AI Internship presentations

Here are notebooks for the tools presented each week.

Week 1: Windows Subsystem for Linux (WSL)
Week 2: Bash shell
Week 3: MISE (universal tool version manager)
Week 4: venv (python virtual environments), and pip (python dependency manager)
Week 5: poetry (better python virtual environment and dependency manager)
Week 6: Testing (pytest)
Week 7: jupyter notebooks
Week 8: gradio (for publishing AI projects quickly)
Week 9: How to start a personal AI project
Week 10: Game night GPT (introduction to my personal project that I will use as a teaching tool)
Week 11: Analyze Question-Answers (using the tools you are learning about in the data science course)
Week 12: llamaindex (getting started - llamaindex is a framework for building AI applications)
Week 13: Machine learning principles (quick overview to prepare you for the machine learning course)
Week 14: Evaluation (how to evaluate the quality of your AI outputs)
Week 15: DSPy (getting started - DSPy is a tool for automated prompt optimization)
Week 16: Hyperparameter optimization (using optuna)

Name		Name	Last commit message	Last commit date
Latest commit History 110 Commits
archive_2023		archive_2023
data		data
images		images
.gitignore		.gitignore
.mise.toml		.mise.toml
01_WSL.ipynb		01_WSL.ipynb
02_Bash.ipynb		02_Bash.ipynb
03_mise.ipynb		03_mise.ipynb
04_venv_pip.ipynb		04_venv_pip.ipynb
05_poetry.ipynb		05_poetry.ipynb
06_testing.ipynb		06_testing.ipynb
07_notebooks.ipynb		07_notebooks.ipynb
08_gradio.ipynb		08_gradio.ipynb
08_gradio.py		08_gradio.py
09_how_to_start_a_personal_project.ipynb		09_how_to_start_a_personal_project.ipynb
10_game_night_gpt_intro.ipynb		10_game_night_gpt_intro.ipynb
11_game_night_gpt_analyze_qa.ipynb		11_game_night_gpt_analyze_qa.ipynb
12_llamaindex_getting_started.ipynb		12_llamaindex_getting_started.ipynb
13_machine_learning_principles.ipynb		13_machine_learning_principles.ipynb
14_llamaindex_eval.ipynb		14_llamaindex_eval.ipynb
15_hyperparameter_optimization.ipynb		15_hyperparameter_optimization.ipynb
16_dspy_tutorial.ipynb		16_dspy_tutorial.ipynb
20_RAG_overview.ipynb		20_RAG_overview.ipynb
21_crawling.ipynb		21_crawling.ipynb
22_RAG_splitting.ipynb		22_RAG_splitting.ipynb
23_RAG_querying.ipynb		23_RAG_querying.ipynb
24_RAG_advanced_retrieval.ipynb		24_RAG_advanced_retrieval.ipynb
25_frontend_recommendations.ipynb		25_frontend_recommendations.ipynb
README.md		README.md
requirements-dev.txt		requirements-dev.txt
requirements.txt		requirements.txt

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