Natural Language Processing Bootcamp in Python from Udemy

Welcome aboard your inaugural voyage into the vibrant world of Natural Language Processing (NLP) and Text Mining. This course offers a risk-free foray (backed by a 30-day refund policy) into the fundamental concepts that serve as the bedrock for the text data operations of tech giants like Google, Amazon, and Microsoft.

Text mining has become a cornerstone of modern Data Science and Analytics. The profound leap in technology that allows a machine to understand words and phrases has revolutionized tasks like Information Retrieval, Translation, and Text Classification. I'm here to help you navigate these waters and jump from the foundational aspects of classical NLP into the misterious realms of Generative AI Tools (such as ChatGPT).

Our journey will take us from the classical to the neural, exploring the evolution of language processing techniques. We'll begin with traditional statistical methods and work our way up to the cutting-edge world of deep learning and neural networks. By linking theory with practical exercises, I hope to guide you through the NLP World.

Don't fret if Python isn't your forte yet - included in this course is a crash course in Python that will acquaint you with the language and provide the necessary foundation for the rest of the topics we'll cover.

The course will illuminate a variety of key NLP concepts including:

Manipulating the basic building blocks of NLP - strings - in Python;
Tokenizing Sentences and Documents;
Stemming and Lemmatizing words;
Training machine learning models using text;
Extracting the Part-of-Speech Tag from words in a sentence;
Extracting Text Data from a Web Page;
Training a Neural Network to extract Word Embeddings;
Developing your own sentiment classifier (Sentiment Analysis);
Representing Sentences as Tabular Data;

Upon completing this course, you'll be equipped with the skills to construct your own basic NLP applications, and you'll have a strong understanding of the fundamental concepts underlying most NLP algorithms. This knowledge will open doors to more advanced studies in NLP, while providing an understanding of the strategies and techniques utilized by companies when launching their NLP applications.

Embark on this exhilarating journey through the world of NLP with me. Whether you're a newcomer or an expert seeking to broaden your horizons, there's a place for you here. I'm eagerly looking forward to our adventure together in the course.

What's inside

Syllabus

Course Introduction

Welcome to the Natural Language processing Course!

In this lecture we will talk a bit about my experience and the overview of the course, namely three different important points:

What we will cover throughout the course.
How the lectures will be organized.
What you should expect to know at the end of the course.

Happy to have you onboard!

Time to test your knowledge on Python strings!

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Includes a Python crash course, which will help students with little to no programming experience to grasp the fundamentals needed for NLP

Features a project-based learning section where students role-play as data scientists working for IMDB, which allows them to apply their knowledge in a practical context

Covers classical NLP techniques and progresses to deep learning and neural networks, which are essential for understanding modern NLP applications like ChatGPT

Equips learners with the skills to construct basic NLP applications and provides a strong understanding of the fundamental concepts underlying most NLP algorithms

Explores word vectors, including creating one-hot vectors, initializing co-occurrence matrices, exploring cosine similarity, and visualizing word vectors

Covers reading text data from various sources, including CSV files, TXT files, and web pages using Requests and BeautifulSoup

Reviews summary

Comprehensive introduction to practical nlp in python

According to learners, this course offers a solid introduction to Natural Language Processing using Python. Students appreciated the practical, hands-on approach and found the inclusion of a Python basics module helpful for newcomers. The course moves from classical techniques to newer concepts like word embeddings, providing a good foundation for further study or application. While some found specific sections challenging, the course is generally seen as a valuable starting point, particularly for those with some programming background.

Optional module helps beginners with Python.

"As someone relatively new to Python, the included basic course was a lifesaver and made the rest accessible."

"It was helpful that they included an optional Python basics section for those who needed a refresher or introduction."

"The Python basics mini-course was sufficient to get me up to speed for the NLP topics."

"I liked that the course catered to both Python beginners and those with more experience."

Moves from classical to modern NLP concepts.

"I liked the progression from basic string manipulation and NLTK to word vectors and neural nets."

"The way the course built up from traditional methods to deep learning concepts felt very logical and easy to follow."

"It was interesting to see the evolution of NLP techniques covered in the syllabus."

"Covers a good range of topics from basic text cleaning to word embeddings."

Provides a strong base for NLP fundamentals.

"It provided a really strong foundation in fundamental NLP concepts and techniques."

"I now have a much clearer understanding of things like tokenization, stemming, and POS tagging."

"This course is a great starting point for anyone looking to get into Natural Language Processing."

"I feel well-prepared to tackle more advanced topics after completing this bootcamp."

Emphasizes practical skills and applications.

"The hands-on coding and projects are the strongest part of the course for me, really helped solidify my understanding."

"I appreciated how the instructor focused on practical applications rather than just theory."

"This course gave me the practical tools I needed to start working with text data in Python."

"I found the project-based learning section, like the IMDB review analysis, very useful for applying concepts."

Some advanced or coding parts are difficult.

"I found the section on training your own POS tagger a bit difficult to grasp initially."

"The neural network implementation and word vectors section was the most challenging part for me."

"Needed to rewatch lectures on the CBOW model multiple times to fully understand."

"Some of the coding exercises required more time and effort than I expected."

Assumes some comfort with coding concepts.

"While they have a Python intro, a basic understanding of programming concepts definitely helps."

"Even with the Python module, absolute beginners might struggle with some of the coding exercises."

"I think having some prior coding experience made this course much easier to follow and complete."

"It's called a 'bootcamp', so expect to be doing a good amount of coding right from the start."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Natural Language Processing Bootcamp in Python with these activities:

Review Python Fundamentals

Show steps

Solidify your understanding of Python fundamentals to better grasp the NLP concepts implemented in Python.

Browse courses on Python Basics

Show steps

Review data types, loops, and functions in Python.
Practice writing simple Python scripts.
Complete online Python tutorials or exercises.

Read 'Natural Language Processing with Python'

Show steps

Supplement your learning with a comprehensive guide to NLP using Python and the NLTK library.

View Natural Language Processing with Python:... on Amazon

Show steps

Read the chapters relevant to the course syllabus.
Experiment with the code examples provided in the book.
Try to apply the concepts to your own text data.

Practice Tokenization and POS Tagging

Show steps

Reinforce your understanding of tokenization and POS tagging through repetitive exercises.

Show steps

Tokenize various sentences and documents using NLTK.
Apply different POS taggers to the tokenized text.
Compare the results and analyze the differences.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Build a Simple Sentiment Analyzer

Show steps

Apply your NLP knowledge to build a practical sentiment analysis application.

Show steps

Collect a dataset of text with sentiment labels.
Preprocess the text data using tokenization and cleaning.
Train a machine learning model to predict sentiment.
Evaluate the performance of your model.

Write a Blog Post on Word Embeddings

Show steps

Deepen your understanding of word embeddings by explaining the concept in a blog post.

Show steps

Research different types of word embeddings.
Explain the intuition behind word embeddings in simple terms.
Provide examples of how word embeddings are used in NLP.
Publish your blog post online.

Dive into Deep Learning for NLP

Show steps

Expand your knowledge of neural networks in NLP with a dedicated deep learning resource.

View Melania on Amazon

Show steps

Read the chapters on recurrent neural networks and transformers.
Implement some of the models described in the book.
Experiment with different hyperparameters to improve performance.

Contribute to an NLP Open Source Project

Show steps

Gain practical experience by contributing to an open-source NLP project.

Show steps

Find an NLP open-source project on GitHub.
Identify a bug or feature to work on.
Submit a pull request with your changes.
Respond to feedback from the project maintainers.

Career center

Learners who complete Natural Language Processing Bootcamp in Python will develop knowledge and skills that may be useful to these careers:

Natural Language Processing Engineer

A Natural Language Processing Engineer develops and implements NLP systems. This course in Natural Language Processing and Text Mining provides a strong foundation for this role, especially with its coverage of fundamental concepts used by tech companies. The course helps one understand how machines understand words and phrases, which is crucial for tasks like information retrieval and text classification. Learning how to manipulate strings in Python, tokenize sentences, and use stemming and lemmatization techniques builds essential skills for any Natural Language Processing Engineer. This knowledge forms a bedrock for more advanced studies and provides insights into industry applications.

See salaries and explore the career path for Natural Language Processing Engineer

Data Scientist

A Data Scientist analyzes data to extract meaningful insights and inform decision-making. This Natural Language Processing Bootcamp provides a valuable toolkit for any data scientist. The course introduces text mining, a cornerstone of modern data science, and provides a risk-free entry into NLP. The course provides an understanding of how machines understand words and phrases, revolutionizing tasks like information retrieval and text classification. By linking theory with practical exercises, the course guides individuals through the NLP world, helping Data Scientists better leverage text data in their analyses.

See salaries and explore the career path for Data Scientist

Computational Linguist

A Computational Linguist focuses on the intersection of linguistics and computer science, developing computational models of language. This course serves as a solid stepping stone for aspiring Computational Linguists. The journey from classical to neural approaches to language processing, exploring the evolution of techniques is essential. The course helps build a foundation in traditional statistical methods and exposure to deep learning and neural networks. The course will illuminate key NLP concepts, including how to extract Part of Speech tags from words, which is fundamentally important.

See salaries and explore the career path for Computational Linguist

Machine Learning Engineer

A Machine Learning Engineer designs, develops, and deploys machine learning models. This course may be useful, as it covers training machine learning models using text, developing sentiment classifiers, and training neural networks to extract word embeddings. The course's focus on bridging classical to neural approaches helps build a comprehensive understanding of language processing, while practical exercises provide hands-on experience. The course teaches how to represent sentences as tabular data. As a Machine Learning Engineer, understanding these techniques becomes invaluable for creating efficient and accurate models.

See salaries and explore the career path for Machine Learning Engineer

Chatbot Developer

A Chatbot Developer builds and maintains conversational AI applications. This course may be useful as it introduces students to text mining as a cornerstone of modern Data Science and Analytics. The course teaches how a computer can understand words and phrases. This is revolutionary to tasks like information retrieval and translation. The course provides an opportunity to develop your own sentiment classifier. It also teaches how to represent sentences as Tabular Data.

See salaries and explore the career path for Chatbot Developer

Text Mining Analyst

A Text Mining Analyst extracts insights from textual data using various NLP techniques. This course may be useful because it explicitly introduces text mining as a cornerstone of modern data science and analytics allowing a machine to understand words and phrases. Moreover, the course dives into the classical and neural aspects of text mining. By explaining how to tokenize sentences and documents the course provides a strong foundation to anyone wanting to become a Text Mining Analyst. The journey will lead to the misterious realsm of Generative AI Tools such as Chat GPT.

See salaries and explore the career path for Text Mining Analyst

Information Retrieval Specialist

An Information Retrieval Specialist designs and implements systems for efficient information access. This course may be useful as it covers text mining which has revolutionized tasks like information retrieval. The course provides a comprehensive overview of NLP techniques. From manipulating basic string operations in Python to training machine learning models using text, these concepts equip Information Retrieval Specialists with the tools to enhance search algorithms and improve data retrieval processes.

See salaries and explore the career path for Information Retrieval Specialist

Search Engine Optimization Specialist

A Search Engine Optimization Specialist improves website visibility in search engine results. This course provides a valuable foundation for anyone in Search Engine Optimization. By understanding how machines process and interpret language, SEO specialists can better optimize content and keywords. The course helps one learn how to tokenize sentences and documents. This knowledge informs more effective keyword research. It also helps with crafting content strategies that align with search engine algorithms.

See salaries and explore the career path for Search Engine Optimization Specialist

Content Analyst

A Content Analyst examines and categorizes content, often to improve organization or searchability. This course, with its exploration of Natural Language Processing concepts, may provide Content Analysts valuable skills. One can learn to appreciate how machines understand words and phrases which can revolutionize tasks like information retrieval and text classification. This course helps one understand the strategies and techniques utilized by companies when launching their NLP applications. By the end of the course the student will be equipped with the skills to construct their own basic NLP applications.

See salaries and explore the career path for Content Analyst

Data Analyst

A Data Analyst interprets data to identify trends and insights. This course, focusing on Natural Language Processing, may provide Data Analysts with additional tools for handling text-based data. The course introduces key NLP concepts, including tokenizing sentences and documents, stemming and lemmatizing words, and extracting Part of Speech tags. These skills provide Data Analysts with capabilities to extract and analyze insights from unstructured text data, enhancing their ability to provide comprehensive analyses.

See salaries and explore the career path for Data Analyst

Digital Marketing Analyst

A Digital Marketing Analyst analyzes digital marketing campaigns to optimize performance. This course may provide a useful skill set. The course teaches the fundamental concepts that serve as the bedrock for the text data operations. This course can also help with sentiment classification and analysis. All of this can help Digital Marketing Analysts improve their ability to gauge customer sentiment from text-based feedback.

See salaries and explore the career path for Digital Marketing Analyst

Healthcare Data Analyst

A Healthcare Data Analyst analyzes healthcare data to improve patient outcomes and operational efficiency. This course helps greatly to gain the basic understanding of data and how to apply it to the professional world. By linking theory with practical exercises, I hope to guide you through the NLP World. Healthcare Data Analysts require a strong understanding of the fundamental concepts underlying most NLP algorithms. This knowledge will open doors to more advanced studies in NLP.

See salaries and explore the career path for Healthcare Data Analyst

Market Research Analyst

A Market Research Analyst studies market conditions to examine potential sales of a product or service. This course helps a market research analyst to get more insight from surveys and questionnaires. By the end of the course, you will be equipped with the skills to construct your own basic NLP application and you'll have a strong understanding of the fundamental concepts underlying most NLP algorithms. This knowledge will open doors to more advanced studies in NLP.

See salaries and explore the career path for Market Research Analyst

Business Intelligence Analyst

A Business Intelligence Analyst uses data analysis to identify business trends and opportunities. This course may be useful as it teaches the basic building blocks of Natural Language Processing such as manipulating strings in Python. It also teaches tokenizing sentences and documents and stemming and lemmatizing words. This data can be used to train machine learning models using text. This course will illuminate a variety of key NLP concepts. This will equip BI analysts with skills to extract greater insights.

See salaries and explore the career path for Business Intelligence Analyst

Technical Writer

A Technical Writer creates technical documentation for various products and services. This course helps Technical Writers who deal with AI and NLP technologies. By understanding the fundamental concepts behind Natural Language Processing, a technical writer can more effectively document these systems. The course will lead from classical to neural approaches of language processing techniques. It will also explore the evolution of language processing techniques.

See salaries and explore the career path for Technical Writer

Natural Language Processing Bootcamp in Python

Here's a deal for you

What's inside

Syllabus

Traffic lights

Save this course

Reviews summary

Comprehensive introduction to practical nlp in python

Activities

Career center

Reading list

Share

Similar courses