AI+ AudioTM
A certification that empowers learners to elevate music production, enhance sound design, and create immersive auditory experiences using AI technologies.
AI+ AudioTM
A certification that empowers learners to elevate music production, enhance sound design, and create immersive auditory experiences using AI technologies.
Why This Certification Matters?
What You'll Learn?
1.1 What is AI?
1.2 AI in Daily Life: Audio Examples
1.3 Basics of Sound Waves, Amplitude, Frequency
1.4 Digital Audio Fundamentals
2.1 AI for Audio Enhancement and Restoration
2.2 AI for Audio Accessibility and Personalization
2.3 AI in Speech and Voice Technologies
2.4 Popular Audio Libraries: Librosa, PyAudio
2.5 Use Case:AI-Driven Real-Time Captioning and Translation for Live Events
2.6 Case Study:Personalized Hearing Aid Adaptation Using AI and Smart Earbuds
2.7 Hands-on: Voice Emotion Detection using Deepgram’s Voice AI Platform
3.1 Machine Learning Models for Audio Applications
3.2 Deep Learning & Advanced AI Techniques for Audio
3.3 Audio-Specific Architectures: CNNs, RNNs, Transformers
3.4 Transfer Learning in Audio AI
3.5 Use Case: Speech-to-Text Transcription for Medical Records
3.6 Case Study: AI-powered Music Generation with Deep Learning
3.7 Hands-on: Build a Speech-to-Text Model Using TensorFlow
4.1 Fundamentals of Speech Recognition & Phonetics
4.2 API-based ASR Solutions
4.3 Building Custom ASR Models with Transformers
4.4 Introduction to TTS & Voice Cloning
4.5 Use Case: Automating Meeting Transcriptions with Google Speech-to-Text API
4.6 Case Study: Custom Transformer-based ASR Model for Multilingual Customer Support
4.7 Hands-on: Transcribe audio with an ASR API; generate speech from text
5.1 Common Audio Issues
5.2 AI-based Noise Filtering & Enhancement
5.3 Use Cases: Enhancing Audio Quality for Remote Work Calls Using AI Noise Reduction
5.4 Case Study: Krisp’s AI-powered Noise Cancellation in Podcast Production
5.5 Hands-on: Use Krisp or Adobe Enhance Speech to clean noisy audio
6.1 Introduction to Emotion Detection
6.2 AI Models for Emotion Detection: RNNs, LSTMs, CNNs
6.3 Challenges: Bias, Multilingual Contexts, Reliability
6.4 Use Case: Enhancing Customer Service with Emotion Detection from Speech
6.5 Case Study: IBM Watson Tone Analyzer for Real-Time Emotion Recognition
6.6 Hands-on: Use IBM Watson Tone Analyzer or similar APIs to analyze speech samples
7.1 Deepfakes and Voice Cloning Risks
7.2 Privacy and Data Security
7.3 Bias and Fairness in Audio AI
7.4 Use Case: Implementing Ethical Voice Data Collection and Consent Management
7.5 Case Study: Addressing Bias and Privacy in Audio AI under GDPR Compliance
7.6 Hands-on: Detect fake audio clips; create an ethical AI checklist
8.1 Sound Event Detection & Classification
8.2 Audio Search and Indexing
8.3 Innovations: Multimodal AI, Edge Computing, 3D Audio
8.4 Emerging Careers in Audio AI
8.1 Sound Event Detection & Classification
8.2 Audio Search and Indexing
8.3 Innovations: Multimodal AI, Edge Computing, 3D Audio
8.4 Emerging Careers in Audio AI
8.1 Sound Event Detection & Classification
8.2 Audio Search and Indexing
8.3 Innovations: Multimodal AI, Edge Computing, 3D Audio
8.4 Emerging Careers in Audio AI
Job Roles & Industry Outlook
Skills You’ll Gain
AI-Driven Music Composition
Audio Signal Processing
Sound Classification and Tagging
Speech and Voice Recognition
Generative Audio Synthesis
Neural Audio Enhancement
Emotion-Based Sound Design
Intelligent Mixing and Mastering
Adaptive Soundscapes for Interactive Media
Real-Time Audio Analysis and Optimization
Tools You’ll Master
Tools You’ll Master
Prerequisites
- Basic programming knowledge – Familiarity with Python or similar languages.
- Understanding of audio signal processing – Know fundamental audio manipulation techniques.
- Machine learning fundamentals – Basic knowledge of algorithms and model training.
- Mathematical proficiency – Comfort with linear algebra and probability concepts.
- Experience with audio software tools – Hands-on use of DAWs or similar tools.
Exam Details
Duration
Passing Score
Format
Delivery Method
Exam Blueprint
Introduction to AI and Sound – 7%
Harnessing AI Across Audio Domains – 15%
Machine Learning & AI for Audio – 15%
Speech Recognition & Text-to-Speech – 15%
Audio Enhancement & Noise Reduction – 12%
Emotion & Sentiment Detection from Audio – 12%
Ethical and Privacy Considerations – 12%
Advanced Applications and Future Trends – 12%
Choose the Format That Fits Your Schedule
What’s Included (One-Year Subscription + All Updates):
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
- Access for Tablet & Phone
Self-Paced Online
● Learn anywhere, anytime, with modular quizzes to track progress
Rp 1.621.000
Group Live Classes
● Join a scheduled, trainer-led online program with fellow learners.
● Supported by modular quizzes to track your progress.
Rp 6.000.000 → Rp 5.500.000
Instructor-led Training
● Private, trainer-led program that starts immediately — set your own schedule, online or offline