Natural Language Processing (NLP) for Beginners using Python
Md. Rezuwan Hassan
Instructor
Md. Rezuwan Hassan
Course Level
Beginner
Duration
Duration 7 hrs 46 min
Rating
Rating 4.33
Students
Students 18

Natural Language Processing (NLP) for Beginners using Python

Are you ready to dive into the world of Natural Language Processing (NLP), where machines understand and respond to human language? Then, this course is for you! This essential AI field empowers you to automate tasks, analyze text data, and gain valuable insights, making it a crucial skill in today's data-driven world.

 

Why Is This Course Important to Learn?

In today's data-driven world, understanding and processing human language is crucial for many applications. From chatbots and sentiment analysis to text summarization and translation, NLP is the backbone of these innovations.

 

Who Is This Course For?

  • Beginners eager to explore the world of NLP.
  • Data enthusiasts looking to deepen their understanding of text processing.
  • Professionals seeking to integrate NLP techniques into their work.
  • Students and researchers aiming to enhance their analytical skills.
  • Anyone interested in leveraging language data for business or personal projects.

 

Why Should You Enroll?

  • Master Text Cleaning: Learn techniques to clean and preprocess text data.
  • Enhance Data Accuracy: Improve the quality of your text data by correcting typos and removing unwanted elements.
  • Boost Analytical Skills: Develop skills in tokenization, stemming, lemmatization, and more.
  • Understand Text Representation: Dive into methods like Bag of Words and TF-IDF.
  • Gain Practical Experience: Apply your knowledge to real-world datasets and practical examples.
  • Explore Advanced Topics: Delve into EDA, text representation, and statistical language modeling.

 

What Will You Learn?

  • Introduction to NLP: Understand the basics and applications of NLP.
  • Text Cleaning and Preprocessing: Learn to clean and preprocess text by removing punctuation, stopwords, and correcting typos.
  • Text Representation Techniques: Master Bag of Words, TF-IDF, and converting text to sequences.
  • Handling Text Data: Tackle exceptions with OOV tokens and use padding techniques.
  • Practical Applications: Work with real datasets and practical examples to solidify your learning.

 

Enrol in LEAD Academy’s NLP Course today to enhance your skills, automate tasks, and unlock career opportunities in the rapidly growing field of language data analysis.

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What Will I Learn?
  • NLP Fundamentals
  • Text Cleaning
  • Data Accuracy
  • Tokenization
  • Text Representation
  • Practical Examples
Course content
  • 6 Chapters
  • 50 Lessons
  • 7 hrs 46 min

Course Overview

Free Preview 00:05:59

Kaggle Introduction

Free Preview 00:09:45

Google Colab Introduction

00:11:27

Huggingface Introduction

00:05:56

Removing Punctuation

00:03:16

Correction of Typos

00:06:37

Removing Stopwords

00:03:40

Tokenization

00:06:25

Stemming and Lemmatization

00:04:42

Stemming and Lemmatization Difference

00:03:10

Number to Words Conversion

00:02:15

Part-Of-Speech (POS) Tagging

00:04:31
Quiz

Quiz 01

Text Cleaning & Text Preprocessing

00:02:21

Bag of Words

00:03:29

Term Frequency Inverse Document Frequency

00:10:34

Text to Sequence

00:08:14

Handling Exceptions (Out of Vocabulary Tokens)

00:01:39

Padding

00:08:02

Introduction to Real Datasets

00:01:14

Kaggle Account Setup

00:02:26

EDA and Text Representation Practical Example

00:08:06

Natural Language Processing Pipeline

00:01:14

Language Model Evolution

00:02:41

Statistical Language Model

00:01:30

Logistic Regression

00:07:03

Logistic Regression with Binary Classification

00:11:43

Logistic Regression with Binary Classification and Parameter Tuning

00:07:07

Multinomial Logistic Regression

00:04:31

Naive Bayes Classifier

00:11:45

Bernoulli Naive Bayes Classifier

00:03:57

Bernoulli Naive Bayes Classifier with Parameter Tuning

00:03:05

Multinomial Naive Bayes Classifier

00:04:28

N-gram Models

00:15:44

N-Gram Models Project (Intro & Preprocessing Data)

00:19:20

N-Gram Models Project (Modeling Algorithm)

00:30:57

N-Gram Models Project (Perplexity and Queries)

00:23:14

Deep Learning Models: Part 1

00:23:36

Deep Learning Models: Part 2

00:30:40

Deep Learning Models Practical

00:20:49

Natural Language Processing Pipeline

00:02:36

What is a large language model or LLM

00:05:20

Generative AI and Conversational AI

00:06:50

Transformers Models

00:05:47

Hugging Face Spaces

00:02:10

Machine Translation

00:20:49

Automatic Text Summarization

00:21:45

Contextual Question Answering

00:06:45

Tabular Question Answering

00:09:26

Named Entity Recognition

00:14:19

Automatic Speech Recognition

00:33:19
Pre Requisites
  • Basic Computer Skill
  • Keep video resolution at 1080p
Meet Your Instructor

Md. Rezuwan Hassan

4.33 Instructor Rating
6 Reviews
18 Students
1 Course

Review
4.33
Mohammad Shahadul Islam

Mohammad Shahadul Islam

3 months ago

The course was well designed. Those whoare interested in this topic will findthis course helpful

Reply from Instructor

Thank you for your positivefeedback.Stay connected.

Arunim Ahmed

Arunim Ahmed

3 months ago

This is the best hands-on NLP course forbeginners like me. The instructoravoided lengthy explanations and complexmathematics, making the concepts clearand concise. The practicaldemonstrations of the concepts on codesusing python are very helpful. Highlyrecommended for any beginners.

Reply from Instructor

Thank you, Keep learning!

Dipankar Banik

Dipankar Banik

3 months ago

Jubayer

Jubayer

3 months ago

The "(NLP) for Beginners using Python"course from Lead Academy was a greatlearning experience. The high-qualityvideos, well-structured content, andclear instructional materials made NLPconcepts accessible and engaging.Although the sound quality could beimproved, the instructor’s engagingdelivery and seamless video load timesgreatly enhanced my understanding. Ihighly recommend this course for anyonestarting in NLP.

Reply from Instructor

Thank you, Keep learning!

MD Tanvir Rahman

MD Tanvir Rahman

3 months ago

বলতেছে একজিনিস হচ্ছেআরেক জিনিস ।তার পড়েবলতেচ্ছে"আচ্ছা তাহলেএখন এমন হয়" ।ভাই শেখাতেআসছেন নাকিশিখতে আসছেন ??বিন্দুমাত্রকোর্স প্লানআপনার নাই। ভাই শুদ্ধভাষায় স্পষ্টকরে কথা না বলতেপাড়লে কোর্সবানানোর দরকারনাই। বাংলাইংলিশ , লোকাল accentএ কথা এমন ভাবেবলতেছেন যেনআপনার সাথে টংএর দোকানেআড্ডা দিতেবসছি । একটাকোর্স বানাবেনসাউন্ড কয়ালিটিএতো লো কেন ?টিচার মিন মিনকরে নিজে নিজেকথা বলে ।টিচারের নিজেরকোন প্রস্তুতিনেই । একটাকোর্স বানাবেনকি বলবেন সেটাঠিক করা নাই।ভিডিও তে বসেট্রায়ালঅ্যান্ড এরররকরতেছে । কোনকিছু না হলেবলতেছে আচ্ছাএভাবে না করি ,টাকা নইয়েফাইযলামিকরতেছেন?? । LLMনিয়ে একটাসেকশন সেখানেATTENTION model নিয়েদুইটা ভিডিওনাই বেশি কিছুবলা নাই । টিচারএর লেসসন প্লানবলে কিছু নাই ।মনে হয়কম্পিউটার এরসামনে ২০ টাকারহেডফোন নিয়েবসে গেছে কোর্সবানাতে । Coursera,pluralsight এর কোর্সদেখেন লেসন সবপ্লান করা । কিবলবে আগে থেকেপ্লান করা ।

Reply from Instructor

As I tried to make this a hands-on,practical course, I pretty much tried toavoid maths and complex theories ratherthan focusing on practical works. Forexample, it is my belief, one does notneed to know "computer architecture " tooperate a computer in general. Accentdoesn't matter if the meaning/context isconveyed properly to the other side.Some YouTube educators or local publicfigures are some of the best examples.But still your feedback is alwaysappreciated, I can always work on thisto be a betterspeaker/presenter. Trial and errorwere done to show what to do and whatnot to do or how much a result maydeviate if something different is givenas input to something. The math was doneby myself on paper before putting themon those slides, I knew beforehand whatI should put as input to get theexpected output. But, I tried to show afew different outcomes because I wantedto show probable deviated results too.As for the non-math contents, I tried toput those contents on slides along witha brief introduction. So, I did studyabout them and tried to deliver them thebest way possible by myself or theeasiest way possible for the learners tounderstand. Sometimes, one approachseemed tough halfway, I took anotherapproach to make it easier tounderstand. These processes were done sothe learners may get a hands-onexperience. NLP is a huge ocean, andthis is a beginner-friendly course fornon-cs people background, just enough toget one started with practical NLP.There are opportunities to improve andenhance this course and your feedback isreally an important value addition forthat. Thank you.

Dipankar Banik

Dipankar Banik

3 months ago

Dear Rezuwan Bhaiya, Thanks a ton toyou for giving us a awesome course. Myrequest is to you, please give advanceNLP courses.

Reply from Instructor

Thank you, I'll try. Keep learning!

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