Opleiding: AI+ Audio Practitioner™

Formerly known as AI+ Audio™<br> <br> Experience the power of AI in Audio to reinvent music production, elevate sound design, and craft immersive auditory experiences.

• Empower Audio Innovation with AI: Creative, Practical, Transformative
• Beginner-Friendly Learning: Perfect for newcomers eager to explore AI-powered audio, covering essential concepts with ease
• Comprehensive Skill Building: Includes speech processing, sound enhancement, voice synthesis, and real-world audio AI applications
• Industry-Ready Expertise: Understand how AI is reshaping music, media, entertainment, and communication sectors
• Hands-On Direction: Provides practical frameworks and guided exercises to help you create, analyse, and optimise audio using AI

• 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

• TensorFlow Audio Recognition
• PyTorch Sound Classification
• Librosa
• OpenAI Jukebox
• Google Magenta Studio
• Audacity AI Plugins
• Adobe Podcast AI Tools
• AIVA
• Wav2Vec
• SpeechBrain
• JUCE Framework
• FL Studio with AI Integrations
• Logic Pro Smart Tools
• Sonible Smart EQ
• Spotify Audio Analysis API
• NVIDIA Riva Speech SDK
• Deep Learning for Audio Toolkit
• AudioLDM
• Sound Design Automation Tools

Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam

Access to all materials and exams is provided for 365 days after delivery.