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Natural Language Processing (NLP) Fundamentals with Python
What is Natural Language Processing (NLP) Fundamentals with Python?
Natural Language Processing (NLP) is a key subfield of artificial intelligence (AI) focused on enabling machines to understand, interpret, and generate human language. With the increasing reliance on AI technologies, NLP plays a crucial role in applications like chatbots, sentiment analysis, language translation, and more. This course offers essential knowledge in NLP using Python, providing delegates with the tools to apply these techniques effectively.
Proficiency in NLP is vital in today’s tech-driven world, as it powers many real-world applications. Professionals such as dAta Scientists, Software Developers, Business Analysts, and anyone involved in AI or machine learning will benefit from mastering NLP. The ability to process and analyse large datasets of text efficiently has become an invaluable skill for career advancement in various sectors, including healthcare, finance, marketing, and technology.
This 2-day Natural Language Processing (NLP) Fundamentals with Python Course offered by Oakwood Internationals will equip delegates with a strong foundation in NLP. The course covers practical techniques, including text preprocessing, classification, and model training, providing delegates with the skills to work on real-life NLP projects. By the end of the course, delegates will have the knowledge to apply NLP tools to various industries and leverage Python to implement these methods with confidence.
Course Objectives:
- To understand the basics of Natural Language Processing (NLP)
- To learn Python programming for NLP tasks
- To explore text preprocessing techniques
- To understand named entity recognition (NER) and its applications
- To work with word embeddings and vector representations of text
- To apply NLP techniques to real-world projects
- To develop problem-solving skills for NLP challenges
Delegates will receive a certificate of completion, recognising their newly acquired skills in Natural Language Processing. This certification will enhance their professional profile and demonstrate their proficiency in NLP to potential employers or clients.
Course Outline
Natural Language Processing (NLP) Fundamentals with Python
Module 1: Introduction to NLP
- What is Natural Language Processing?
- Why is NLP Important?
- Applications of NLP
- Challenges in NLP
- Tools and Resources for NLP
Module 2: Text Preprocessing
- Text Cleaning and Normalisation
- Tokenisation
- Part of Speech Tagging
- Named Entity Recognition
- Stop Word Removal
Module 3: Text Representation
- Bag of Words
- Term Frequency-Inverse Document Frequency (TF-IDF)
- Word Embeddings
- Topic Modelling
Module 4: Text Classification
- Supervised Learning
- Naive Bayes
- Support Vector Machines (SVM)
- Decision Trees
- Evaluation Metrics for Text Classification
Module 5: Advanced NLP Techniques
- Sequence Labelling
- Language Modelling
- Neural Machine Translation
- Sentiment Analysis
- Text Summarisation
Included
Included
- No course includes are available.
Offered In This Course:
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Video Content
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eLearning Materials
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Study Resources
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Completion Certificate
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Tutor Support
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Interactive Quizzes
Individual Training
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Learning Options
Discover a range of flexible learning options designed to meet your needs. Select the format that best supports your personal growth and goals.
Online Instructor-Led Training
- Live virtual classes led by experienced trainers, offering real-time interaction and guidance for optimal learning outcomes.
Online Self-Paced Training
- Flexible learning at your own pace, with access to comprehensive course materials and resources available anytime, anywhere.
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Frequently Asked Questions
Q. What is Natural Language Processing (NLP)?
NLP is a subfield of artificial intelligence (AI) that focuses on the interaction between computers and human language. It enables machines to process, understand, and generate human language.
Q. Who should take this NLP course?
Q. Do I need prior experience in programming to take this course?
Basic programming knowledge, particularly in Python, is helpful but not essential. The course includes a foundational introduction to Python for NLP tasks.
Q. What topics will be covered in this course?
The course covers text preprocessing, classification, named entity recognition (NER), word embeddings, sentiment analysis, and building machine learning models for NLP.
Q. Is this course suitable for beginners?
Yes, the course is designed to be beginner-friendly, with no advanced knowledge of NLP required. It starts with basic concepts and builds up to more complex applications.
