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Machine Learning Engineering R&D Applications

12 Modules · 95 Lessons

Recommended resources

Module 2

Mathematics for Implementing ML Models

Module 3

Digital Signal Processing in Python

Module 4

Reliable PyTorch Experimentation

Module 5

Core Neural Architectures for Speech Enhancement and Separation

Module 6

Python DSA Interview Track: Trees, Graphs, and Dynamic Programming

Module 7

Acoustics and Multichannel Audio Modeling

Module 8

Speech Recognition, Representations, and Foundation Models

Module 9

Generative Modeling for Speech and Voice

Module 10

Research Reasoning and Experimental Evaluation

Module 11

Audio ML Systems, Streaming Inference, and Efficiency

Module 12

Capstone Evidence and Job Interview Readiness