136010 UE Introduction to DH Tools and Methods (2021S)

Lehrende

• Renato Rocha Souza

Termine (iCal) - nächster Termin ist mit N markiert

Topics/Dates

1) Overview on digital ecosystem for DH: OCR & NLP Pipelines, Visualization & Dashboards, Spatial Analysis, Image Analysis, Social Network Analysis, Sentiment Analysis, Temporal Series Analysis, SQL and NoSQL, Database Management, RDF triplestores, etc.

2) The basics of Programming:
IDEs and Digital Research Frameworks
Programming Languages: why Python?
First steps into programming
Hands on: Installing Anaconda and programming the first “Hello World”

3) The basics of Versioning:
Versioning Code: Git, Github, Gitlab
Versioning Data: Dolthub
Hands on: Installing Github Desktop. Full cycle on versioning files.

4) The basics of Python language I:
Python objects and methods
Python native structures: data containers
Hands on: small scripts with native structures.

5) The basics of Python language II:
Python control flow
Python functions
Python scopes
Hands on: Mining text with simple functions.

6) The basics of Python language III:
Python packages and modules
Python data persistence
Hands on: Exploring common packages from the standard library: os, time, sys, string, pickle, dill, random
Suggested readings:
Python generators and comprehensions

7)Advanced topics of Python language:
Python classes and OOP
Hands on: Creating classes to represent DH entities
Suggested readings:
Python decorators
Code Optimization

8) Topics in Exploratory Data Analysis (EDA) I
Basic Statistics
Data Visualization
Data Wrangling
Hands on: Python EDA with Numpy, Pandas, Matplotlib, Seaborn

9) Topics in Exploratory Data Analysis (EDA) II
Basic Statistics
Data Visualization
Data Wrangling
Hands on: Python EDA with Numpy, Pandas, Matplotlib, Seaborn

10) NLP Intro:
Motivations, Tasks, Goals and Challenges
NLP and the Humanities
Python NLP Packages (NLTK, Spacy, TextBlob, Wordnet)
Hands on: Python NLP Pipeline for Corpus Acquisition and Cleaning - Information extraction and Scraping, Regular Expressions, Frequency Analysis, N-grams, POS Tagging, Syntax parsing, NER, Summarization

11) Topic Modeling,
Text Classification
Sentiment Analysis
Python NLP Packages (Gensim, PyLDAVis)
Hands on: Python NLP Pipelines for Text Representation (BoW, TfIDf)

12) Word Embeddings
Dimensionality Reduction
Text Visualization
Hands on: Detection of Biases in Corpora

13) Semantic Web Technologies
Knowledge Organization Systems
Thesauri and Ontologies
Hands on: Python and Text Annotation - TEI/XML (XML, LXML, XLPATH)

14) Social Network Analysis
Graphs
Knowledge Graphs,
Hands on: SNA with Python Graph Structures (NetworkX, PyVIS)

15) Where to go from here:
Temporal Series Analysis
Image analysis and Computer Vision
Machine Learning and Deep Learning for NLP
Text Classification
Text Clustering
Stylistic Analysis
Information Extraction
Information Retrieval Systems