Natural Language Processing Specialization

Course Description

Course Description

This specialization introduces learners to key NLP methods, focusing on classical ML (logistic regression, Naïve Bayes, word vectors), sequence models (RNN, LSTM, GRU, Siamese), and attention-based models (Transformer, BERT, T5). Understanding these is crucial for building text analytics, conversational AI, translation systems and modern LLM-based tools today.

Trax, TensorFlow, Hugging Face Transformers (BERT, T5, Transformer models); ML tools like logistic regression, Naïve Bayes, HMM, LSTM, GRU, attention mechanisms

Tools / Techniques Covered

Trax, TensorFlow, Hugging Face Transformers (BERT, T5, Transformer models); ML tools like logistic regression, Naïve Bayes, HMM, LSTM, GRU, attention mechanisms
Intermediate Python, ML foundations, calculus, linear algebra, stats

Prerequisites

Intermediate Python, ML foundations, calculus, linear algebra, stats

Difficulty Level

Difficulty Level

Intermediate
Start Learning

Course Includes:

  • Artificial Intelligence
    Skill
    Artificial Intelligence
  • AI & Natural Language Models
    Topic
    AI & Natural Language Models
  • Coursera
    Platform
    Coursera
  • DeepLearning.AI
    Provider
    DeepLearning.AI
  • Duration of Course
    Duration of Course
    110 Hours
  • Ratings
    Ratings
    4.6 (5,766 reviews)
  • Course Language
    Course Language
    English
  • Video Transcript
    Video Transcript
    Yes
Start Learning

The information provided here is created as a community resource and is not intended as professional advice or a recommendation by ILSS or Koita Foundation. While we strive to ensure the accuracy of the content, we do not take responsibility for any errors or omissions. Users should use their own discretion before making any decisions based on this information. ILSS or Koita Foundation assume no liability for any actions taken based on the information provided.

  • © 2025 India Leaders for Social Sector. All Rights Reserved.