsite) is designed for intermediate to advanced professionals who want to customize pre-trained models for specific tasks and datasets.

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

• Grasp the principles of fine-tuning and its applications.
• Prepare datasets for fine-tuning pre-trained models.
• Fine-tune large language models (LLMs) for NLP tasks.
• Optimize model performance and address common challenges.

The course 'LLMs for Code Understanding, Refactoring, and Documentation' is a technical program designed to teach the application of large language models (LLMs) to enhance code quality, minimize technical debt, and streamline documentation processes within software teams.

This instructor-led live training, available both online and onsite, is tailored for intermediate to advanced software professionals aiming to utilise LLMs like GPT to better analyse, refactor, and document intricate or legacy codebases.

Upon completing this training, participants will gain the ability to:

• Utilise LLMs to elucidate code, dependencies, and logic within unfamiliar repositories.
• Identify and refactor anti-patterns while enhancing code readability.
• Automatically generate and maintain inline comments, README files, and API documentation.
• Integrate LLM-driven insights into existing CI/CD and review workflows.

Course Format

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

Customization Options

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

This instructor-led, live training in India (online or onsite) is designed for 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:

• Set up a development environment equipped with LLMs and essential tools.
• Expertly perform NLU and NLI tasks using LLMs.
• Extract, infer, and utilize knowledge graphs effectively.
• 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 the responsible use of LLMs.

LangGraph serves as a framework for constructing LLM applications with graph structures, enabling capabilities such as planning, branching, tool integration, memory management, and controllable execution.

This instructor-led training, available both online and onsite, is tailored for beginner-level developers, prompt engineers, and data professionals looking to design and implement robust, multi-step LLM workflows using LangGraph.

Upon completing this training, participants will be able to:

• Articulate the fundamental concepts of LangGraph (nodes, edges, state) and identify appropriate use cases.
• Construct prompt chains that support branching, tool invocation, and memory retention.
• Incorporate retrieval mechanisms and external APIs into graph-based workflows.
• Conduct testing, debugging, and evaluation of LangGraph applications to ensure reliability and safety.

Course Format

• Interactive lectures and guided discussions.
• Hands-on labs and code walkthroughs conducted in a sandbox environment.
• Scenario-based exercises focusing on design, testing, and evaluation.

Customization Options

• For personalized training arrangements for this course, please reach out to us.

This instructor-led, live training in India (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use Large Language Models for various natural language tasks.

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

• Set up a development environment that includes a popular LLM.
• Create a basic LLM and fine-tune it on a custom dataset.
• Use LLMs for different natural language tasks such as text summarization, question answering, text generation, and more.
• Debug and evaluate LLMs using tools such as TensorBoard, PyTorch Lightning, and Hugging Face Datasets.

This instructor-led, live training in India (online or onsite) is aimed at observability and SRE engineers who want to integrate LLMs and AI into their monitoring, alerting, and incident analysis workflows.

This instructor-led, live training in India (online or onsite) is aimed at IT support professionals who wish to use AI tools and automation platforms to streamline support processes, standardize responses, and reduce manual documentation effort.

This instructor-led live training in India (online or onsite) is designed for intermediate-level engineers and architects who wish to use Tencent Hunyuan to deploy large and MoE models with reduced latency, enhanced throughput, and better cost control.

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

This instructor-led live training in India (available online or onsite) is intended for intermediate-level developers, technical product teams, and AI practitioners who aim to use Hunyuan models to develop multimodal applications for generating and delivering images, 3D content, and videos.

By the end of this training, participants will be able to: establish prompt-driven workflows, generate and review multimodal assets, serve outputs through applications or APIs, and connect Hunyuan capabilities with enterprise product ecosystems.

Course objectives turn software and AI engineers into legal engineers—professionals who can build AI for legal work (eDiscovery, review, investigations).

In two days, participants will construct the full core stack: ingesting and extracting messy real-world legal data, searching and retrieving it, adding retrieval-augmented generation (RAG) with citations, ensuring privacy via a local model to prove compliance, conducting a defensible AI review with court-ready metrics, and packaging the result for deployment.

This instructor-led, live training in India (available online or onsite) is designed for beginner-level, intermediate-level, or advanced-level AI professionals who wish to utilise MCP to connect AI assistants with external tools, data, and enterprise services.

By the conclusion of this training, participants will be able to explain MCP concepts, identify key architectural components, set up a basic integration, and apply security best practices.

This instructor-led, live training in India (online or onsite) is aimed at intermediate-level enterprise architects who wish to use Model Context Protocol to design secure, scalable, and governable agent integration platforms for enterprise environments.

By the end of this training, participants will be able to: explain MCP architecture and enterprise patterns, design secure integration platforms, apply governance and access controls, and evaluate deployment and scaling options.

This instructor-led, live training in India (online or onsite) is targeted at intermediate-level developers, architects, and platform engineers who wish to use MCP to build reliable servers and clients for enterprise deployment and operations.

By the end of this training, participants will be able to: explain MCP architecture in practice, build production-ready integrations, deploy and observe MCP services, and apply versioning, resilience, and support patterns.

This instructor-led, live training in India (online or onsite) is aimed at intermediate-level IT leaders, compliance professionals, security teams, and enterprise architects who wish to leverage sovereign AI principles and governance practices. The objective is to design AI environments that protect sensitive data, support localization requirements, and reduce vendor lock-in.

By the end of this training, participants will be able to explain sovereign AI concepts, evaluate hosting and governance options, define controls for prompts and logs, and create a practical adoption roadmap.