2190513 Data Science (ICE) @CU (2025/1)

Syllabus:

Syllabus

Code:

Week01: Intro to Numpy, Pandas

1. Pandas:

2. Pandas with Youtube stat data:

3. (Advanced) Pandas with Youtube stat data:

Week02-03: Data Preparation

1. Impute Missing Value:

2. OneHotEncoder:

3. Outliers - Take Log:

4. Outliers - Remove them with Z-Score:

5. Split Train/Test:

Week04-07: Traditional ML

Week04: Tree-based model, Pipeline, Evaluation

Week05: Regression

Week06: kNN, GridSearch + Clustering

Week07: NN

1. Decision Trees:

2. Linear Regression:

3. Logistic Regression:

4. Neural Network:

5. K Nearest Neighbors (GridSearchCV):

6. SVM:

7. Save and Load Model:

8. K-Means:

9. Market-Basket Analysis:

10. Scikit-learn pipeline:

Week08: Intro to Deep Learning

1. Image classification with CNN (PyTorch Lightning):

2-1. Image classification with EfficientNetV2s (PyTorch Lightning):

2-2. Image classification with EfficientNetV2s (PyTorch Lightning) with TensorBoard:

2-3. Image classification with EfficientNetV2s (PyTorch Lightning) with Weights & Biases:

2-4. Image classification with EfficientNetb0 (Load a Pretrained Model from Hugging Face) (PyTorch Lightning) with Weights & Biases:

3-1. Object detection with YOLOv8 (basic script):

3-2. Object detection with YOLOv8 (custom dataset):

4. Semantic segmentation with deeplabv3 (PyTorch Lightning):

5. Time series Forecasting: Stock Price:

Week09: Webscraping

1. Basic Web Scraping:

2. Wiki Scraping Example:

3. REST API Extraction:

4. Selenium:

Week10: Fast API

1-1. Simple:

1-2. Simple Request:

2-1. Path Param:

2-2. Path Param Request:

3-1. Post:

3-2. Post Request:

4-1. Put:

4-2. Put Request:

Week11: Visualization with Streamlit

Streamlit Runner (for running files below in Colab)

1. Streamlit Layout: 🔗

2. Streamlit Iris: 🔗

3. Streamlit Gapminder: 🔗

4. Streamlit Uber: 🔗

5. Dash Histogram:

6. Dash Gapminder:

Week12: Advanced DL & Text Classification

1. Text Classification (TF-IDF) [PyTorch]:

2. Text Classification (BERT) [PyTorch]:

3. Text Classification (Phayathaibert) [PyTorch Lightning]:

4. Multi-label Text Classification (microsoft/deberta-v3-small) [PyTorch]:

Week13: Generative AI (Prompt Engineering, Monitoring, Agentic Workflow, RAG, Fine-tuning)

1. Basic API Call with LangChain

2. Basic Prompt Engineering

3. Advanced Prompt Engineering

4. LangChain Playground and Tracking with LangSmith

5. Basic LangGraph

6. RAG with LangChain and Agentic RAG with LangGraph