Level 2: Introduction to ML
Advanced Machine Learning architectures and Deep Learning.
Modules6 Sessions
DurationAcademic Year 2
Outcomes4 Skills
Course Overview
For students passing Level 1, we dive into the second half of the ML curriculum and the entirety of Deep Learning. Students shift from standard analysis to profound bio-inspired architectures, tackling K-means clustering, backpropagation, Convolutional Neural Networks (CNNs), and sequence modeling via Transformers.
Tools & Technologies
PyTorchTransformersCNNsScikit
Curriculum
6 ModulesWhat You'll Learn
- A professional certificate in Applied AI Engineering
- Deploy unsupervised clustering algorithms
- Design CNNs for high-accuracy image classification
- Execute architectural transfers on pre-trained models
Prerequisites
- Level 1: Foundation OR Strong Python Experience
Learning Path Flow
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