Natural Language in Python (Basic to Advance)
Natural Language in Python (Basic to Advance)
Published 10/2025
Duration: 1h 46m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 1.50 GB
Genre: eLearning | Language: English
Published 10/2025
Duration: 1h 46m | .MP4 1280x720 30 fps(r) | AAC, 44100 Hz, 2ch | 1.50 GB
Genre: eLearning | Language: English
Master Natural Language Processing (NLP) in Python — from text basics to advanced AI language models and applications.
What you'll learn
- Build NLP models using popular Python libraries like NLTK, spaCy, and Hugging Face
- Perform real-world NLP tasks — Named Entity Recognition (NER), Sentiment Analysis, and Language Translation
- Get hands-on with transformers and modern AI tools powering today’s chatbots and assistants
- Master text preprocessing: tokenization, stemming, lemmatization, and cleaning
Requirements
- Familiarity with Python programming Language
Description
Have you ever wondered how chatbots talk, how Google Translate works, or how your phone predicts what you’re about to type?Welcome toNatural Language in Python (Basic to Advance)— a complete journey into the world ofNatural Language Processing (NLP)made simple and practical.
In this course, you’ll start by understanding how computers make sense of human language — from the meaning of words to the structure of sentences. Step by step, you’ll learn how to clean, analyze, and transform text data using Python. You’ll explore essential NLP techniques liketokenization, stemming, lemmatization, N-grams, embeddings, and more.
Then we’ll take things to the next level by usingHugging Face Transformersto build modern AI applications — likelanguage translation,sentiment analysis, andnamed entity recognition— all with hands-on examples.
By the end, you’ll not only understand how machines process language but also have the confidence to build your own NLP projects from scratch.
What You’ll Learn
What NLP is and how it helps computers understand human language
The basics of linguistics — syntax, semantics, and morphology
How to clean and prepare text data for analysis
Techniques like Bag of Words, N-grams, and word embeddings
How to explore and visualize text data
Using Hugging Face for real NLP tasks: translation, sentiment analysis, and question answering
Who this course is for:
- Python learners who want to explore real-world applications in AI and NLP
- Data science and machine learning enthusiasts eager to work with text data
- Students and professionals looking to build projects in NLP or AI
More Info