Python AI & ML
In order for students to earn this badge they must show general understanding and implementation of the following items:
- Data Manipulation with Pandas
- Data Visualization with Python
- Intro to Machine Learning
- Train Test Split and K-fold Cross Validation
- K-nearest Neighbors
- Decision Trees
- Logistic Regression
- Regularization with Linear Regression
- Sampling with and without Replacement
- Bagged Trees and Random Forests
- Feature Selection
- K-Means
- Hierarchical Clustering
- Principal Component Analysis
- NLP
- NLP with NLTK
- Bag of Words, n-grams, TF-IDF
- NLP for Finance
- Synthetic Data
- Deep Learning
- Reinforcement Learning
- Deep Learning and Natural Language Processing
- Theory of LLMs
- PyTorch
- Retrieval-Augmented Generation
![Image](/images/2024/06/21/aimlpython.png)