PyTorchCNN
Machine LearningAdvanced
Deep Learning & Neural Networks with PyTorch
Learn how modern neural networks work and train your own vision, language and generative models.
48 hrs5 modules9.1K learners
₹6,499₹12,999
Machine Learning IntermediateBestseller
Machine Learning A–Z with scikit-learn
Understand, build and evaluate ML models the right way.
17.3K learners English Updated October 2026
Taught by Rohan Kapoor, Machine Learning Researcher
What you'll learn
- Implement regression, classification and clustering models
- Engineer features and prevent data leakage
- Evaluate with proper metrics and cross-validation
- Tune hyper-parameters and build ML pipelines
- Interpret models with SHAP and permutation importance
About this course
Learn how machine-learning models work, when to use each, and how to evaluate them honestly. Through guided projects you'll build a full ML workflow — from data preparation to tuned, explainable models.
- scikit-learn
- Regression
- Classification
- Feature Engineering
Syllabus overview
6 modules · 52 hrs total. Full lessons are delivered inside the Hyskilled app.
Learning paradigms, bias–variance and the ML workflow.
Requirements
- Python basics
- High-school level maths
Who this is for
- Aspiring ML engineers and data scientists
- Developers pivoting to ML
Your instructor
RK
Rohan Kapoor
Machine Learning Researcher
- 15,700 learners
- 2 courses
Rohan bridges research and practice, with experience in computer vision and NLP. He explains the intuition first, then the math, then the code.
Frequently asked questions
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