AAUBS Data Science 2022
Info, Schedule & Co
Infrastructure
Modules
Literature & Resources
Semester Schedule
Semester Project Requirements
1.
Applied Data Science and Machine Learning
Basics of Statistical Programming and Data Manipulation (W35-36)
Basics Statistical Programming
Statistics Refresher
Basics Data Visualization
Hands-on data manipulation and EDA
EDA workshop & Working with JSON/APIs/MongoDB
M1 EDA Hackathon
Rapid Prototyping with Streamlit
Mathematics (Brushup)
Intro to Unsupervised Machine Learning (W38)
Unsupervised Machine Learning (UML) intro
UML Appliations - Recommender Systems
Supervised Machine Learning (W39)
Supervised Machine Learning (SML)
Time Series Forecasts
SML - Further topics
SML Appliations - Airbnb Pricing
2.
Network Analysis & NLP
Network Analysis
Basics Network Analysis
2 Mode Networks
NW Exercises
NW Cases
Natural Language Processing
Basics of NLP
NLP - Other areas
NLP Applications Chatbot
NLP Word Vectors
4.
Applied Deep Learning and Artificial Intelligence
Intro to Deep Learning
Basics Deep Learning
Neural network architectures
Exercise Session 1
Group assignment 1
Neural network architectures
CNNs
RNNs and LSTMs
Exercise Session 2
Group assignment 2
Intro to transformer models
Introduction to transformers
Sentence-Transformers SBERT
Exercise Session 3
Group assignment 3
Transformer models in 2023
Fine-tuning transformers
Timeseries Transformers intro
Exercise Session 4
5.
Data Governance and Ethics
In-calss Presentations
6.
Data Engineering and MLOps
Databases
Introduction to databases
Building PoC with DB backend
Portfolio Assignment Databases
MLOps: A Framework and Maturity Model
Big Data workflows
Introduction to Big Data workflows
Exercise 2: Performing a Big Data workflow with Spark and Polars
Group assignment 2
From notebook to API
From notebook to API
MLOps
Introduction MLOps with mlflow
MLOps on AWS: a Hands-On Tutorial
Group assignment 3
Deployment
From notebook to containarized app in the cloud
Introduction to Docker and deploying scalable ML
Group assignment 4
Clear History
Built with
from
Grav
and
Hugo
Social / Business Data Science 2022
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Applied Data Science and Machine Learning
>
Supervised Machine Learning (W39)
> SML - Further topics
SML - Further topics
This session introduces adittional topics of intertest in SML
Notebook(s)
Introduction to Explainable ML
Recommended Datacamp exercises:
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Recommended Readings and resources
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