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🤖Natural Language Processing with Deep Learning and Python hero

Level: Beginner

🤖Natural Language Processing with Deep Learning and Python

Understand how machines read text, build intuition for embeddings, RNNs, and Transformers, and use pre-trained models like BERT and GPT through Hugging Face to build a real NLP application.

5.0

2.9k+ learners

Duration

0 min

Learners

2.9k+ Enrolled Students

Session Recording

Lifetime Access

Post Session

Mentor support

Session Schedule

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₹399

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₹399

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Includes

• Expert Designed Curriculum

• Doubt Clearing Session

• Forever Community Access

After this course, you can

Process and analyze text data

Build NLP applications

Train text classification models

Use modern NLP libraries

Course Curriculum

Expand or explore the full learning path.

Lessons

Start here after enrolling. These lessons form the core learning path for the course.

What NLP Actually Is, and Why Text Is Harder Than Numbers

Tokenization: Chopping Sentences into Pieces

Cleaning Text: Lowercasing, Stopwords, Stemming vs Lemmatization

From Words to Numbers: Bag of Words and TF-IDF

Mini Project #1: Build a Spam Classifier with TF-IDF

Why Counting Words Isn't Enough: The Meaning Problem

The Big Idea: Words That Appear Together, Mean Similar Things

Word2Vec Intuition: CBOW and Skip-gram Without the Scary Math

GloVe and Pre-trained Embeddings: Standing on Google's Shoulders

Playing with Embeddings: King - Man + Woman = Queen

Visualizing Embeddings with t-SNE

Why "Bank" (River) and "Bank" (Money) Break Everything

Why Order Matters: "Dog Bites Man" vs "Man Bites Dog"

RNNs: A Network with Memory, One Word at a Time

The Vanishing Gradient Problem: Why RNNs Forget Long Sentences

LSTMs and GRUs: Gates That Decide What to Remember

Mini Project #2: Building a Sentiment Classifier with an LSTM

The Bottleneck: Why Sequential Processing Had to Go

Attention: Letting Every Word Look at Every Other Word

Self-Attention Step by Step: Queries, Keys, and Values

Multi-Head Attention and Positional Encoding: Order Without Recurrence

The Full Transformer: Encoders, Decoders, and What Goes Where

BERT vs GPT: Reading Both Ways vs Predicting the Next Word

Pre-training and Fine-tuning: Why Nobody Trains from Scratch Anymore

The Hugging Face Ecosystem: Hub, Transformers, Datasets, Pipelines

Pipelines in 5 Lines: Sentiment, Summarization, QA, Translation

Loading Models and Tokenizers Manually: What Pipelines Hide from You

Fine-tuning a Pre-trained Model on Your Own Dataset

Capstone Build: Review Radar, a Summarizer + Sentiment Dashboard

Deploying with Gradio, and Where to Go Next

Live Session Content

This topic will be taught live in an interactive session, allowing you to engage with the instructor and ask questions in real time. While recordings will be available, attending live offers the best learning experience.

Post Session Study Material

This section will be unlocked after the session. You'll get access to exclusive bonus content, additional examples, and on-demand resources to support continuous learning and deeper understanding.

Requirements

What you should have before starting the course.

Basic Python programming knowledge

Familiarity with machine learning basics

Understanding of Python libraries

A computer with Python installed

Tools you are going to use

PyTorch

PyTorch

TensorFlow

TensorFlow

Keras

Keras

NumPy

NumPy

Google Colab

Google Colab

Learn From Expert Instructor

Meet the mentors leading the live sessions.

Aarav Sharma

Aarav Sharma

Senior Frontend Engineer, StudioLabs

Aarav has mentored 1200+ learners and specializes in production UI systems and scalable frontend architecture.

LinkedIn
Ananya Mehta

Ananya Mehta

Design Technologist, CraftLabs

Ananya blends design and code to help learners ship portfolio-ready projects.

LinkedIn
Kabir Sayed

Kabir Sayed

Frontend Mentor, PixelWorks

Kabir focuses on clean code, accessibility, and practical frontend delivery.

LinkedIn

You should join this course if you

Students & Fresh Graduates

Build a strong portfolio

Learn from live mentors

Get feedback on your work

Working Professionals

Upgrade frontend skills

Ship real projects

Join a peer community

Career Switchers

Structured learning path

Hands-on practice

Guided sessions

Freelancers & Creators

Build client-ready sites

Improve delivery speed

Learn modern workflows

What you will get after completing this course

Completion certificate

Receive an official course completion certificate

Earn skill-focused feedback from mentors

Showcase your project in the Shattak community

Access lifetime notes and references

Stay connected with instructors for guidance

Completion bonus

Certificate access, community showcase, and lifetime mentor guidance.

Hear From Learners Who've Taken This Course

Honest feedback from learners who completed the live sessions.

4.8

24

Clear structure, solid examples, and a fast pace that keeps you engaged.

Riya Jain

Riya Jain

B.Tech, NIT Trichy

4.6

18

Practical sessions with feedback that helped improve my portfolio.

Kabir Singh

Kabir Singh

Frontend Intern, PixelWorks

4.9

12

Loved the structure and the live walkthroughs.

M

Meera Patel

Design Graduate

See what they have build

ZS

Zainab Shaikh

Portfolio Landing Page

Portfolio Landing Page

300 Likes

View Live
DS

Devendra Singh

Product Marketing Site

Product Marketing Site

214 Likes

View Live
NA

Nadia Ahmed

Interactive Web Story

Interactive Web Story

183 Likes

View Live

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Get Life Time Access

₹0

₹399

100% off

Get Life Time Access

₹0

₹399

100% off