IIIProgram
Applied Machine Learning
Classical ML and the math that underwrites it.
Admission
Enrol as a Scholar to enter this Program, keep a record of your progress, and pursue the Certificate in Applied ML (Practitioner tier)..
Enrol in the AcademyNo tuition is configured for this Program. Register your interest and we will write to you when admissions open.
Request information →- 301Course
Linear Algebra for ML
The math the field is written in.
6 lessons·PractitionerVectors and matricesDecompositions - 302Course
Probability for ML
Uncertainty, precisely.
7 lessons·PractitionerProbabilityInference - 303Course
Optimization and Gradient Descent
How models actually learn.
6 lessons·PractitionerThe theoryThe modern toolbox - 304Course
Feature Engineering
The 80% of applied ML.
5 lessons·PractitionerThe craftThe discipline - 305Course
Regression
The most-used model.
5 lessons·PractitionerLinear regressionRegularization - 306Course
Classification
The other half of supervised learning.
6 lessons·PractitionerLogistic regressionTrees and ensembles - 307Course
Neural Networks
The building block of modern AI.
6 lessons·PractitionerThe MLPTraining in practice - 308Course
CNNs
Vision's workhorse.
5 lessons·PractitionerThe primitiveModern vision - 309Course
RNNs and Sequence Models
Before transformers, and after.
3 lessons·PractitionerThe RNN family - 310Course
Transformers (Applied)
The architecture, from scratch.
4 lessons·PractitionerFrom scratch - 311Course
Embeddings and Representation Learning
How meaning becomes math.
4 lessons·PractitionerThe techniques - 312Course
Transfer Learning and Foundation Models
Standing on shoulders.
4 lessons·PractitionerThe paradigm