Text Data Analysis and Insights Training

InfoShare Academy is a leading IT academy offering comprehensive educational programs in new technologies for companies. Since 2015, we have been supporting organizations in developing technology teams through dedicated courses in Machine Learning, DevOps, Data Engineering, Python, UX/UI Design, AWS, and Kubernetes. Our training is based on practical skills and real business cases. We collaborate with over 300 industry practitioners, ensuring that our programs are tailored to current market needs. We specialize in reskilling and upskilling employees. With us, you will build effective teams implementing new technologies that will accelerate innovation and strengthen your company's competitiveness in the market. Check out our training offerings designed for companies, created to enhance your employees' competencies in the IT field.

Advanced two-day practical workshops that will introduce you to the world of natural language processing (NLP) as a powerful analytical tool for business. The training combines solid theoretical knowledge with intensive workshop sessions, demonstrating how to transform raw text data into valuable business insights using Python.

• Business analysts looking to expand their skills in advanced data analysis
• Business intelligence specialists interested in modern knowledge extraction methods
• Product managers wanting to better understand analytical tools
• Programmers wishing to learn practical applications of NLP in business
• Consultants and specialists from sectors: marketing, finance, customer service

• You will learn:
• Advanced text processing techniques using Python
• Implementation of NLP models in business processes
• Automatic extraction of key information from documents
• Practical strategies for transforming text data into measurable business indicators

• Day 1: Fundamentals of NLP and Data Preparation
  1.1. Module 1: Introduction to NLP in Business

  • Key concepts of natural language processing

  • Practical NLP application scenarios in various industries
    1.2. Module 2: Setting up the programming environment

  • Configuring the Python environment for NLP

  • Installing and managing libraries: NLTK, spaCy, Gensim

  • Setting up virtual programming environments
    1.3. Module 3: Preprocessing text data

  • Techniques for cleaning and normalizing text

  • Tokenization, stopword removal, lemmatization

  • Practical exercises in transforming raw text data
    1.4. Module 4: Information extraction

  • Named Entity Recognition (NER)

  • Identifying key phrases and relationships

  • Practical scenarios for data extraction from business documents

• Day 2: Advanced NLP Techniques
  2.1. Module 5: Advanced NLP Models

  • Introduction to neural networks

  • Transformers – architecture and applications

  • Practical applications of BERT, GPT models in business analysis
    2.2. Module 6: Text Classification

  • Text classification algorithms

  • Building machine learning models for document categorization

  • Workshop: document classification project
    2.3. Module 7: Sentiment Analysis

  • Building basic sentiment models

  • Customer opinion analysis in a business context

  • Workshop: sentiment analysis project for a selected industry
    2.4. Module 8: Final Project

  • Independently creating a mini NLP project

  • Presentation of solutions

  • Individual consultations and feedback

16 h/2 days

• Certificate of completion
• Monthly access to the training recording (in case of online format)
• Customization of the training program to client needs