Course Features
Duration
4 hours
Delivery Method
Online
Available on
Limited Access
Accessibility
Mobile, Desktop, Laptop
Language
English
Subtitles
English
Level
Intermediate
Teaching Type
Self Paced
Video Content
4 hours
Course Description
Highlights
Pedagogy
Top 30 Percentile
Rating & Reviews
Top 30 Percentile
Parameters
Pedagogy
Acquire all major Python Programming skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in Python Programming, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.
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Rating & Reviews
This highly acclaimed course is among the top-rated in Python Programming, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in Python Programming.
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Course Overview
Virtual Labs
International Faculty
Post Course Interactions
Hands-On Training,Instructor-Moderated Discussions
Skills You Will Gain
Prerequisites/Requirements
Intermediate Python
Introduction to Natural Language Processing in Python
Supervised Learning with scikit-learn
What You Will Learn
Learn to load, transform, and transcribe human speech from raw audio files in Python
You'll start by seeing what raw audio looks like in Python. And then finish by working through an example business use case, transcribing and classifying phone call data
You'll learn the first steps to working with speech files by converting two different audio files into soundwaves and comparing them visually
In this section, you'll learn how to use the SpeechRecognition library to easily start converting the spoken language in your audio files to text
Then you'll perform sentiment analysis using NLTK, named entity recognition using spaCy and text classification using scikit-learn on the transcribed text
Course Instructors
Course Reviews
Average Rating Based on 3 reviews
100%