Online Natural Language Processing (NLP) Training in Tunisia

This instructor-led, live training in Tunisia (online or onsite) is aimed at intermediate-level to advanced-level AI researchers, data scientists, and developers who wish to understand, fine-tune, and implement Meta AI's Large Language Models for various NLP applications.

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

• Understand the architecture and functioning of Meta AI's Large Language Models.
• Set up and fine-tune Meta AI LLMs for specific use cases.
• Implement LLM-based applications such as text summarization, chatbots, and sentiment analysis.
• Optimize and deploy large language models efficiently.

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

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

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

This instructor-led, live training in Tunisia (online or onsite) is aimed at beginner-level to intermediate-level customer support and IT professionals who wish to implement LLMs to create responsive and intelligent customer support chatbots.

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

• Understand the fundamentals and architecture of Large Language Models (LLMs).
• Design and integrate LLMs into customer support systems.
• Enhance 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 Tunisia (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.

This instructor-led, live training in Tunisia (online or onsite) is aimed at beginner-level business analysts and automation engineers who wish to understand how to use LangChain and APIs for automating repetitive tasks and workflows.

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

• Understand the basics of API integration with LangChain.
• Automate repetitive workflows using LangChain and Python.
• Utilize LangChain to connect various APIs for efficient business processes.
• Create and automate custom workflows using APIs and LangChain’s automation capabilities.

This instructor-led, live training in Tunisia (online or onsite) is aimed at intermediate-level public sector professionals who wish to use Gemini to generate high-quality content, assist with research, and improve productivity through more advanced AI interactions.

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

• Craft more effective and tailored prompts for specific use cases.
• Generate original and creative content using Gemini.
• Summarize and compare complex information with precision.
• Use Gemini for brainstorming, planning, and organizing ideas efficiently.

This instructor-led, live training in Tunisia (online or onsite) is aimed at intermediate-level professionals who wish to deepen their understanding of conversational agents and apply LangChain to real-world use cases.

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

• Understand the fundamentals of LangChain and its application in building conversational agents.
• Develop and deploy conversational agents using LangChain.
• Integrate conversational agents with APIs and external services.
• Apply Natural Language Processing (NLP) techniques to improve the performance of conversational agents.

This instructor-led, live training in Tunisia (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 Tunisia (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.

This instructor-led, live training in Tunisia (online or onsite) is aimed at intermediate-level professionals who wish to deepen their expertise in modern NLU techniques.

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

• Implement advanced NLU techniques for AI systems.
• Leverage deep learning models for semantic understanding.
• Perform intent recognition and classification in complex applications.
• Utilize state-of-the-art tools like Hugging Face Transformers for NLU tasks.

This instructor-led, live training in Tunisia (online or onsite) is aimed at beginner-level professionals who wish to integrate Claude AI into their daily workflows to improve efficiency and automation.

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

• Use Claude AI for automating repetitive tasks and streamlining workflows.
• Enhance personal and team productivity using AI-powered automation.
• Integrate Claude AI with existing business tools and platforms.
• Optimize AI-driven decision-making and task management.

This instructor-led, live training in Tunisia (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to customize pre-trained models for specific tasks and datasets.

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

• Understand 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.

This instructor-led, live training in Tunisia (online or onsite) is aimed at intermediate-level customer service professionals who wish to implement Google Gemini AI in their customer service operations.

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

• Understand the impact of AI on customer service.
• Set up Google Gemini AI to automate and personalize customer interactions.
• Utilize text-to-text and image-to-text transformations to improve service efficiency.
• Develop AI-driven strategies for real-time customer feedback analysis.
• Explore advanced features to create a seamless customer service experience.

This instructor-led, live training in Tunisia (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 Tunisia (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 Tunisia (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.

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 introduces linguists or programmers to NLP in Python. During this course we will mostly use nltk.org (Natural Language Tool Kit), but also we will use other libraries relevant and useful for NLP. At the moment we can conduct this course in Python 2.x or Python 3.x. Examples are in English or Mandarin (普通话). Other languages can be also made available if agreed before booking.

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.

Audience

• Network engineers
• Network operations personnel
• Telecom technical managers

Format of the course

• Part lecture, part discussion, hands-on exercises

This course is intended for developers and data scientists who want to understand and implement artificial intelligence in their applications. Special focus is placed on data analytics, distributed AI, 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 Tunisia, 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.

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

By the end of the training the delegates are expected to be sufficiently equipped with the essential python concepts and should be able to sufficiently use NLTK to implement most of the NLP and ML based operations. The training is aimed at giving not just an executional knowledge but also the logical and operational knowledge of the technology therein.

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/

This instructor-led, live training in Tunisia (online or onsite) is aimed at data scientists and developers who wish to use TextBlob to implement and simplify NLP tasks, such as sentiment analysis, spelling corrections, text classification modeling, etc.

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

• Set up the necessary development environment to start implementing NLP tasks with TextBlob.
• Understand the features, architecture, and advantages of TextBlob.
• Learn how to build text classification systems using TextBlob.
• Perform common NLP tasks (Tokenization, WordNet, Sentiment analysis, Spelling correction, etc.)
• Execute advanced implementations with simple APIs and a few lines of codes.

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.
• Evaluate three Python summarization libraries: sumy 0.7.0, pysummarization 1.0.4, readless 1.0.17

Audience

• Developers
• Data Scientists

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

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