What are the prerequisites?

You needbasic programming knowledge (Python), an understanding ofaudio signal processing, and familiarity withmachine learning fundamentals.

What key skills will I gain?

Speech-to-Text (ASR), Text-to-Speech (TTS), audio enhancement, noise reduction, voice emotion detection,andethical voice AI practices.

What tools will I learn to use?

You'llwork withPython libraries (Librosa,PyAudio), TensorFlow,and commercial APIs likeDeepgram, IBM Watson Tone Analyzer,andKrisp/Adobe Enhance Speech.

Does the course cover deep learning for audio?

Yes, a dedicated module covers usingCNNs, RNNs, and Transformer modelsto analyze audio and build ML models for sound and speech tasks.

Will I build an application?

Yes, you will gain hands-on experience building aSpeech-to-Text modelwith TensorFlow, performingemotion detection, and cleaning noisy audio.

What is covered in the ethics module?

The module addressesvoice deepfakes, cloning risks, data privacy (GDPR compliance),and strategies to mitigatealgorithmic biasin audio systems.

What industry applications are covered?

Case studies includeAl-powered music generation, medical record transcription,andpersonalized hearing aid adaptationusing AI.

What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

AI for Audio and Music

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AI for Audio and Music

Instructor: AI CERTs Team

Included with

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8 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

4 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

8 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

4 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Enhance & Clean Audio:Use AI to reduce noise, improve clarity, and enhance audio using ML-based restoration and speech cleanup techniques.
Build Speech & Voice Systems:Apply ASR/TTS tools to convert speech to text, generate synthetic voices & power intelligent voice-driven applications.
Apply Deep Learning for Sound:Use CNNs, RNNs, and transformers to analyze audio, detect emotions, and build ML models for speech and music tasks.
Capstone Project:Create and deploy an AI audio application such as speech transcription, audio enhancement, or emotion detection.

Skills you'll gain

Tools you'll learn

Tensorflow

Details to know

Shareable certificate

Add to your LinkedIn profile

See how employees at top companies are mastering in-demand skills

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There are 8 modules in this course

Sound is no longer just heard - it’s understood, generated, enhanced, and personalized by AI. From voice assistants and smart speakers to automated mixing, voice cloning, and adaptive audio for AR/VR, the future of sound is intelligent and interactive.

The AI for audio and music certification introduces you to the fundamentals of AI-driven audio processing and modern speech technologies, blending theory with hands-on practice. You’ll explore how machines listen, analyze, and generate sound using signal processing, machine learning, and neural networks — and how these technologies power real-world applications in media, gaming, accessibility, customer experience, and immersive systems. Through guided labs, you’ll work with Python, Librosa, Hugging Face speech models, Audacity, and no-code AI tools to build audio enhancement pipelines, speech-to-text models, voice synthesis demos, and real-time intelligent audio workflows. You’ll also learn evaluation techniques, ethics for voice AI, copyright considerations for generated audio, and best-practice guidelines for transparent and responsible AI usage. By the end of this program, you'll be able to: Build basic AI-powered audio and speech prototypes Enhance sound quality and remove noise using ML Create simple TTS/voice applications Apply audio AI in creative, business, and product workflows.

This module covers a quick summary of what the certification is going to cover from start to finish. Here is the brief about the structure of the overall certification: Each of our certifications follows a consistent, multimodal structure to provide a flexible learning experience. The content is available across four formats: eBooks: In-depth written material for focused learning. Audiobooks: Audio version of the eBook, perfect for learning on the go. Podcasts: Engaging audio content to reinforce key concepts. Videos: Modular video chunks, each covering a specific topic. The names of the eBooks, Audiobooks, and Podcasts are the same, ensuring you can seamlessly switch between formats without losing track of the content. Videos are divided into bite-sized modules for easier consumption, and all content across these mediums is consistent, so no matter which format you choose, the information remains the same. This gives you the freedom to learn in the way that works best for you.

What's included

8 videos1 assignment2 plugins

8 videosTotal 106 minutes

Course Introduction5 minutes
Audiobook: Module 01: Introduction to AI and Sound55 minutes
Podcast: Module 01: Introduction to AI and Sound26 minutes
1.1 What is AI?4 minutes
1.2 AI in Daily Life: Audio Examples3 minutes
1.3 Basics of Sound Waves, Amplitude, Frequency5 minutes
1.4 Digital Audio Fundamentals3 minutes
1.5 Case Study: AI Tool for Audio4 minutes

1 assignmentTotal 30 minutes

Quiz 130 minutes

2 pluginsTotal 30 minutes

Module 01: Introduction to AI and Sound15 minutes
ACTIVITY: FlipCard15 minutes

What's included

11 videos1 reading1 assignment2 plugins

11 videosTotal 337 minutes

Audiobook: Module 02: Harnessing AI Across Audio Domains217 minutes
Podcast: Module 02: Harnessing AI Across Audio Domains74 minutes
2.1 AI For Audio Enhancement and Restoration6 minutes
2.2 Audio Super-Resolution And Upscaling5 minutes
2.3 Real-World Applications: Podcasts, Broadcasts, And Audio Archives5 minutes
2.4 AI For Audio Accessibility And Personalization6 minutes
2.5 AI in Speech and Voice Technologies3 minutes
2.6 Synthetic Voice Generation And Voice Cloning5 minutes
2.7 Emotion and Intent Detection in Speech6 minutes
2.8 Popular Audio Libraries: Librosa and Pyaudio5 minutes
2.9 Use Case and Case Study6 minutes

1 readingTotal 10 minutes

Hands - On10 minutes

1 assignmentTotal 30 minutes

Quiz 230 minutes

2 pluginsTotal 30 minutes

Module 02: Harnessing AI Across Audio Domains15 minutes
ACTIVITY: Tab15 minutes

What's included

9 videos1 reading1 assignment2 plugins

9 videosTotal 224 minutes

Audiobook: Module 03: Machine Learning and AI for Audio132 minutes
Podcast: Module 03: Machine Learning and AI for Audio58 minutes
3.1 Machine Learning Models for Audio Applications5 minutes
3.2 Audio Classification and Music Generation5 minutes
3.3 Deep Learning and Advanced AI Techniques for Audio4 minutes
3.4 Audio-Specific Architectures: CNNs, RNNs, Transformers5 minutes
3.5 Transfer Learning in Audio AI5 minutes
3.6 Use Case: Speech-to-Text Transcription for Medical Records4 minutes
3.7 Case Study: AI-powered Music Generation with Deep Learning6 minutes

1 readingTotal 10 minutes

Hands - On10 minutes

1 assignmentTotal 30 minutes

Quiz 330 minutes

2 pluginsTotal 30 minutes

Module 03: Machine Learning and AI for Audio15 minutes
ACTIVITY: Problem Statement15 minutes

What's included

8 videos1 assignment2 plugins

8 videosTotal 228 minutes

Audiobook: Module 04: Speech Recognition and Text-to-Speech147 minutes
Podcast: Module 04: Speech Recognition and Text-to-Speech52 minutes
4.1 Fundamentals of Speech Recognition and Phonetics4 minutes
4.2 API-based ASR Solutions5 minutes
4.3 Building Custom ASR Models with Transformers5 minutes
4.4 Introduction to Text-to-Speech (TTS) and Voice Cloning 6 minutes
4.5 Use Case: Automating Meeting Transcriptions with Google Speech-to-Text API3 minutes
4.6 Case Study: Custom Transformer-based ASR Model for Multilingual Customer Support4 minutes

1 assignmentTotal 30 minutes

Quiz 430 minutes

2 pluginsTotal 30 minutes

Module 04: Speech Recognition and Text-to-Speech15 minutes
ACTIVITY: True False15 minutes

What's included

7 videos1 reading1 assignment2 plugins

7 videosTotal 137 minutes

Audiobook: Module 05: Audio Enhancement and Noise Reduction74 minutes
Podcast: Module 05: Audio Enhancement and Noise Reduction41 minutes
5.1 Common Audio Issues5 minutes
5.2 Noise Reduction Algorithms and Real-time Audio Enhancement Techniques5 minutes
5.3 AI Tools for Audio Cleaning4 minutes
5.4 Use Case: Enhancing Audio Quality for Remote Work Calls Using AI Noise Reduction4 minutes
5.5 Case Study: Krisp’s AI-powered Noise Cancellation in Podcast Production5 minutes

1 readingTotal 10 minutes

Hands - On10 minutes

1 assignmentTotal 30 minutes

Quiz 530 minutes

2 pluginsTotal 30 minutes

Module 05: Audio Enhancement and Noise Reduction15 minutes
ACTIVITY: Scenario Activity15 minutes

What's included

7 videos1 reading1 assignment2 plugins

7 videosTotal 201 minutes

Audiobook: Module 06: Emotion and Sentiment Detection from Audio122 minutes
Podcast: Module 06: Emotion and Sentiment Detection from Audio59 minutes
6.1 Introduction to Emotion Detection4 minutes
6.2 AI Models for Emotion Detection: RNNs, LSTMs, and CNNs4 minutes
6.3 Challenges: Bias, Multilingual Contexts, Reliability5 minutes
6.4 Use Case: Enhancing Customer Service with Emotion Detection from Speech3 minutes
6.5 Case Study: IBM Watson Tone Analyzer for Real-Time Emotion Recognition3 minutes

1 readingTotal 10 minutes

Hands - On10 minutes

1 assignmentTotal 30 minutes

Quiz 630 minutes

2 pluginsTotal 30 minutes

Module 06: Emotion and Sentiment Detection from Audio15 minutes
ACTIVITY: Short Answer15 minutes

What's included

7 videos1 reading1 assignment2 plugins

7 videosTotal 173 minutes

Audiobook: Module 07: Ethical and Privacy Considerations96 minutes
Podcast: Module 07: Ethical and Privacy Considerations58 minutes
7.1 Deepfake and Voice Cloning Risks4 minutes
7.2 Privacy and Data Security4 minutes
7.3 Bias and Fairness in Audio AI4 minutes
7.4 Use Case: Implementing Ethical Voice Data Collection and Consent Management3 minutes
7.5 Case Study: Addressing Bias and Privacy in Audio AI under GDPR Compliance4 minutes

1 readingTotal 10 minutes

Hands - On10 minutes

1 assignmentTotal 30 minutes

Quiz 730 minutes

2 pluginsTotal 30 minutes

Module 07: Ethical and Privacy Considerations15 minutes
ACTIVITY: Accordion15 minutes

What's included

7 videos1 assignment2 plugins

7 videosTotal 176 minutes

Audiobook: Module 08: Advanced Applications and Future Trends109 minutes
Podcast: Module 08: Advanced Applications and Future Trends45 minutes
8.1 Sound Event Detection and Classification5 minutes
8.2 Audio Search and Indexing4 minutes
8.3 Innovations: Multimodal AI, Edge Computing, and 3D Audio5 minutes
8.4 Emerging Careers in Audio AI4 minutes
Course Summary5 minutes

1 assignmentTotal 30 minutes

Quiz 830 minutes

2 pluginsTotal 30 minutes

Module 08: Advanced Applications and Future Trends15 minutes
ACTIVITY: Multiple Response15 minutes

Instructor

AI CERTs Team

AI CERTs

57 Courses29,595 learners

Offered by

AI CERTs

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Frequently asked questions

The certification focuses on integrating AI withaudio technologies, covering speech recognition, processing, machine learning for sound, and AI-driven audio enhancement.

It'sa1-day intensive programwith hands-on labs, designed for quick mastery of AI audio workflows.

Audio engineers, data scientists, and tech professionalsfocused on audio-related AI solutions across media, communication, and entertainment.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

AI for Audio and Music

AI for Audio and Music

What you'll learn

Skills you'll gain

Tools you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

There are 8 modules in this course

Module 01: Introduction to AI and Sound

What's included

Module 02: Harnessing AI Across Audio Domains

What's included

Module 03: Machine Learning and AI for Audio

What's included

Module 04: Speech Recognition and Text-to-Speech

What's included

Module 05: Audio Enhancement and Noise Reduction

What's included

Module 06: Emotion and Sentiment Detection from Audio

What's included

Module 07: Ethical and Privacy Considerations

What's included

Module 08: Advanced Applications and Future Trends

What's included

Instructor

Offered by

Explore more from Music and Art

AI Sound Generation for Business Communication

Creative AI: Sound, Music and Interaction

Transform Audio: Extract Features & Augment Models

Generative AI for Audio and Images: Models and Applications

Why people choose Coursera for their career

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

Open new doors with Coursera Plus

Advance your career with an online degree

Join over 3,400 global companies that choose Coursera for Business

Frequently asked questions

What is this course about?

How long is the program?

Who is the target audience?

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