NLP Free Course: Discover the Power of Natural Language Processing

Explore Self-learning Systems using Natural Language Processing

  • Learn to leverage Python libraries for NLP projects. 
  • Develop a solid understanding about NLP foundational concepts.
  • Learn to apply modern NLP techniques to real problems. 
  • 450,000 + Professionals trained
  • 250 + Workshops every month
  • 100 + Countries and counting

Mastering Basics of Natural Language Processing

Stay ahead in the rapidly evolving AI landscape by immersing yourself in the world of Natural Language Processing (NLP) and its transformative elements. Dive into NLP and explore how advanced models like transformers are reshaping the field with our NLP free course.

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Highlights

  • 18+ Hours of Self-Paced Learning  

  • Practice with Guided Hands-On Exercises 

  • Learn-by-Doing with Immersive Learning 

  • Test Your Learning with Recall Quizzes 

  • Unlock Knowledge with Interactive eBooks 

  • Accelerate Progress with Auto-Graded Assessments 

Ready to get started?

Contact Learning Advisor

The KnowledgeHut Edge  

Superior Outcomes

Focus on skilled-based outcomes with advanced insights from our state-of-the art learning platform. 

Immersive Learning

Go beyond just videos and learn with recall quizzes, interactive eBooks, assessments and more. 

World-Class Instructors

Course instructors and designers from top businesses including Google, Amazon, Twitter and IBM. 

Real-World Learning

Get an intimate, insider look at companies in the field through real-world exercises. 

Industry-Vetted Curriculum

Curriculum primed for industry relevance and developed with guidance from industry advisory boards. 

Continual Support

Learn better with support along the way. Get 24/7 help, stay unblocked and ramp up your skills. 

prerequisites for NLP Free Course

Prerequisites

The prerequisites for this introductory course are:

  • Python Programming Knowledge
  • Understanding of Linguistics
  • Knowledge of Statistics and Probability
  • Data Manipulation and Analysis
  • Machine Learning Fundamentals
  • Familiarity with Text Processing Techniques

Who Should Attend

Web Developers

Data Scientists

ML Engineers

Business Analysts

Researchers

Language Professionals

Education Professionals

What You Will Learn

Introduction to NLP

Learn how natural language processing (NLP) works and its components. 

Essentials of NLP

Learn the fundamentals of NLP and the key terms associated with it. 

NLP Feature Extraction

Learn the process of extracting features from text data for use. 

NLP with TextBlob

Use the Python library for NLP tasks, such as sentiment analysis and text classification. 

NLP with Spacy

Use the Python library for NLP tasks, with a focus on speed and accuracy. 

Evolution of NLP

Learn about the origins of NLP, from its early days to the present scenario. 

NLP Pipeline

Understand the steps that are typically performed when processing text data with NLP. 

NLP Toolkits and Libraries

Explore a large collection of tools and resources that can be used for NLP tasks. 

Challenges of using NLP

Understand the difficulties and limitations of NLP, such as the ambiguity of natural language. 

Text Analysis

Explore the process of analyzing text data to extract meaning and insights. 

Tokenization and POS Tagging

Understand how to break text into tokens and assign parts-of-speech tags to each token. 

Lemmatization and NER

Learn how to group together words with the same meaning and identify named entities.

Skill You Will Gain

Understanding of NLP fundamentals and its applications

NLP feature extraction techniques

Hands-on experience with NLP libraries and toolkits

Knowledge of the NLP pipeline for text analysis

Proficiency in text analysis techniques

Tokenization and part-of-speech tagging

Lemmatization and named entity recognition (NER)

Awareness of NLP challenges and limitations

Understanding of the evolution of NLP approaches and techniques

Curriculum

Learning Objective:

Get an introduction to Natural Language Processing. The main learning objective of this session is to learn what NLP is and its applications.  

Topics
  • What is Natural Language Processing?  
  • History of Natural Language Processing  
  • NLP Applications  
  • NLP Levels  
  • NLP Components  
  • NLU  
  • NLG  
  • NLU vs NLG  
  • NLP Pipeline and Tasks  
  • NLP Toolkits and Libraries   
  • NLP Challenges  

Learning Objective :

Learn concepts like tokenization, PoS tagging, stop word removal, text normalization, spelling correction, stemming and lemmatization named entity recognition word sense disambiguation. And finally, we will end up the module with sentence boundary detection.   

Topics
  • Basic Text Analysis  
  • Tokenization  
  • POS Tagging  
  • Stop Word Removal  
  • Text Normalization  
  • Spelling Correction  
  • Stemming   
  • Lemmatization  
  • Named Entity Recognition (NER)  
  • Word Sense Disambiguation  
  • Sentence Boundary Detection  

Learning Objective  

The vectorization method will be covered in this module, including the back of the word, the frequency of the vector or the count vectorization, one hot encoded, distributed representation, word embedding, and finally, word2vec. 

Topics
  • Data Structures 
  • Data cleans up with re - Demo 
  • NLP Pre Processing 
  • Data Collocations - Demo 
  • Feature Extraction Methods 
  • The Bag of Words 
  • Frequency Vector  
  • One-Hot Encoding 
  • Term Frequency – Inverse Term Frequency 
  • Distributed Representation 
  • Word Embedding 
  • Tokenizers - Demo 
  • Stemming-Lemmatization and stop word removal - Demo 
  • Vectorization – Demo 

Learning Objective:

In this module, you will learn about the NLP libraries. We will be focusing on the TextBlob library and its features.   

Topics
  • Introduction to TextBlob  
  • Installation of TextBlob  
  • Installing TextBlob - Demo  
  • Language Detection  
  • Language Detection - Demo  
  • POS  
  • POS - Demo  
  • Word Inflection  
  • Word Inflection - Demo  
  • Sentiment Analysis  
  • Sentiment Analysis – Demo  

Learning Objective:

In this module, you will learn about another NLP library - spaCy that is easy to use and easy to implement for any problems within any business domain.   

Topics
  • The spaCy Library 
  • Installing spaCy – Demo 
  • Introduction to spaCy Library 
  • Reading a Document or Text – Demo 
  • Objects of spaCy Library 
  • Part of Speech Tagging – Demo 
  • The Statistical Modeling 
  • Large-scale Data Analysis with spaCy - Demo 
  • Processing Pipelines 
  • Named Entity Recognition – Demo 
  • TXT normalization and inflection – Demo 
  • Semantic Similarity – Demo 
  • Stops Words in Spacy - Demo 

Frequently Asked Questions

Introduction and Benefits:

NLP is short for Natural language processing, a technology sub-domain that helps machines, in this case computers understand and process human language(s). It is a rapidly growing domain with applications in healthcare, finance, customer service, etc.

NLP uses a variety of techniques to identify the meaning of words and phrases, as well as the structure of sentences. It is a powerful tool used for automation, personalization, and improving interactions between machines and humans. As NLP continues to develop, one can expect to see even more innovative applications of this technology. 

Learning NLP can help explore the intricacies of human language and gain valuable skills in lucrative domains such as AI, data science, and linguistics. NLP is a rapidly growing domain with many applications, thus providing many career advancement opportunities.  

Here are some of the benefits of learning NLP:  

  • Learn how to analyze, interpret, and generate textual content.  
  • Gain a competitive edge in AI.  
  • Process and extract valuable insights from unstructured textual data.  
  • Contribute to language translation, sentiment analysis, and voice assistants.  

If you are interested in a free NLP certification, KnowledgeHut can help you. 

Python is a popular choice for NLP because it has a large and active community, many powerful libraries (e.g., NLTK and SpaCy), and a simple syntax. These factors make it easy to learn and use Python for NLP tasks.

NLP practitioners and researchers prefer Python because it is efficient and effective for creating sophisticated NLP applications and algorithms. Python's versatility enables efficient data manipulation, feature extraction, and model building. This makes it an ideal language for analyzing and processing human language data.  

KnowledgeHut offers a free NLP certification course that includes on-demand videos, hands-on exercises, interactive eBooks, and recall quizzes. This course is a great way to learn the basics of NLP and gain the skills required for you to start a career in this field.

This is a self-paced course for you to learn at your own time convenience. If NLP is something that genuinely intrigues you, you can check out the free NLP courses on KnowledgeHut. 

The prerequisites to learn NLP include a basic understanding of Python programming, linguistics, statistics, data manipulation, machine learning, and text processing. These skills will help you understand the concepts and techniques used in NLP and use them in real-world problems.

If you are new to NLP, we recommend that you start by learning the basics of Python programming. With a solid foundation in the prerequisites, you will be well-positioned to learn NLP and apply it to your work. 

Course and Certification:

The time it takes to complete a free NLP course depends on your existing knowledge, experience, and skills. If you have some prior knowledge of computer science or linguistics, you may be able to complete the course in 3 months or less. If you are new to the subject, it may take a bit longer to complete.

KnowledgeHut's free NLP training is self-paced. However, we recommend setting aside at least 10-15 hours per week to study. This will give you enough time to watch the videos and complete the quizzes. 

You will receive a certificate of completion upon completing the free NLP training. This certificate will demonstrate your knowledge of the fundamentals of NLP and can be used to highlight your skills to potential employers.

The certificate is issued by KnowledgeHut. The certificate is free to download, and you can add it to your LinkedIn profile or resume. 

NLP courses can be a valuable investment for those interested in learning about natural language processing, artificial intelligence, or data analysis. The worth of a free NLP certification depends on your learning goals and career aspirations.

If you are interested in learning the basics of NLP and want to gain a general understanding of the field, then this free NLP certification online may be sufficient. However, if you are serious about pursuing a career in NLP, then a more in-depth course with hands-on experience may be a better investment. This course can still be a great starting point for your journey.  

The best NLP course for you will depend on your individual preferences and learning style. One free NLP course that we recommend is KnowledgeHut's free NLP certification. This free course is self-paced and covers the basics of NLP. It is a good option if you want to learn the basics of NLP without spending a lot of money.

If you are looking for a more in-depth course, check out some of best NLP courses online (for) free. 

Yes, you can learn natural language processing (NLP) directly by exploring our free NLP course(s). Knowledgehut's NLP free course is self-paced and comes with multiple resources, including on-demand videos, hands-on exercises, recall quizzes, and interactive eBooks.

The free NLP training covers the basics of NLP, such as tokenization, parts-of-speech tagging, and named entity recognition. This free course also covers foundational topics. 

NLP comes with its share of challenges, including language ambiguity, context sensitivity, and the requirement for substantial labelled data for specific tasks. These challenges make NLP development complex and resource intensive. However, there have been significant advancements in the field in recent years. These advancements have made it possible to develop NLP algorithms that are more accurate and effective.

Despite these challenges, continuous advancements and research in the field aim to address these limitations and improve the effectiveness and accuracy of NLP applications. 

Career and Job Opportunities:

Yes, NLP typically requires coding skills, particularly a foundational understanding of Python programming. Python is widely used in the NLP domain for implementing algorithms, manipulating text data, and utilizing NLP libraries effectively. 

Coding proficiency enables data preprocessing, feature extraction, and the application of various NLP techniques, such as tokenization, stemming, and part-of-speech tagging. By leveraging Python, NLP practitioners can develop powerful applications and models to analyze, understand, and generate human language, making coding an essential prerequisite. 

Start by building a strong foundation in the field through KnowledgeHut's NLP free course. Embrace problem-solving and stay up to date with the latest technologies. Demonstrate your expertise by completing certifications and working on real-world projects. Showcase your skills in data analysis, text processing, and model building to potential employers. 

Stay active in NLP communities, participate in hackathons, and contribute to open-source projects to stand out. Networking, internships, and building a strong portfolio are essential for increasing your chances of landing a rewarding NLP job and making a valuable impact in the field. 

Prominent companies excelling in NLP include SAS, OpenAI, SoundHound, Baidu, Apple, Amazon, Google, IBM, and Microsoft, as recognized by Technology Magazine. These global brands are at the forefront of advancing NLP technologies.  

In the Indian market, companies like Skit.ai, Gnani.ai, and RaGaVeRa Indic Technologies are making significant strides in the NLP domain. These companies are driving innovation and shaping the future of NLP applications across various industries, solidifying their position as leaders in the field. 

According to AmbitionBox, the average annual salary for NLP Engineers in India is INR 8 lakhs per annum. The package may vary depending on experience, job role, and company size. Experienced professionals may earn more, while those with less experience may earn less. It is important to consider your expertise and work experience when assessing potential earnings in the NLP domain. 

Please keep in mind that these are just averages. The actual salary you earn will depend on a number of factors, including your skills, experience, and the specific job market. 

NLP is a good career for professionals who are passionate about problem-solving and want to make a real impact on the world. The field is growing rapidly, and there is a high demand for NLP skills. NLP professionals can command high salaries, and they have the opportunity to work on challenging and rewarding projects.

One way to get started in an NLP career is to enrol in KnowledgeHut's free NLP certification online. This starter course equips learners with essential NLP skills and provides a valuable certification to demonstrate expertise in the domain. 

As AI and language processing technologies evolve, the demand for NLP expertise will continue to grow. So yes! NLP holds a bright future ahead. With its numerous applications across various industries, NLP will play an imperative role in shaping human interaction with technology and processing information.  

Embracing NLP and honing related skills with free NLP training is an excellent way to stay at the forefront of this transformative field and secure rewarding opportunities in the dynamic world of AI and language processing. 

Yes, NLP is in high demand. The field is rapidly growing, and there is a high demand for skilled NLP professionals as well. This is probably because NLP can be used to solve a wide variety of problems, like extracting insights from data, automating tasks, and creating natural language interfaces.

As businesses continue to adopt AI-driven solutions, the need for skilled NLP experts will only grow. This makes NLP an exciting and rewarding career path for those interested in the intersection of technology and language. 

What Learners Are Saying

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Emma Dupont Data Analyst

Enrolling in the NLP free course online was a smart investment. I was able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood. Learning isn't about being better at your job: it's so much more than that. 

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Yuki Tanaka Financial Analyst

Brilliant explanation, sticking with basics most of the time but not wasting time unnecessarily in simple explanations. Also I got to explore the important areas and understand the code with utmost clarity. Theoretical explanation was also on point. Every video feels like a skill being added and doesn't include unnecessary information. 

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Rafael Ramos Front-End Developer

As a new developer, I was looking for a way to learn more about the practical applications of NLP. This course was perfect for me to do that. The videos showed how NLP can be used to solve real-world problems. I learned a lot about how to use NLP in my work. 

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Matej Novak Software Developer

This course made it easy to understand the basics. It also helped me learn more about the latest trends in NLP. I enjoyed this course. The videos and quizzes helped, and I feel like I'm now up-to-date on the latest developments in the field. I learned a lot about NLP, and I'm now confident of these skills to use them professionally.  

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Nikita Bharti Student

I'm not a technical person, but I was able to follow along with this course thanks to the on-demand videos. I also appreciated the fact that the course included a variety of recall quizzes and other exercises, which helped me to better my understanding of NLP. I would highly recommend it. 

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Maria Fernandez Business Analyst

I was a complete beginner to NLP, but this course made it easy to understand the basics. I enjoyed this course. It was well-organized and easy to follow. I learned a lot about NLP, and I'm now confident that I can use these skills in my work. I would recommend this course to others.