Natural Language Processing in Marketing
( 30 Modules )

Module #1
Introduction to NLP in Marketing
Overview of NLP, its applications in marketing, and the benefits of using NLP in marketing

Module #2
NLP Fundamentals
Basic concepts of NLP, including tokenization, stemming, and entity recognition

Module #3
Text Preprocessing
Steps involved in preprocessing text data for NLP, including tokenization, stopword removal, and lemmitization

Module #4
Word Embeddings
Introduction to word embeddings, including Word2Vec and GloVe, and their applications in marketing

Module #5
Sentiment Analysis
Introduction to sentiment analysis, including its applications in marketing and customer service

Module #6
Sentiment Analysis Tools and Techniques
Hands-on experience with sentiment analysis tools and techniques, including NLTK and TextBlob

Module #7
Topic Modeling
Introduction to topic modeling, including Latent Dirichlet Allocation (LDA) and Non-Negative Matrix Factorization (NMF)

Module #8
Topic Modeling Applications in Marketing
Applications of topic modeling in marketing, including customer segmentation and product categorization

Module #9
Named Entity Recognition (NER)
Introduction to NER, including its applications in marketing and customer service

Module #10
NER Tools and Techniques
Hands-on experience with NER tools and techniques, including spaCy and Stanford CoreNLP

Module #11
Part-of-Speech (POS) Tagging
Introduction to POS tagging, including its applications in marketing and language understanding

Module #12
Dependency Parsing
Introduction to dependency parsing, including its applications in marketing and language understanding

Module #13
Language Models
Introduction to language models, including Markov models and recurrent neural networks (RNNs)

Module #14
Language Model Applications in Marketing
Applications of language models in marketing, including chatbots and content generation

Module #15
Conversational AI
Introduction to conversational AI, including chatbots and voice assistants

Module #16
Conversational AI in Marketing
Applications of conversational AI in marketing, including customer service and lead generation

Module #17
Social Media Analytics
Introduction to social media analytics, including sentiment analysis and topic modeling on social media data

Module #18
Case Studies in NLP in Marketing
Real-world case studies of companies using NLP in marketing, including successes and challenges

Module #19
Ethical Considerations in NLP
Ethical considerations in using NLP in marketing, including bias and transparency

Module #20
NLP Tools and Platforms for Marketing
Overview of NLP tools and platforms for marketing, including IBM Watson, Google Cloud NLP, and MeaningCloud

Module #21
Building an NLP Project in Marketing
Hands-on experience building an NLP project in marketing, including data preprocessing and model training

Module #22
Evaluating NLP Models in Marketing
Metrics and techniques for evaluating NLP models in marketing, including precision, recall, and F1 score

Module #23
NLP for Customer Service
Applications of NLP in customer service, including chatbots and sentiment analysis

Module #24
NLP for Content Generation
Applications of NLP in content generation, including language models and text summarization

Module #25
NLP for Social Media Monitoring
Applications of NLP in social media monitoring, including sentiment analysis and topic modeling

Module #26
NLP for Market Research
Applications of NLP in market research, including customer feedback analysis and competitor analysis

Module #27
NLP for Personalization
Applications of NLP in personalization, including customer profiling and product recommendation

Module #28
NLP for Influencer Identification
Applications of NLP in influencer identification, including social media analytics and topic modeling

Module #29
NLP for Competitive Intelligence
Applications of NLP in competitive intelligence, including competitor analysis and market trend analysis

Module #30
Course Wrap-Up & Conclusion
Planning next steps in Natural Language Processing in Marketing career

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Natural Language Processing in Marketing ( 30 Modules )

Natural Language Processing in Marketing
( 30 Modules )