Customer churn predictor
Built end to end, reviewed by a mentor and added to your portfolio.
AI & ML course
Machine Learning & Deep Learning
Go from data to deployed model: classic machine learning, then neural networks for vision and language.
4 monthsIntermediateClassroom + Live online
Overview
Course at a glance
Duration4 months
LevelIntermediate
ModeClassroom + Live online
Career rolesML Engineer, Data Scientist, Computer Vision Engineer
Curriculum
What you will learn
Module by module.
Module 01Data handling
Pandas, visualisation, cleaning and feature engineering.
Module 02Supervised learning
Linear and logistic regression, trees, random forests, gradient boosting.
Module 03Unsupervised learning
Clustering, dimensionality reduction and anomaly detection.
Module 04Neural networks
Backpropagation, optimisers, regularisation and PyTorch basics.
Module 05Computer vision
CNNs, transfer learning, object detection fundamentals.
Module 06Sequence models
Text classification, embeddings and an introduction to transformers.
Learning outcomes
- Clean data and engineer useful features
- Choose, train and tune the right model
- Build CNNs and sequence models in PyTorch
- Explain results with clear metrics
Tools & technologies
Pythonscikit-learnPyTorchOpenCVJupyter
Projects
Projects you will build
Defect detection from images
Built end to end, reviewed by a mentor and added to your portfolio.
Movie review sentiment model
Built end to end, reviewed by a mentor and added to your portfolio.
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