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