From 09ba4a66a61337e22f6caa7585064fa7a0d9d478 Mon Sep 17 00:00:00 2001 From: Caitlin Malloch Date: Wed, 22 Oct 2025 13:28:13 -0700 Subject: [PATCH] Enhance AI-ML Roadmap with detailed learning topics Expanded the AI-ML roadmap with detailed beginner, intermediate, and advanced topics including goals and specific skills to learn. --- Domains/AI-ML/Roadmap.md | 42 +++++++++++++++++++++++++++++++++++++++- 1 file changed, 41 insertions(+), 1 deletion(-) diff --git a/Domains/AI-ML/Roadmap.md b/Domains/AI-ML/Roadmap.md index 0105117f..c48bbc45 100644 --- a/Domains/AI-ML/Roadmap.md +++ b/Domains/AI-ML/Roadmap.md @@ -1,2 +1,42 @@ # AI-ML Roadmap -Beginner → Intermediate → Advanced \ No newline at end of file +Beginner → Intermediate → Advanced + +This roadmap is a suggested plan for learning Artificial Intelligence and Machine Learning skills, including specific topics and areas of interest that can have separate files added to expand on in this folder. + + +## Beginner: Foundation Skills + +### Goal +Learn the basics of machine learning and AI, building confidence in the use of Python coding skills, basic data analysis, and visualization skills + +### Topics +- Python Fundamentals: focus on basic Python syntax, variables, loops, functions, NumPy +- Pandas Library: importing and cleaning data +- Visualization Libraries: Matplotlib and Seaborn +- Machine Learning: basics of supervised and unsupervised learning, model basics +- Model Training: test/train split, linear regression, logistic regression +- Evaluation: accuracy, precision, recall, F1, confusion matrix + +## Intermediate: Applied Machine Learning + +### Goal +Move beyond basic skills into model performance and testing, and engineering skills. + +### Topics +- Feature Engineering: scaling, domain knowledge +- Pipelines and Cross-Validation: `Pipeline`, `GridSearchCV` +- Model Comparison: Random Forest, SVM, KNN +- Data Leakage and Validation: prevent overfitting and leakage traps +- Deep Learning: TensorFlow, PyTorch +- Natural Language Processing (NLP) + +## Advanced: Production and Responsible AI + +### Goal +Building competency with deploying, monitoring and scaling machine learning systems, with an understanding of ethics. + +### Topics +- Model Deployment +- MLOps Concepts: CI/CD, versioning +- Bias: identify and mitigate bias in models +- Privacy and Governance: secure data handling