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Free Text Classification in NLP Course

Text Classification in NLP

star 4.59  Beginner level 2.25 learning hrs 2.6K+ Learners

Text Classification in NLP online free course lessons connect datasets, metrics, and analysis choices with practical examples, so the subject feels useful for analytics projects, not just theory.

Instructor:

Ms. Sowmya Vivek

Text Classification in NLP

star 4.59  Beginner level 2.25 learning hrs 2.6K+ Learners
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Skills you will gain

Text classification

NLP

Text classification models

Key Highlights

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About this course

This free text classification in nlp course is built for analytics, data science, and business learners who want the topic explained with context and usable examples. The course introduces data preparation, model thinking, visual analysis, and evaluation in a way that shows how the pieces work together. Instead of treating text classification in nlp as a list of terms, it explains what to look for, how to reason through common tasks, and why the subject appears in real projects, teams, or business decisions.


The course is a good fit if you want to turn data, models, or analysis outputs into clearer decisions. You can use it to prepare for assignments, interviews, workplace conversations, or a first hands-on project depending on your goal. After finishing, you should be able to explain the core idea of text classification in nlp, recognize when it is relevant, and choose a sensible next step such as practice exercises, deeper tools, related frameworks, or a more advanced course.

Stand out with an industry-recognized certificate

Start learning

10,000+ certificates claimed, get yours today!

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Course outline

Introduction to Text Classification

How does text classification work ?

Python walkthrough - Text classification-Naïve Bayes, Linear classifier, Support vector classifier

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Text Classification in NLP

rating icon 4.59

2.25 Hours

Beginner

Sign up with Email

2.6K+ learners enrolled so far

Get free course content

Master in-demand skills & tools

Test your skills with quizzes

Trusted by 1 Crore+ Learners globally

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Learner reviews of the Free Courses

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Reviewer Profile
Agnesh Reddy Kondam

4.0

★★★ ★ ☆
India
“Learning NLP in a Great Environment: An Enriching Experience Combining Theory with Practical Applications”
Engaging in hands-on projects enhances understanding, from basic text processing to advanced machine learning models like Word2Vec, TF-IDF, and transformer-based architectures. The collaborative atmosphere fosters knowledge-sharing, encouraging students to tackle real-world problems like sentiment analysis and machine translation.
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Reviewer Profile
Vignesh Repala

5.0

★★★★ ★
India
“Growth through Diverse Learning Experiences”
I loved the depth and breadth of learning, especially the blend of theory and hands-on practice. The diverse range of topics kept me engaged and challenged, while the interactive sessions fostered collaboration and critical thinking. The real-world applications made the learning truly impactful.
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Reviewer Profile
MADATHA BHAVANA

5.0

★★★★ ★
India
“Fundamentals of Text Classification in NLP”
Text classification in natural language processing (NLP) involves categorizing text into predefined labels, which helps organize and analyze large volumes of text data. The process begins with a dataset of text samples, each labeled with a category, such as 'spam' or 'not spam.'
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Reviewer Profile
Allapu Srivarshan

4.0

★★★ ★ ☆
India
“A Well-Structured Course with In-Depth Explanations and Practical Quizzes”
This course provided a great balance of theory and hands-on practice, making complex concepts easy to grasp. I especially appreciated the detailed explanations in each topic, which were reinforced through assignments that helped solidify my understanding. The quizzes were well-designed, offering valuable practice in applying the skills learned. Overall, a highly engaging and educational experience!
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Reviewer Profile
NAMALA GOPINATH

5.0

★★★★ ★
India
“Fundamentals of Text Classification in NLP”
The 'Fundamentals of Text Classification in NLP' course provides a comprehensive overview of key concepts, from data collection and preprocessing to feature extraction and model selection. It effectively covers traditional and modern algorithms, offering hands-on experience in training and evaluating models. This course is invaluable for anyone looking to deepen their understanding of text classification techniques and applications in NLP.
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Reviewer Profile
Hriday Bekal

5.0

★★★★ ★
India
“This NLP Course is a Must for Anyone Looking to Build or Enhance Their Skills”
The course content is up-to-date, covering a wide range of topics from basic text processing to advanced techniques like transformer models and sentiment analysis. The real-world examples and projects provided valuable practical experience, helping me apply what I learned to real scenarios.
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Reviewer Profile
CHINTHALA THARUN

5.0

★★★★ ★
India
“Transformative Learning Experience!”
I really enjoyed the depth of the topics covered and how practical the curriculum was. The instructor made complex concepts easy to understand, and the quizzes were engaging and helped reinforce my learning. Overall, the course was well-structured and easy to follow, making it a great learning experience.
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Reviewer Profile
sanket parulekar

5.0

★★★★ ★
India
“NLP Course: A Wonderful Course in Detail”
Natural Language Processing (NLP) is indeed a fascinating and highly useful field within artificial intelligence and computer science. It deals with the interaction between computers and human language, enabling machines to understand, interpret, and respond to human language in a valuable way.
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Reviewer Profile
samala somanath

5.0

★★★★ ★
India
“NLP Enhances Data Analysis by Enabling the Extraction of Insights from Unstructured Text Data”
NLP enhances data analysis by enabling the extraction of insights from unstructured text data, such as customer reviews, social media posts, and news articles. By using text mining techniques, NLP can identify patterns, trends, and sentiments that are not immediately obvious in large datasets. Sentiment analysis enables the extraction of subjective qualities—attitudes, emotions, sarcasm, confusion, or suspicion—from text. This is often used for routing communications to the system or the person most likely to make the next response.
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Reviewer Profile
Neeti Poonia

5.0

★★★★ ★
India
“Brilliant Instructor and the Depth of Concepts”
All the videos were planned topic-wise and very well. Examples and quizzes were the best.
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What our learners enjoyed the most

Our course instructor

instructor img

Ms. Sowmya Vivek

Independent Consultant, Visiting Faculty

Artificial Intelligence Expert

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8.4K+ Learners
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3 Courses
Sowmya is an Independent consultant working on projects on Customer Analytics, Deep Learning & NLP. She is a visiting faculty at Great Learning and a course Instructor at DataCamp USA. Sowmya has 25 years of experience spread across ML modelling, Business Intelligence, Workflow optimisation, Content Management & e-learning content development.

Frequently Asked Questions

Will I receive a certificate upon completing this free course?

Yes, upon successful completion of the course and payment of the certificate fee, you will receive a completion certificate that you can add to your resume.

Is this course free?

Yes, you may enroll in the course and access the course content for free. However, if you wish to obtain a certificate upon completion, a non-refundable fee is applicable.

What will I learn in this free Text Classification in NLP course?

You will study NLP, analytics, datasets, and methods so the topic learningls easier to use in real learning situations. The focus is on useful foundations, not memorizing terms.

Who should start with this Text Classification in NLP course?

This course is useful for learners who want to connect concepts with data-backed decisions and project practice. It starts with the basics, then shows how NLP and analytics connect to practical decisions.

How does Text Classification in NLP help in practical learning?

Text Classification in NLP becomes useful when you can analyze the basics, compare examples, and explain why each step matters. The course keeps those ideas tied to beginner-friendly practice.

What Text Classification in NLP basics should I know before advanced study?

Focus first on NLP, analytics, datasets, and the common mistakes beginners make. These basics make advanced lessons easier to follow later. It keeps the learning practical without adding unrelated admin details.

Can beginners learn Text Classification in NLP online through this course?

Beginners can use the lessons to build a clear starting point for Text Classification in NLP. The flow keeps concepts, examples, and practice connected so online learning learningls structured.

What makes this Text Classification in NLP training useful for projects?

The training helps you connect NLP with analytics and datasets, which is important when turning a lesson into an assignment, portfolio task, or workplace example.

How should I practice after finishing Text Classification in NLP?

After finishing, revisit the core terms, repeat one small example, and explain your steps aloud. Then move into dataset practice, project notebooks, evaluation metrics, and a more advanced analytics or ML course...

What questions does this free Text Classification in NLP course answer for learners?

It answers how Text Classification in NLP works, where it is used, which basics matter first, and how learners can move from definitions to practical examples without getting lost in advanced details.

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