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Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.
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Allan BusiDec 1, 20269 min readOklahoma CityThe Training: Mastering Gensim: Thematic Analysis and Modeling of Texts training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.
The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.
To ensure the quality of the Training: Mastering Gensim: Thematic Analysis and Modeling of Texts training, Learni provides the following teaching resources:
For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.
The assessment of skills acquired during the Training: Mastering Gensim: Thematic Analysis and Modeling of Texts training is carried out through:
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Learni training programs are available for inter-company and intra-company settings, both in-person and remote. Registration is possible up to 48 business hours before the start of training. Our programs are eligible for OPCO, Pôle emploi, and FNE-Formation funding. Contact us to discuss your training project and funding possibilities.
Presentation of Gensim in NLP, installation, general architecture. Importing datasets, initial manipulations: loading, cleaning, tokenization, stopword removal, lemmatization. Building a dictionary and creating a corpus. Practical exercises on preparing textual datasets.
Presentation of thematic analysis (topic modeling), theory on LDA (Latent Dirichlet Allocation). Step-by-step implementation of an LDA model with Gensim: parameter selection, model training, exploration and visualization of topics. Practices on various datasets, introduction to the coherence method for evaluating the relevance of extracted topics.
Introduction to Word2Vec and Doc2Vec. Creating word and document vector representation models with Gensim, training and using them for semantic similarity. Building a complete thematic analysis pipeline. Hyperparameter optimization, advanced evaluation, exporting results for further analyses or visualizations. End-of-course workshop: automatic extraction and analysis of themes from a sectoral corpus.
8 participants max.
$2,420 / per person
2 days
distancielTarget audience
Data scientists, analysts, researchers, natural language processing (NLP) professionals, and developers seeking to automate in-depth text analysis.
Prerequisites
Mastery of Python, basics in text processing, general understanding of machine learning.
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