Natural Language Processing (NLP) Fundamentals with Python

The NLP Fundamentals with Python course provides a comprehensive introduction to Natural Language Processing concepts, techniques, and applications. It equips learners with the skills to process, analyse, and derive insights from textual data using Python’s NLP libraries.

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Overview

The Natural Language Processing (NLP) Fundamentals with Python course is designed for professionals and learners seeking to understand and implement NLP techniques. This course introduces foundational concepts of NLP, enabling learners to process and analyse textual data effectively using Python.

NLP is a key area of AI, driving innovations in applications such as chatbots, sentiment analysis, and language translation. This course covers essential topics including text preprocessing, tokenisation, sentiment analysis, and text classification, empowering learners to create NLP solutions for real-world problems.

This intensive 2-day training includes expert-led sessions, hands-on exercises, and practical case studies. Learners will gain experience with popular Python libraries like NLTK, spaCy, and TensorFlow, equipping them to implement NLP techniques in various applications.

Course Objectives

Understand the fundamentals of Natural Language Processing
Learn to preprocess and tokenise textual data using Python libraries
Develop skills in sentiment analysis and text classification
Explore techniques for language modelling and text summarisation
Apply NLP techniques to real-world datasets and projects

Upon completion, learners will possess the knowledge and skills to implement NLP techniques effectively, advancing their expertise in AI and data science applications.

Average completion time

2 Month

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Course Details

Develop your understanding of essential financial, business and management accounting techniques with ACCA Applied Knowledge. You'll learn basic business and management principles and the skills required of an accountant working in business.

Entry Requirements

Educational Background: A basic understanding of programming and data science is recommended.
Technical Proficiency: Familiarity with Python is essential, as the course involves hands-on coding exercises.
Interest in NLP: Ideal for individuals eager to explore Natural Language Processing and its applications in AI and data science.

Learning Outcomes

Master NLP Fundamentals: Understand key concepts such as tokenisation, language modelling, and text classification.
Develop Practical Skills: Gain expertise in using Python libraries like NLTK and spaCy for text processing and analysis.
Solve Real-World Problems: Apply NLP techniques to tasks such as sentiment analysis, text summarisation, and entity recognition.
Build NLP Solutions: Learn to implement and evaluate NLP models for various applications.

Target Audience

The Natural Language Processing (NLP) Fundamentals with Python course is tailored for professionals and learners eager to explore NLP techniques. It provides practical skills to process and analyse textual data effectively using Python. Below are the individuals who will benefit from this course:

Software Developers
Data Scientists
Machine Learning Engineers
Data Analysts
Artificial Intelligence (AI) Researchers
Product Managers
Business Analysts

Course content

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

MPES Support That Helps You Succeed

At MPES, we offer comprehensive support to help you succeed in your studies. With expert guidance and valuable resources, we help you stay on track throughout your course.

MPES Learning offers dedicated support to help you succeed in Accounting and Finance courses.
Get expert guidance from tutors available online to assist with your studies.
Check your eligibility for exemptions with the relevant professional body before starting.
Our supportive team is here to offer study advice and support throughout your course.
Access a range of materials to help enhance your learning experience. These resources include practice exercises and additional reading to support your progress.

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George Evans

George Evans

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James Robinson

James Robinson

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Laura Bennett

Laura Bennett

Chief Financial Officer

Emma Johnson

Emma Johnson

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Arvy Pasanting

Arvy Pasanting

Audit Senior (incoming Reconciliations Manager)

David Ford

David Ford

Accountant

Aaron Allcote

Aaron Allcote

Finance Officer

Bob Beaumont

Bob Beaumont

Senior Accountant

Have Questions? We’ve Got You

If you have any questions, we’re here to help. Find the answers you need in the MPES detailed FAQ section.

Q. What is the focus of the NLP Fundamentals with Python course?

This course focuses on introducing learners to NLP concepts and techniques, enabling them to process and analyse textual data effectively using Python libraries like NLTK and spaCy.

Q. Do I need prior experience with Python to take this course?

Yes, familiarity with Python is essential, as the course involves hands-on coding exercises and practical implementation of NLP techniques.

Q. What practical skills will I gain from this course?

You will learn to preprocess text, perform sentiment analysis, implement text classification, and use Python libraries like TensorFlow for NLP tasks such as language modelling and summarisation.

Q. Who should take this course?

This course is ideal for Data Scientists, Machine Learning Engineers, Software Developers, and anyone interested in building NLP solutions for AI and data science applications.

Q. How is the course delivered?

The course combines expert-led sessions, hands-on exercises, and practical case studies, ensuring a comprehensive and applied understanding of NLP concepts and techniques.

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04-Dec-2024

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