Artificial Intelligence and Machine Learning Courses

AI+ Audio - Self-paced

  • Length 365 days access
  • Inclusions Online exam
Course overview
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Why study this course

The AI+ Audio course teaches professionals to integrate AI with audio technologies. It covers speech recognition, audio processing, and machine learning for sound analysis and enhancement. Participants gain hands-on experience with AI audio tools, demonstrating proficiency to innovate in communication and digital media. Ideal for audio engineers and data scientists.

Exam and certification

This course prepares students for the corresponding certification. The exam/assessment is completed online and provided as part of the course content.

The exam is:

  • 90 minutes

  • 50 multiple choice / multiple response questions

  • Pass mark is 35 out of 50 (i.e. 70%)

  • Online via AI Proctoring platform

Course availability update

Lumify Work is actively monitoring demand for this course. It is currently offered as a self-paced eLearning course and includes the certification exam. If you're interested in joining a waitlist for future instructor-led training — or exploring options for a tailored delivery for your organisation — please contact us. Your feedback helps shape our activation roadmap.

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What you’ll learn

This course is designed to teach participants how to:

  • Automates tasks like transcription and audio cleanup

  • Implements advanced AI for noise reduction and personalised audio to improve user experience

  • Enables rapid development of next-generation features such as generative AI and edge computing

  • Uses emotion detection for smarter customer support and actionable insights

  • Mitigates risks related to voice deepfakes and ensures data privacy and fairness in compliance with GDPR


AI CERTs Authorized Training Partner Platinum logo Oct 2025

AI CERTs at Lumify Work

AI CERTs® stands at the forefront of AI and blockchain certification, offering world-class programs that prepare individuals to lead in these rapidly growing fields. AI CERTs courses and certifications are vendor agnostic and designed to bridge the gap between theoretical knowledge and practical application, ensuring learners are equipped to make an immediate impact in their careers.
Lumify Work is a Platinum Authorized Training Partner for AI CERTs in Australia, New Zealand, and the Philippines.


Who is the course for?

This course is intended for:

  • Media professionals

  • Product managers

  • Audio engineers

  • Speech Recognition Developers (ASR)


Course subjects

Module 1: Introduction to AI and Sound

  • What is AI?

  • AI in Daily Life: Audio Examples

  • Basics of Sound Waves, Amplitude, Frequency

  • Digital Audio Fundamentals

Module 2: Harnessing AI Across Audio Domains

  • AI for Audio Enhancement and Restoration

  • AI for Audio Accessibility and Personalisation

  • AI in Speech and Voice Technologies

  • Popular Audio Libraries: Librosa, PyAudio

  • Use Case: AI-Driven Real-Time Captioning and Translation for Live Events

  • Case Study: Personalised Hearing Aid Adaptation Using AI and Smart Earbuds

  • Hands-on: Voice Emotion Detection Using Deepgram's Voice AI Platform

Module 3: Machine Learning & AI for Audio

  • Machine Learning Models for Audio Applications

  • Deep Learning & Advanced AI Techniques for Audio

  • Audio-Specific Architectures: CNNs, RNNs, Transformers

  • Transfer Learning in Audio AI

  • Use Case: Speech-to-Text Transcription for Medical Records

  • Case Study: AI-Powered Music Generation with Deep Learning

  • Hands-on: Build a Speech-to-Text Model Using TensorFlow

Module 4: Speech Recognition and Text-to-Speech

  • Fundamentals of Speech Recognition & Phonetics

  • API-Based ASR Solutions

  • Building Custom ASR Models with Transformers

  • Introduction to TTS & Voice Cloning

  • Use Case: Automating Meeting Transcriptions with Google Speech-to-Text API

  • Case Study: Custom Transformer-Based ASR Model for Multilingual Customer Support

  • Hands-on: Transcribe Audio with an ASR API; Generate Speech from Text

Module 5: Audio Enhancement & Noise Reduction

  • Common Audio Issues

  • AI-Based Noise Filtering & Enhancement

  • Use Case: Enhancing Audio Quality for Remote Work Calls Using AI Noise Reduction

  • Case Study: Krisp’s AI-Powered Noise Cancellation in Podcast Production

  • Hands-on: Use Krisp or Adobe Enhance Speech to Clean Noisy Audio

Module 6: Emotion & Sentiment Detection from Audio

  • Introduction to Emotion Detection

  • AI Models for Emotion Detection: RNNs, LSTMs, CNNs

  • Challenges: Bias, Multilingual Contexts, Reliability

  • Use Case: Enhancing Customer Service with Emotion Detection from Speech

  • Case Study: IBM Watson Tone Analyser for Real-Time Emotion Recognition

  • Hands-on: Use IBM Watson Tone Analyser or Similar APIs to Analyse Speech Samples

Module 7: Ethical and Privacy Considerations

  • Deepfakes and Voice Cloning Risks

  • Privacy and Data Security

  • Bias and Fairness in Audio AI

  • Use Case: Implementing Ethical Voice Data Collection and Consent Management

  • Case Study: Addressing Bias and Privacy in Audio AI Under GDPR Compliance

  • Hands-on: Detect Fake Audio Clips; Create an Ethical AI Checklist

Module 8: Advanced Applications & Future Trends

  • Sound Event Detection & Classification

  • Audio Search and Indexing

  • Innovations: Multimodal AI, Edge Computing, 3D Audio

  • Emerging Careers in Audio AI


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


Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.


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