AI for Audio and Music

AI for Audio and Music

Instructor: AI CERTs Team

Access provided by La Dreamer & Daisy Helping Hands Foundation Inc

9 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

9 hours to complete

Flexible schedule

Learn at your own pace

9 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

9 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Create Music with AI
Use AI tools for composition, arrangement, melody ideas, and creative sound exploration.
Improve Audio Quality
Apply AI for mastering support, noise reduction, vocal cleanup, mixing preparation, and instrument enhancement.
Build Faster Editing Workflows
Use AI to simplify repetitive tasks such as stem separation, transcription, audio cleanup, and basic editing.
Design New Sounds and Samples
Explore AI-assisted sound design, sample creation, and generative music tools to develop unique textures and styles.

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

8 assignments

Taught in English

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There are 9 modules in this course

AI is changing how music is created, edited, mixed, and produced. The AI for Audio and Music Certification is a practical, beginner-friendly course designed for musicians, producers, audio engineers, sound designers, and creators who want to use AI tools with confidence.

The course covers real-world creative workflows, including vocal cleanup, stem separation, mastering support, sound design, sample creation, and AI-assisted composition. You’ll learn how to use AI to speed up production, improve sound quality, and experiment with new creative ideas while staying in control of your artistic direction. Through guided exercises, you’ll explore how AI can support composition, editing, audio enhancement, vocal processing, mixing preparation, and creative experimentation. The course helps you build faster, more efficient workflows for real audio and music projects. By the end, you’ll be ready to use AI across music creation, audio editing, and sound design to produce cleaner, sharper, and more production-ready work. Enroll today and start building practical AI skills for modern audio production.

Provides an overview of Artificial Intelligence (AI) concepts and their role in audio technologies. This module introduces the fundamentals of sound, digital audio processing, AI-driven audio systems, and how intelligent technologies are transforming the way audio is created, analyzed, and experienced.

What's included

6 videos1 assignment1 plugin

Explores the diverse applications of AI across different audio fields, including music production, broadcasting, entertainment, healthcare, education, and communication. Learners will understand how AI-powered tools enhance audio creation, analysis, automation, and personalization.

What's included

9 videos1 assignment1 plugin

9 videosTotal 46 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 assignmentTotal 30 minutes

Quiz 230 minutes

1 pluginTotal 5 minutes

Activity: Tab5 minutes

Introduces machine learning techniques used in audio processing and analysis. This module covers audio data representation, feature extraction, deep learning models, neural networks, and how AI systems learn patterns to perform tasks such as classification, generation, and recognition.

What's included

7 videos1 assignment1 plugin

7 videosTotal 34 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 assignmentTotal 30 minutes

Quiz 330 minutes

1 pluginTotal 5 minutes

Activity: Problem Statement5 minutes

Examines AI technologies behind speech-to-text and text-to-speech systems. Learners will explore automatic speech recognition, voice synthesis, virtual assistants, voice interfaces, and real-world applications of AI-powered speech technologies.

What's included

6 videos1 assignment1 plugin

6 videosTotal 28 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

1 pluginTotal 5 minutes

Activity: True or False5 minutes

Focuses on AI-based methods for improving audio quality. This module covers noise removal, speech enhancement, audio restoration, echo cancellation, and techniques used to create clearer and more immersive audio experiences across various environments.

What's included

5 videos1 assignment1 plugin

5 videosTotal 22 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 assignmentTotal 30 minutes

Quiz 530 minutes

1 pluginTotal 5 minutes

Activity: Scenario5 minutes

Explores how AI analyzes vocal patterns, tone, pitch, and speech characteristics to identify emotions and sentiments. Learners will understand applications in customer experience, healthcare, human-computer interaction, and behavioral analysis while recognizing the challenges of accurate emotion interpretation.

What's included

5 videos1 assignment1 plugin

5 videosTotal 20 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 assignmentTotal 30 minutes

Quiz 630 minutes

1 pluginTotal 5 minutes

Activity: Text Entry5 minutes

Addresses responsible AI use in audio technologies by examining privacy, consent, data security, voice identity protection, bias, transparency, and ethical challenges associated with collecting and processing audio information.

What's included

5 videos1 assignment1 plugin

5 videosTotal 19 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 assignmentTotal 30 minutes

Quiz 730 minutes

1 pluginTotal 5 minutes

Activity: Accordian 5 minutes

Explores emerging AI innovations in audio, including generative audio, AI-assisted music creation, intelligent voice systems, real-time audio processing, and future developments shaping the next generation of audio technologies.