Natural Language Processing with Deep Learning in Python
Udemy · Lazy Programmer Inc. · Updated
AI Tutor Rating
8.3/10
Duration
12 hours video
Classes
96
Complete guide on deriving and implementing word2vec, GloVe, word embeddings, and sentiment analysis with recursive nets.
Natural Language Processing with Deep Learning in Python on Udemy is a 12-hour video course with 96 lectures that provides a complete guide to foundational NLP techniques. It serves learners aiming to implement core algorithms like word2vec and GloVe from scratch and apply deep learning to tasks such as sentiment analysis. The course focuses on hands-on work with word embeddings and semantic similarity, positioning itself for those with basic Python and machine learning knowledge who want to build practical NLP skills.
What you'll learn in Natural Language Processing with Deep Learning in Python
Our Review of Natural Language Processing with Deep Learning in Python
The course structure is comprehensive, moving from an overview through mastering embeddings and into advanced concepts, culminating in a capstone project. This progression suggests a practical, implementation-focused journey where learners will actively build NLP systems. The teaching format relies entirely on 12 hours of video lectures, which provides a structured walkthrough but demands self-directed application of the concepts presented. The curriculum indicates you will finish with the ability to implement word2vec and GloVe models yourself and construct a sentiment analysis system using deep learning workflows, translating theory into functional code.
The depth appears significant, targeting a learner who wants to understand these algorithms 'from scratch,' which implies mathematical and coding depth beyond high-level API usage. The prerequisite of basic ML suggests this is not an introductory course, but one for practitioners looking to solidify their foundational NLP engineering skills. At its promotional price of $13.99, the course offers substantial content volume and a certificate of completion, representing strong value for a self-paced, skill-specific training module compared to more theoretical or broader alternatives.
Pros and cons of Natural Language Processing with Deep Learning in Python
Pros
- Comprehensive curriculum covering core NLP algorithms like word2vec and GloVe from the ground up
- Clear, practical outcomes focused on implementation and building projects like sentiment analysis
- High content volume with 12 hours of video across 96 lectures for a very low price point
- Includes a certificate of completion, adding formal recognition for the skills learned
- Structured path from fundamentals to a capstone project, providing a complete learning journey
Things to consider
- Requires solid prerequisites in Python and basic machine learning, making it unsuitable for beginners
- Learning format is exclusively video-based, which may not suit all learning styles without supplemental practice
- The depth on advanced concepts may be challenging without prior exposure to deep learning or NLP fundamentals
Who should take Natural Language Processing with Deep Learning in Python?
This course is an ideal fit for the intermediate Python developer or data scientist who understands basic machine learning concepts and now wants to dive deep into the engineering of NLP systems. It's specifically designed for learners whose goal is to implement foundational algorithms like word2vec and GloVe themselves and build practical deep learning models for tasks such as sentiment analysis, rather than just using pre-built libraries.
Course curriculum for Natural Language Processing with Deep Learning in Python
Natural Language Processing with Deep Learning in Python at a glance
| Provider | Udemy |
|---|---|
| Instructor | Lazy Programmer Inc. |
| Level | Intermediate |
| Time to complete | 12 hours video |
| Pricing | $13.99 |
| Certificate | Certificate |
| Prerequisites | Python, basic ML |
Fit
Best for
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The bottom line on Natural Language Processing with Deep Learning in Python
Natural Language Processing with Deep Learning in Python delivers intensive, practical training in core NLP engineering for a remarkably low cost. It is a strong investment for learners with the required Python and ML background who are committed to understanding and building these algorithms from the ground up through a structured, project-based video curriculum.
Natural Language Processing with Deep Learning in Python: frequently asked questions
What exactly will I learn to build in the Natural Language Processing with Deep Learning in Python course?
You will learn to implement word2vec and GloVe models from scratch, work with word embeddings to measure semantic similarity, and build a sentiment analysis system using deep learning techniques, culminating in a capstone project.
What background knowledge do I need before taking this NLP deep learning course?
You need proficiency in Python programming and a basic understanding of machine learning concepts to successfully follow the material in Natural Language Processing with Deep Learning in Python.
Does this Udemy course offer a certificate and is the cost worth it?
Yes, the course offers a certificate of completion. Given its 12 hours of video content focused on practical implementation for around $14, it presents significant value for skill-specific training.
How does this course compare to a typical university module on NLP?
Unlike a broad university module, this course is intensely practical and focused on implementing specific algorithms like word2vec and GloVe from scratch and building a deep learning project, offering hands-on engineering skills over theoretical breadth.
How can I get the most out of this deep learning for NLP course?
To get the most from this course, actively code along with the lectures, ensure your Python and basic ML prerequisites are solid, and thoroughly engage with the capstone project to solidify the implementation skills taught.