Python Programming with Machine Learning
- Python syntax & keywords
- Variables & data types
- Control flow (if, loops)
- Functions & debugging
- Data structures (list, tuple, dict, set)
- OOP concepts
- File handling
- Arrays & linked lists
- Stacks & queues
- Trees & graphs
- Searching algorithms
- Sorting algorithms
- Recursion
- Time & space complexity (Big O)
- NumPy arrays & operations
- Indexing, slicing & reshaping
- Statistical & linear algebra functions
- Pandas Series & DataFrames
- Data cleaning & transformation
- Grouping & aggregation
- Merging & joining data
- Matplotlib basics
- Line, bar & scatter plots
- Histograms & pie charts
- Customizing graphs
- Seaborn visualizations
- Statistical plotting
- Data preprocessing
- Feature scaling & encoding
- Statistics & probability
- Supervised learning algorithms
- Unsupervised learning
- Model evaluation metrics
- scikit-learn workflows
- KNN, SVM, Decision Trees
- Random Forest & PCA
- Regression & classification
- Introduction to Deep Learning
- CNN & RNN basics
- Real-time ML projects
- End-to-end ML pipeline
