Online or onsite, instructor-led live Natural Language Processing (NLP) training courses demonstrate through interactive discussion and hands-on practice how to extract insights and meaning from this data. Utilizing different programming languages such as Python and R and Natural Language Processing (NLP) libraries, our trainings combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to help participants understand the meaning behind text data. NLP trainings walk participants step-by-step through the process of evaluating and applying the right algorithms to analyze data and report on its significance.
NLP training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Natural Language Processing (NLP) training can be carried out locally on customer premises in Tunis or in NobleProg corporate training centers in Tunis.
NobleProg -- Your Local Training Provider
North Urban Centre
Lot B17, Tunis, tunisia
Location close to the airport in Tin, this stylish venue offers a relaxed and comfortable environment, conducive to a great learning experience.
This modern venue provide everything you need, while Tunis’ UNESCO monuments create a memorable atmosphere for any event.
This instructor-led, live training in Tunis (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 Tunis (online or onsite) is aimed at intermediate-level data scientists and AI engineers who wish to fine-tune large language models more affordably and efficiently using methods like LoRA, Adapter Tuning, and Prefix Tuning.
By the end of this training, participants will be able to:
Understand the theory behind parameter-efficient fine-tuning approaches.
Implement LoRA, Adapter Tuning, and Prefix Tuning using Hugging Face PEFT.
Compare performance and cost trade-offs of PEFT methods vs. full fine-tuning.
Deploy and scale fine-tuned LLMs with reduced compute and storage requirements.
This instructor-led, live training in Tunis (online or onsite) is aimed at intermediate-level business professionals and data analysts who wish to harness the power of LLMs for extracting business insights.
By the end 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.
Mistral AI is a powerful family of open-source and enterprise-ready AI models for language, multimodal, and agentic applications.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to build, deploy, and manage AI agents using Mistral’s Medium 3, Le Chat Enterprise, and Devstral models.
By the end of this training, participants will be able to:
Understand the architecture and capabilities of Mistral Medium 3, Le Chat Enterprise, and Devstral.
Design and implement AI agents leveraging Mistral models for enterprise and developer use cases.
Integrate coding systems, connectors, and enterprise data into agent workflows.
Optimize performance, cost, and compliance for Mistral-powered agents.
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.
Ollama is a platform for running large language and multimodal models locally and at scale.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level engineers who wish 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) provides powerful deployment and optimization tools for real-time AI applications in computer vision and NLP, especially on Huawei Ascend hardware.
This instructor-led, live training (online or onsite) is aimed at intermediate-level AI practitioners who wish to build, deploy, and optimize vision and language models using the CANN SDK for production use cases.
By the end of this training, participants will be able to:
Deploy and optimize CV and NLP models using CANN and AscendCL.
Use CANN tools to convert models and integrate them into live pipelines.
Optimize inference performance for tasks like detection, classification, and sentiment analysis.
Build real-time CV/NLP pipelines for edge or cloud-based deployment scenarios.
Format of the Course
Interactive lecture and demonstration.
Hands-on lab with model deployment and performance profiling.
Live pipeline design using real CV and NLP use cases.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
Vertex AI provides powerful tools for building multimodal LLM workflows that integrate text, audio, and image data into a single pipeline. With long context window support and Gemini API parameters, it enables advanced applications in planning, reasoning, and cross-modal intelligence.
This instructor-led, live training (online or onsite) is aimed at intermediate to advanced-level practitioners who wish to design, build, and optimize multimodal AI workflows in Vertex AI.
By the end of this training, participants will be able to:
Leverage Gemini models for multimodal inputs and outputs.
Implement long-context workflows for complex reasoning.
Design pipelines that integrate text, audio, and image analysis.
Optimize Gemini API parameters for performance and cost efficiency.
Format of the Course
Interactive lecture and discussion.
Hands-on labs with multimodal workflows.
Project-based exercises for applied multimodal use cases.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
Ollama is a platform that enables running and fine-tuning large language and multimodal models locally.
This instructor-led, live training (online or onsite) is aimed at advanced-level ML engineers, AI researchers, and product developers who wish to build and deploy multimodal applications with Ollama.
By the end of this training, participants will be able to:
Set up and run multimodal models with Ollama.
Integrate text, image, and audio inputs for real-world applications.
Build document understanding and visual QA systems.
Develop multimodal agents capable of reasoning across modalities.
Format of the Course
Interactive lecture and discussion.
Hands-on practice with real multimodal datasets.
Live-lab implementation of multimodal pipelines using Ollama.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
This instructor-led, live training in Tunis (online or onsite) is aimed at intermediate-level data scientists and developers who wish to apply NLP techniques using Python in Google Colab.
By the end of this training, participants will be able to:
Understand the core concepts of natural language processing.
Preprocess and clean text data for NLP tasks.
Perform sentiment analysis using NLTK and SpaCy libraries.
Work with text data using Google Colab for scalable and collaborative development.
Advanced Ollama Model Debugging & Evaluation is an in-depth course focused on diagnosing, testing, and measuring model behavior when running local or private Ollama deployments.
This instructor-led, live training (online or onsite) is aimed at advanced-level AI engineers, ML Ops professionals, and QA practitioners who wish to ensure reliability, fidelity, and operational readiness of Ollama-based models in production.
By the end of this training, participants will be able to:
Perform systematic debugging of Ollama-hosted models and reproduce failure modes reliably.
Design and execute robust evaluation pipelines with quantitative and qualitative metrics.
Implement observability (logs, traces, metrics) to monitor model health and drift.
Automate testing, validation, and regression checks integrated into CI/CD pipelines.
Format of the Course
Interactive lecture and discussion.
Hands-on labs and debugging exercises using Ollama deployments.
Case studies, group troubleshooting sessions, and automation workshops.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
This instructor-led, live training in Tunis (online or onsite) is aimed at intermediate-level researchers, analysts, and knowledge workers who want to leverage Claude AI for processing large amounts of data, synthesizing information, and automating research tasks.
By the end of this training, participants will be able to:
Use Claude AI for literature reviews and research synthesis.
Summarize reports, research papers, and long-form documents.
Extract key insights and trends from structured and unstructured data.
Integrate Claude AI into research and knowledge management workflows.
This instructor-led, live training in Tunis (online or onsite) is aimed at beginner-level to intermediate-level content creators, writers, and marketers who want to leverage Claude AI for content generation, editing, and summarization to enhance blogs, reports, and marketing materials.
By the end of this training, participants will be able to:
Use Claude AI for content brainstorming and idea expansion.
Enhance writing with AI-assisted editing and proofreading.
Generate summaries for long-form content and reports.
Automate marketing copy creation for different platforms.
This instructor-led, live training in Tunis (online or onsite) is aimed at advanced-level professionals who wish to fine-tune and customize AI models on Ollama for enhanced performance and domain-specific applications.
By the end of this training, participants will be able to:
Set up an efficient environment for fine-tuning AI models on Ollama.
Prepare datasets for supervised fine-tuning and reinforcement learning.
Optimize AI models for performance, accuracy, and efficiency.
Deploy customized models in production environments.
Evaluate model improvements and ensure robustness.
Mistral is a high-performance family of large language models optimized for cost-effective production deployment at scale.
This instructor-led, live training (online or onsite) is aimed at advanced-level infrastructure engineers, cloud architects, and MLOps leads who wish to design, deploy, and optimize Mistral-based architectures for maximum throughput and minimum cost.
By the end of this training, participants will be able 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.
This instructor-led, live training in Tunis (online or onsite) is aimed at intermediate-level data scientists, AI developers, and AI enthusiasts who wish to use LLMs to perform various NLP tasks and create novel and diverse content for different purposes.
By the end of this training, participants will be able to:
Establish a development environment with LLMs and essential tools.
Expertly perform NLU and NLI tasks with LLMs.
Extract, infer, and utilize knowledge graphs effectively.
Generate and manage dialogues using LLMs for conversational applications.
Evaluate content quality and diversity generated by LLMs and generative AI.
Apply ethical principles, ensuring fairness and responsible use of LLMs.
This instructor-led, live training in Tunis (online or onsite) is aimed at intermediate-level professionals who wish to enhance their NLP projects through the effective fine-tuning of pre-trained language models.
By the end of this training, participants will be able to:
Understand the fundamentals of fine-tuning for NLP tasks.
Fine-tune pre-trained models such as GPT, BERT, and T5 for specific NLP applications.
Optimize hyperparameters for improved model performance.
Evaluate and deploy fine-tuned models in real-world scenarios.
This instructor-led, live training in (online or onsite) is aimed at data scientists, machine learning engineers, NLP researchers, and AI enthusiasts who wish to understand the inner workings of GPT models, explore the capabilities of GPT-3 and GPT-4, and learn how to leverage these models for their NLP tasks.
By the end of this training, participants will be able to:
Understand the key concepts and principles behind Generative Pre-trained Transformers.
Comprehend the architecture and training process of GPT models.
Utilize GPT-3 for tasks such as text generation, completion, and translation.
Explore the latest advancements in GPT-4 and its potential applications.
Apply GPT models to their own NLP projects and tasks.
This instructor-led, live training in Tunis (online or onsite) is aimed at beginner-level business professionals, customer support teams, and tech enthusiasts who wish to understand the fundamentals of Claude AI and leverage it for business applications.
By the end of this training, participants will be able to:
Understand Claude AI’s capabilities and use cases.
Set up and interact with Claude AI effectively.
Automate business workflows with conversational AI.
Enhance customer engagement and support using AI-driven solutions.
This instructor-led, live training in Tunis (online or onsite) is aimed at beginner-level professionals who wish to install, configure, and use Ollama for running AI models on their local machines.
By the end of this training, participants will be able to:
Understand the fundamentals of Ollama and its capabilities.
Set up Ollama for running local AI models.
Deploy and interact with LLMs using Ollama.
Optimize performance and resource usage for AI workloads.
Explore use cases for local AI deployment in various industries.
It is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data.
This instructor-led, live course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements.
By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance.
Format of the Course
Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
This course has been created for managers, solutions architects, innovation officers, CTOs, software architects and anyone who is interested in an overview of applied artificial intelligence and the nearest forecast for its development.
AI is a collection of technologies for building intelligent systems capable of understanding data and the activities surrounding the data to make "intelligent decisions". For Telecom providers, building applications and services that make use of AI could open the door for improved operations and servicing in areas such as maintenance and network optimization.
In this course we examine the various technologies that make up AI and the skill sets required to put them to use. Throughout the course, we examine AI's specific applications within the Telecom industry.
This course is aimed at developers and data scientists who wish to understand and implement artificial intelligence in their applications. Special focus will be given to data analysis, distributed artificial intelligence, and natural language processing.
ChatBots are computer programs that automatically simulate human responses via chat interfaces. ChatBots help organizations maximize their operations efficiency by providing easier and faster options for their user interactions.
In this instructor-led, live training, participants will learn how to build chatbots in Python.
By the end of this training, participants will be able to:
Understand the fundamentals of building chatbots
Build, test, deploy, and troubleshoot various chatbots using Python
Audience
Developers
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
Note
To request a customized training for this course, please contact us to arrange.
In this instructor-led, live training in Tunis, participants will learn to use Python libraries for NLP as they create an application that processes a set of pictures and generates captions.
By the end of this training, participants will be able to:
Design and code DL for NLP using Python libraries.
Create Python code that reads a substantially huge collection of pictures and generates keywords.
Create Python Code that generates captions from the detected keywords.
In this instructor-led, live training in Tunis, participants will learn how to use Python to produce high-quality natural language text by building their own NLG system from scratch. Case studies will also be examined and the relevant concepts will be applied to live lab projects for generating content.
By the end of this training, participants will be able to:
Use NLG to automatically generate content for various industries, from journalism, to real estate, to weather and sports reporting.
Select and organize source content, plan sentences, and prepare a system for automatic generation of original content.
Understand the NLG pipeline and apply the right techniques at each stage.
Understand the architecture of a Natural Language Generation (NLG) system.
Implement the most suitable algorithms and models for analysis and ordering.
Pull data from publicly available data sources as well as curated databases to use as material for generated text.
Replace manual and laborious writing processes with computer-generated, automated content creation.
This classroom based training session will explore NLP techniques in conjunction with the application of AI and Robotics in business. Delegates will undertake computer based examples and case study solving exercises using Python
This instructor-led, live training (online or onsite) is aimed at developers and data scientists who wish to use spaCy to process very large volumes of text to find patterns and gain insights.
By the end of this training, participants will be able to:
Install and configure spaCy.
Understand spaCy's approach to Natural Language Processing (NLP).
Extract patterns and obtain business insights from large-scale data sources.
Integrate the spaCy library with existing web and legacy applications.
Deploy spaCy to live production environments to predict human behavior.
Use spaCy to pre-process text for Deep Learning
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.
To learn more about spaCy, please visit: https://spacy.io/
In Python Machine Learning, the Text Summarization feature is able to read the input text and produce a text summary. This capability is available from the command-line or as a Python API/Library. One exciting application is the rapid creation of executive summaries; this is particularly useful for organizations that need to review large bodies of text data before generating reports and presentations.
In this instructor-led, live training, participants will learn to use Python to create a simple application that auto-generates a summary of input text.
By the end of this training, participants will be able to:
Use a command-line tool that summarizes text.
Design and create Text Summarization code using Python libraries.
TensorFlow™ is an open source software library for numerical computation using data flow graphs.
SyntaxNet is a neural-network Natural Language Processing framework for TensorFlow.
Word2Vec is used for learning vector representations of words, called "word embeddings". Word2vec is a particularly computationally-efficient predictive model for learning word embeddings from raw text. It comes in two flavors, the Continuous Bag-of-Words model (CBOW) and the Skip-Gram model (Chapter 3.1 and 3.2 in Mikolov et al.).
Used in tandem, SyntaxNet and Word2Vec allows users to generate Learned Embedding models from Natural Language input.
Audience
This course is targeted at Developers and engineers who intend to work with SyntaxNet and Word2Vec models in their TensorFlow graphs.
After completing this course, delegates will:
understand TensorFlow’s structure and deployment mechanisms
be able to carry out installation / production environment / architecture tasks and configuration
be able to assess code quality, perform debugging, monitoring
be able to implement advanced production like training models, embedding terms, building graphs and logging
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Testimonials (4)
prompts engineering part
Michal - GE HealthCare
Course - Generative AI with Large Language Models (LLMs)
Hunter is fabulous, very engaging, extremely knowledgeable and personable. Very well done.
Rick Johnson - Laramie County Community College
Course - Artificial Intelligence (AI) Overview
Organization, adhering to the proposed agenda, the trainer's vast knowledge in this subject
Ali Kattan - TWPI
Course - Natural Language Processing with TensorFlow
This is one of the best hands-on with exercises programming courses I have ever taken.
Laura Kahn
Course - Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
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