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    Oil and Gas Training Courses SLB NEXT

    Text Mining And Machine Learning - (Remote Instructor-Led Series)

    This course introduces essential concepts of natural language processing (NLP) with emphasis on the methods to extract actionable insights from unstructured text data. The topics include text clustering and classification, similarity analysis, text summarization and topic modeling.

    After completing this course you will be able to:

    • Understand the basics of natural language processing and identify the challenges and constraints of mining text data;
    • Apply data preprocessing techniques to address challenges specific to text data, including structuring unstructured data, and dimensionality reduction according to linguistic context;
    • Build and evaluate NLP models using supervised and unsupervised machine learning techniques specific to text mining;
    • Apply state-of-the-art NLP frameworks such as NLTK, Gensim and spaCy for designing and evaluating the NLP models including sentiment analysis, text summarization and topic modeling.
    This is a practical course with 50% of the time dedicated to hands-on sessions using the Data Science profile in Schlumberger's DELFI Cognitive E&P environment and / or Orange Open Source Data Mining Software suite which is based on visual programming. Exercises based on Python programming language and  NLP frameworks such as NLTK, Gensim and spaCy may also be incorporated. Hands-on sessions will all be based on oil and gas datasets.

    This course is delivered entirely online, for 4 hours each day.


    Natural Language Processing Basics

    Introduction to Python for Natural Language Processing

    Text Processing and Feature Engineering

    Text Classification

    Sentiment Analysis

    Text Summarization

    Topic Modeling

    Text Similarity and Clustering

    Geoscientists, Engineers, IT professionals and aspiring Citizen Data Scientists working in the oil and gas industry who want to be introduced to text mining techniques.

    • Natural Language Processing Basics
    • Introduction to Python for Natural Language Processing
    • Text Processing and Feature Engineering
    • Text Classification
    • Sentiment Analysis
    • Text Summarization
    • Topic Modeling
    • Text Similarity and Clustering

    Participants should have completed a foundational course on data analytics, such as NExT Fundamentals of Data Analytics, NExT Essential Data Science for Petroleum Geoscientists and Engineers, or an equivalent course. Exposure to Python programming is also preferred.

    Currently there are no scheduled classes for this course.

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