Deep Learning for NLP (Natural Language Processing) Training Course
DL (Deep Learning) represents a specialized subset of ML (Machine Learning).
Python is a widely adopted programming language that offers robust libraries tailored for Deep Learning in the context of NLP.
Deep Learning for NLP (Natural Language Processing) enables machines to master language processing tasks ranging from simple to highly complex. Current applications include language translation and generating descriptive captions for images.
During this instructor-led, live training, participants will acquire the skills to utilize Python libraries for NLP while building an application capable of processing a set of images and producing corresponding captions.
Upon completion of this training, participants will be able to:
- Design and implement DL solutions for NLP using Python libraries.
- Write Python code capable of reading large-scale image collections and extracting keywords.
- Develop Python code that generates captions based on the identified keywords.
Course Format
- A blend of lectures, discussions, exercises, and intensive hands-on practice.
Course Outline
Introduction to Deep Learning for NLP
Differentiating between various types of DL models
Utilizing pre-trained versus custom-trained models
Employing word embeddings and sentiment analysis to derive meaning from text
Understanding the mechanics of Unsupervised Deep Learning
Installing and configuring Python Deep Learning libraries
Leveraging the Keras DL library atop TensorFlow to enable Python-generated captions
Working with Theano (a numerical computation library) and TensorFlow (a general and linguistic library) as extended DL libraries for caption creation.
Using Keras on top of TensorFlow or Theano for rapid Deep Learning experimentation
Developing a simple Deep Learning application in TensorFlow to add captions to a collection of images
Troubleshooting techniques
Overview of other specialized DL frameworks
Deploying your DL application
Utilizing GPUs to accelerate Deep Learning
Closing remarks
Requirements
- Foundational knowledge of Python programming.
- General understanding of Python libraries.
Audience
- Programmers with an interest in linguistics.
- Programmers seeking to deepen their understanding of NLP (Natural Language Processing).
Open Training Courses require 5+ participants.
Deep Learning for NLP (Natural Language Processing) Training Course - Booking
Deep Learning for NLP (Natural Language Processing) Training Course - Enquiry
Deep Learning for NLP (Natural Language Processing) - Consultancy Enquiry
Upcoming Courses
Related Courses
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursLangGraph is a framework designed for creating stateful, multi-actor LLM applications through composable graphs that maintain persistent state and provide execution control.
This instructor-led, live training (available online or onsite) targets advanced AI platform engineers, AI DevOps specialists, and ML architects who aim to optimize, debug, monitor, and manage production-grade LangGraph systems.
By the conclusion of this training, participants will be equipped to:
- Design and optimize complex LangGraph topologies for enhanced speed, cost-efficiency, and scalability.
- Engineer reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
- Debug and trace graph executions, inspect state variables, 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.
- Extensive exercises and practical application.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training session for this course, please contact us to arrange details.
Building Coding Agents with Devstral: From Agent Design to Tooling
14 HoursDevstral is an open-source framework engineered for the creation and execution of coding agents capable of interacting with code repositories, developer utilities, and APIs to boost engineering efficiency.
This instructor-led, live training (available online or on-site) targets intermediate to advanced ML engineers, developer-tooling teams, and Site Reliability Engineers (SREs) who aim to design, implement, and optimize coding agents using Devstral.
Upon completing this training, participants will be able to:
- Establish and configure the Devstral environment for coding agent development.
- Design agentic workflows for exploring and modifying codebases.
- Integrate coding agents 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 in a live laboratory environment.
Customization Options
- To request tailored training for this course, please contact us to arrange the details.
Open-Source Model Ops: Self-Hosting, Fine-Tuning and Governance with Devstral & Mistral Models
14 HoursDevstral and Mistral models are open-source AI technologies engineered for flexible deployment, fine-tuning, and scalable integration.
This instructor-led live training (available online or onsite) is tailored for intermediate to advanced ML engineers, platform teams, and research engineers who aim to self-host, fine-tune, and govern Mistral and Devstral models within production environments.
Upon completion of this training, participants will be capable of:
- Setting up and configuring self-hosted environments for Mistral and Devstral models.
- Applying fine-tuning techniques to enhance domain-specific performance.
- Implementing versioning, monitoring, and lifecycle governance strategies.
- Ensuring 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.
Customization Options
- To request tailored training for this course, please contact us to arrange.
LangGraph Applications in Finance
35 HoursLangGraph serves as a framework for constructing stateful, multi-agent LLM applications using composable graphs that maintain persistent state and provide precise control over execution flow.
This instructor-led live training, available online or on-site, targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and regulatory compliance.
Upon completion of this training, participants will be able to:
- Design finance-specific LangGraph workflows that align with regulatory and audit requirements.
- Integrate financial data standards and ontologies into graph states and associated tools.
- Implement reliability, safety measures, and human-in-the-loop controls for critical operations.
- Deploy, monitor, and optimize LangGraph systems to ensure high performance, cost efficiency, and adherence to SLAs.
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.
LangGraph Foundations: Graph-Based LLM Prompting and Chaining
14 HoursLangGraph is a framework designed for constructing graph-structured Large Language Model (LLM) applications that facilitate planning, branching, tool utilization, memory management, and controlled execution.
This instructor-led, live training—available online or on-site—is tailored for beginner-level developers, prompt engineers, and data practitioners aiming to design and build reliable, multi-step LLM workflows using LangGraph.
Upon completing this training, participants will be capable of:
- Explaining fundamental LangGraph concepts (nodes, edges, state) and understanding their appropriate use cases.
- Constructing prompt chains that branch, invoke tools, and maintain context memory.
- Integrating retrieval mechanisms and external APIs into graph-based workflows.
- Testing, debugging, and evaluating LangGraph applications to ensure reliability and safety.
Course Format
- Interactive lectures paired with facilitated discussions.
- Guided labs and code walkthroughs conducted within a sandbox environment.
- Scenario-based exercises focusing on design, testing, and evaluation.
Course Customization Options
- To request customized training for this course, please contact us to arrange details.
LangGraph in Healthcare: Workflow Orchestration for Regulated Environments
35 HoursLangGraph empowers stateful, multi-actor workflows driven by LLMs, offering precise control over execution paths and state persistence. For the healthcare sector, these capabilities are essential for ensuring compliance, enabling interoperability, and developing decision-support systems that seamlessly integrate with medical workflows.
This instructor-led, live training—available either online or on-site—is designed for intermediate to advanced professionals looking to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.
Upon completion of this training, participants will be capable of:
- Designing healthcare-specific LangGraph workflows that prioritize compliance and auditability.
- Integrating LangGraph applications with medical ontologies and standards (FHIR, SNOMED CT, ICD).
- Applying best practices for reliability, traceability, and explainability within sensitive environments.
- Deploying, monitoring, and validating LangGraph applications in healthcare production settings.
Format of the Course
- Interactive lectures and discussions.
- Hands-on exercises based on real-world case studies.
- Implementation practice within a live-lab environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
LangGraph for Legal Applications
35 HoursLangGraph serves as a framework for developing stateful, multi-actor LLM applications through composable graphs that maintain persistent state and offer precise execution control.
This instructor-led live training, available online or onsite, targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based legal solutions with robust compliance, traceability, and governance controls.
Upon completion, participants will be capable of:
- Designing legal-specific LangGraph workflows that ensure auditability and regulatory compliance.
- Integrating legal ontologies and document standards into graph state and processing logic.
- Implementing guardrails, human-in-the-loop approvals, and traceable decision paths.
- Deploying, monitoring, and maintaining LangGraph services in production environments with observability and cost management.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical practice.
- Hands-on implementation within a live-lab environment.
Customization Options
- For customized training requests, please contact us to arrange.
Building Dynamic Workflows with LangGraph and LLM Agents
14 HoursLangGraph serves as a framework for constructing graph-structured workflows involving Large Language Models (LLMs), enabling features such as branching, tool integration, memory management, and controlled execution.
This instructor-led live training, available either online or onsite, targets intermediate engineers and product teams looking to merge LangGraph’s graph logic with LLM agent loops. The goal is to build dynamic, context-aware applications, including customer support bots, decision trees, and information retrieval systems.
Upon completing 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 systems, APIs, and structured outputs into agent loops.
- Evaluating, monitoring, and securing agent behavior to ensure reliability and safety.
Course Format
- Interactive lectures and guided discussions.
- Hands-on labs and code walkthroughs within a sandbox environment.
- Scenario-based design exercises and peer reviews.
Customization Options
- To request a customized training for this course, please contact us to make arrangements.
LangGraph 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 HoursLe Chat Enterprise is a private ChatOps solution that provides secure, customizable, and governed conversational AI capabilities for organizations, with support for RBAC, SSO, connectors, and enterprise app integrations.
This instructor-led, live training (online or onsite) is aimed at intermediate-level product managers, IT leads, solution engineers, and security/compliance teams who wish 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.
- 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.
Cost-Effective LLM Architectures: Mistral at Scale (Performance / Cost Engineering)
14 HoursMistral is a family of high-performance large language models specifically optimized for cost-efficient production deployment at scale.
This instructor-led training, available online or onsite, targets advanced infrastructure engineers, cloud architects, and MLOps leaders seeking to design, deploy, and optimize Mistral-based architectures for maximum throughput and minimal cost.
Upon completion of this training, participants will be equipped to:
- Implement scalable deployment patterns for Mistral Medium 3.
- Apply batching, quantization, and efficient serving strategies.
- Optimize inference costs while maintaining performance.
- Design production-ready serving topologies for enterprise workloads.
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.
Productizing Conversational Assistants with Mistral Connectors & Integrations
14 HoursMistral AI offers an open-source AI platform that empowers teams to develop and embed conversational assistants into both enterprise operations and customer-facing workflows.
This instructor-led live training, available either online or onsite, targets beginner to intermediate product managers, full-stack developers, and integration engineers looking to design, integrate, and commercialize conversational assistants using Mistral connectors and integrations.
Upon completion of this training, participants will be able to:
- Connect Mistral conversational models with enterprise and SaaS connectors.
- Implement retrieval-augmented generation (RAG) to ensure grounded responses.
- Create UX patterns for both internal and external chat assistants.
- Deploy assistants into product workflows for practical, real-world applications.
Course Format
- Interactive lectures and discussions.
- Practical integration exercises.
- Live lab sessions for developing conversational assistants.
Course Customization Options
- To arrange a customized training session for this course, please contact us.
Enterprise-Grade Deployments with Mistral Medium 3
14 HoursMistral Medium 3 is a high-performance, multimodal large language model engineered for production-grade deployment within enterprise environments.
This instructor-led live training, available either online or on-site, targets intermediate to advanced AI/ML engineers, platform architects, and MLOps teams looking to deploy, optimize, and secure Mistral Medium 3 for enterprise use cases.
Upon completing this training, participants will be able to:
- Deploy Mistral Medium 3 via API and self-hosted solutions.
- Optimize inference performance and associated costs.
- Implement multimodal use cases utilizing Mistral Medium 3.
- Apply security and compliance best practices suitable for enterprise environments.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice sessions.
- Hands-on implementation within a live lab environment.
Customization Options
- To request customized training for this course, please contact us to arrange details.
Mistral for Responsible AI: Privacy, Data Residency & Enterprise Controls
14 HoursMistral AI offers an open, enterprise-ready AI platform designed to facilitate secure, compliant, and responsible AI deployment.
This instructor-led training, available online or onsite, is designed for intermediate-level compliance leads, security architects, and legal/operations stakeholders seeking to implement responsible AI practices with Mistral by leveraging its privacy, data residency, and enterprise control capabilities.
Upon completing this training, participants will be able to:
- Deploy privacy-preserving techniques within Mistral environments.
- Apply data residency strategies to satisfy regulatory requirements.
- Establish enterprise-grade controls, including RBAC, SSO, and audit logging.
- Evaluate vendor and deployment options to ensure compliance alignment.
Course Format
- Interactive lectures and discussions.
- Case studies and exercises focused on compliance.
- Hands-on implementation of enterprise AI controls.
Customization Options
- To request a customized version of this course, please contact us to arrange.
Multimodal Applications with Mistral Models (Vision, OCR, & Document Understanding)
14 HoursMistral models represent open-source AI technologies that are expanding into multimodal workflows, effectively supporting both linguistic and visual tasks for enterprise and research initiatives.
This live training, led by an instructor and available either online or on-site, is designed for intermediate-level machine learning researchers, applied engineers, and product teams interested in creating multimodal applications using Mistral models. The curriculum includes the development of OCR and document understanding pipelines.
Upon completion of this training, participants will be able to:
- Configure and set up Mistral models for multimodal tasks.
- Implement OCR workflows and seamlessly integrate them with NLP pipelines.
- Design document understanding applications tailored to enterprise use cases.
- Develop functionalities for vision-text search and assistive user interfaces.
Course Format
- Interactive lectures and discussions.
- Practical coding exercises.
- Live laboratory sessions for implementing multimodal pipelines.
Customization Options
- To request tailored training for this course, please contact us to make arrangements.
