Cross-Lingual LLMs Training Course
Cross-lingual LLMs are transforming the field of language translation and content creation by enabling more accurate and context-aware translations across multiple languages.
This instructor-led, live training (online or onsite) is aimed at intermediate-level NLP practitioners and data scientists, content creators and translators, and global businesses who wish to use LLMs for language translation and creating multilingual content.
By the end of this training, participants will be able to:
- Understand the principles of cross-lingual learning and translation with LLMs.
- Implement LLMs for translating content between various languages.
- Create and manage multilingual datasets for training LLMs.
- Develop strategies for maintaining consistency and quality in translation.
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.
Course Outline
Introduction to Cross-Lingual LLMs
- Exploring the capabilities of LLMs in language translation
- Challenges and solutions in cross-lingual NLP
- Case studies: Successful cross-lingual LLM applications
LLMs for Language Translation
- Preprocessing techniques for multilingual data
- Training LLMs for translation tasks
- Evaluating translation quality and performance
Creating Multilingual Content with LLMs
- Designing content strategies for global audiences
- LLMs in content localization and cultural adaptation
- Automating content creation across languages
Best Practices in Cross-Lingual Applications
- Maintaining linguistic accuracy and cultural relevance
- Addressing ethical considerations in automated translation
- Improving user experience in multilingual interfaces
Hands-on Lab: Cross-Lingual Translation Project
- Building a multilingual translation model with LLMs
- Testing the model with diverse language pairs
- Refining the system for industry-specific content
Summary and Next Steps
Requirements
- A basic understanding of natural language processing (NLP)
- Experience with Python programming and machine learning
- Familiarity with language translation and linguistics
Audience
- NLP practitioners and data scientists
- Content creators and translators
- Global businesses seeking to improve international communication
Open Training Courses require 5+ participants.
Cross-Lingual LLMs Training Course - Booking
Cross-Lingual LLMs Training Course - Enquiry
Cross-Lingual LLMs - Consultancy Enquiry
Provisional Upcoming Courses (Require 5+ participants)
Related Courses
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursLangGraph is a framework for building stateful, multi-actor LLM applications as composable graphs with persistent state and control over execution.
This instructor-led, live training (online or onsite) is aimed at advanced-level AI platform engineers, DevOps for AI, and ML architects who wish to optimize, debug, monitor, and operate production-grade LangGraph systems.
By the end of this training, participants will be able to:
- Design and optimize complex LangGraph topologies for speed, cost, and scalability.
- Engineer reliability with retries, timeouts, idempotency, and checkpoint-based recovery.
- Debug and trace graph executions, inspect state, and systematically reproduce production issues.
- Instrument graphs with logs, metrics, and traces, deploy to production, and monitor SLAs and costs.
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.
Building Coding Agents with Devstral: From Agent Design to Tooling
14 HoursDevstral 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.
Open-Source Model Ops: Self-Hosting, Fine-Tuning and Governance with Devstral & Mistral Models
14 HoursDevstral and Mistral models are open-source AI technologies designed for flexible deployment, fine-tuning, and scalable integration.
This instructor-led, live training (online or onsite) is aimed at intermediate–level to advanced–level 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 for domain-specific performance.
- Implement versioning, monitoring, and lifecycle governance.
- Ensure security, compliance, and responsible usage of open-source models.
Format of the Course
- Interactive lecture and discussion.
- Hands-on exercises in self-hosting and fine-tuning.
- Live-lab implementation of governance and monitoring pipelines.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph Applications in Finance
35 HoursLangGraph Foundations: Graph-Based LLM Prompting and Chaining
14 HoursLangGraph is a framework for building 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.
LangGraph in Healthcare: Workflow Orchestration for Regulated Environments
35 HoursLangGraph for Legal Applications
35 HoursBuilding Dynamic Workflows with LangGraph and LLM Agents
14 HoursLangGraph for Marketing Automation
14 HoursLangGraph is a graph-based orchestration framework that enables conditional, multi-step LLM and tool workflows, ideal for automating and personalizing content pipelines.
This instructor-led, live training (online or onsite) is aimed at intermediate-level marketers, content strategists, and automation developers who wish to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.
By the end of this training, participants will be able to:
- Design graph-structured content and email workflows with conditional logic.
- Integrate LLMs, APIs, and data sources for automated personalization.
- Manage state, memory, and context across multi-step campaigns.
- Evaluate, monitor, and optimize workflow performance and delivery outcomes.
Format of the Course
- Interactive lectures and group discussions.
- Hands-on labs implementing email workflows and content pipelines.
- Scenario-based exercises on personalization, segmentation, and branching logic.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Le Chat Enterprise: Private ChatOps, Integrations & Admin Controls
14 HoursCost-Effective LLM Architectures: Mistral at Scale (Performance / Cost Engineering)
14 HoursProductizing Conversational Assistants with Mistral Connectors & Integrations
14 HoursMistral 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.
Enterprise-Grade Deployments with Mistral Medium 3
14 HoursMistral Medium 3 is a high-performance, multimodal large language model designed for production-grade deployment across enterprise environments.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level AI/ML engineers, platform architects, and MLOps teams who wish to deploy, optimize, and secure Mistral Medium 3 for enterprise use cases.
By the end of this training, participants will be able to:
- Deploy Mistral Medium 3 using API and self-hosted options.
- Optimize inference performance and costs.
- Implement multimodal use cases with Mistral Medium 3.
- Apply security and compliance best practices for enterprise environments.
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.
Mistral for Responsible AI: Privacy, Data Residency & Enterprise Controls
14 HoursMistral 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.
