Python
- Structure of a program
- Data Types, Operators & Control
- Constructs
- Encapsulation, Object creation
- Internals
- OO Features: Inheritance,
- Polymorphism, Special Methods
- Collections: Lists, Sets, Dictionaries
- Magic methods, Object usage,
- Library usage, IO
- Modules
- Execution model
- Exceptions
- Project – App Development
- Python for ML:
- NumPy
- Pandas
- Matplotlib
Machine Learning Fundamentals & Math Foundations
- Statistics &Probability
- Linear Algebra
- Multi-Variate Calculus
- Optimization
- ML Foundations:
- Supervise ML:
- Classification & Regression Models:
- Linear Models
- Polynomial Models
- Regularised Models
- Support Vector Machines(SVM)
- Decision Trees
- K Nearest Neighbors
- Naïve Bayes
- Ensemble Models:
- Voting & Bagging Models
- Random Forests
- Boosting
- Unsupervised ML
- K Means Clustering
- Gaussian Mixture Model
- Dimensionality Reduction
- Principal Component
- Analysis (PCA)
