Natural Language Processing With Python
Instructor-led training in Natural Language Processing With Python. Delivered live online by senior practitioners, with hands-on labs and a final assessment. Includes an Skilvi course-completion certificate.
Overview
This course provides an in-depth exploration of Natural Language Processing (NLP) using Python, covering essential techniques and tools to analyze and interpret human language data. Understanding NLP is crucial in today's data-driven world, as it enables applications ranging from chatbots to sentiment analysis.
What you'll learn
- You will be able to implement text preprocessing techniques for NLP tasks.
- You will be able to build and evaluate machine learning models for text classification.
- You will be able to utilize libraries such as NLTK and SpaCy for language processing.
- You will be able to apply sentiment analysis to extract insights from textual data.
- You will be able to create and manipulate word embeddings for improved NLP performance.
- You will be able to develop and deploy a simple chatbot using NLP techniques.
Curriculum
7 modules · outline is indicative and can be tailored to your team.
1Introduction to Natural Language Processing
- Overview of NLP and its importance
- Applications of NLP in various industries
- Introduction to Python libraries for NLP
2Text Preprocessing
- Tokenization and normalization techniques
- Removing stop words and stemming
- Handling punctuation and special characters
3Text Representation
- Bag of Words model
- TF-IDF vectorization
- Word embeddings and their applications
4Machine Learning for NLP
- Supervised vs. unsupervised learning in NLP
- Building and evaluating classification models
- Using scikit-learn for NLP tasks
5Sentiment Analysis
- Understanding sentiment analysis concepts
- Implementing sentiment analysis with Python
- Evaluating sentiment analysis models
6Building Chatbots
- Introduction to chatbot architecture
- Using NLP for intent recognition
- Deploying a simple chatbot application
7Advanced NLP Techniques
- Introduction to deep learning for NLP
- Using recurrent neural networks (RNNs)
- Exploring transformer models and BERT
Prerequisites
Basic knowledge of Python programming is recommended.
Who should attend
This course is designed for data analysts, software developers, and anyone interested in enhancing their NLP skills.
Certification
Frequently asked questions
What is the delivery format of the course?
The course is delivered through live online sessions led by an experienced instructor.
How long is the course?
The course typically spans 6 weeks with weekly sessions lasting 2 hours each.
Will I receive a certificate upon completion?
Yes, participants will receive an Skilvi course-completion certificate after finishing the course.
Are exam vouchers included in the course fee?
Exam vouchers are available through authorized channels on request.
Do I need any prior experience for this course?
Basic knowledge of Python programming is recommended, but no prior experience in NLP is required.
Pricing on request
- Live online (VILT)
- 24–32 hours
- Hands-on labs & assignments
- Skilvi completion certificate
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