Online Course – Packt Institute Certified Professional Internship in Natural Language Processing

Master NLP methodologies with Python. Become a professional in natural language processing using Python.

Suggested by: Coursera (What is Coursera?)

Professional Certificate

Beginners Intermediate level Advanced involved

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Semantic processing
  • Word2Vec
  • NLP
  • Lexical processing
  • Syntactic processing

What you will learn in the course

Courses for which the course is suitable

  • Chatbot developer
  • Text data analyzer
  • NLP Engineer
  • Machine learning model developer
  • Emotion analysis expert
  • App developer with API integration
  • Natural language analyzer
  • Spam detection solution developer
  • Automatic translation systems developer
  • Developing projects with Alexa and Google Home

Internship – a three-unit course series

In this course, you will learn how machines can train themselves to understand and process human language using various NLP (Natural Language Processing) algorithms. You will discover linguistic processing processes, basic syntactic processing, and mechanisms like those used by Google Translate to understand the context of language and the translation process.

Practical project

Includes building a chatbot with Rasa that conducts written and voice conversations, connects to messaging channels, and integrates APIs. You’ll also learn how to train your models for natural language understanding (NLU). Hand-written programs fail to cope with variable input, so the course focuses on creating models that understand context and are flexible.

Course requirements
  • No prior knowledge of machine learning or deep learning is required.
  • The course covers all necessary requirements.

By the end of the course, you will be proficient in building NLP models for text summarization, sentiment analysis, and entity recognition, all through real-world projects. This course is ideal for:

  • Students entering data science.
  • Professionals who are familiar with deep learning.
  • Developers interested in creating chatbots or working on Alexa and Google Home projects.

Hands-on Learning Project

The projects in the course will provide practical experience using NLP techniques, allowing participants to apply the skills in authentic environments such as:

  • Text data analysis.
  • Syntactic and semantic processing.
  • Building models for tasks such as spam detection and information extraction.

Upon completion of these projects, participants will gain practical expertise to solve real-world problems using natural language analysis.

Details of the courses that make up the specialization

Prerequisites and Advanced Machine Learning for NLP

Course 1 • 18 hours

Course Details
  • What you’ll learn
    • Install and configure Python and Anaconda for NLP projects.
    • Understand and evaluate linear regression and gradient descent methods.
    • Create data diagrams efficiently with Matplotlib and Seaborn.
    • Apply machine learning algorithms such as linear regression and KNN to NLP tasks.
Skills you will acquire
  • Category: Linear Regression
  • Category: NumPy
  • Category: Machine Learning
  • Category: Natural Language Processing
  • Category: Data Science

Introduction to NLP and Syntactic Processing

Course 2 • 13 hours
Course Details
  • What you’ll learn
    • Remember the basics of NLP and text encoding.
    • Use regular expressions for text processing.
    • Implement lexical processing techniques such as word bag and Tf-IDF.
    • Create models for correcting spelling errors and handling compound words.
Skills you will acquire
  • Category: Syntactic analysis
  • Category: Lexical processing
  • Category: Natural Language Processing
  • Category: Regular expressions
  • Category: Syntactic processing

Advanced semantic processing

Course 3 • 5 hours
Course Details
  • What you’ll learn
    • Understand the basic concepts of semantic processing.
    • Analyze and implement latent semantic analysis (LSA).
    • Use Word2vec techniques through practical cases.
    • Evaluate and carry out practical projects in the field of semantic processing.
Skills you will acquire
  • Category: Semantic Processing
  • Category: Dispositional semantics
  • Category: Latent Semantic Analysis
  • Category: Advanced NLP
  • Category: Natural Language Processing