The WordLens-Project
  • The WordLens-Project
  • Course Overview
  • Part 1: Transform and Visualize Data
    • 1 Working Environment
    • 2 R and the Tidyverse
    • 3 Data Loading
      • Tabular Data
      • Tidy Data
      • Exploring New Data
    • 4 Data Transformation
      • Select Columns
      • Filter Rows
      • Sort Rows
      • Add Or Change Columns
        • Calculate New Columns
        • Change Data Types
        • Rename Columns
        • Joining Data Sets
      • Summarize Rows
    • 5 Data Visualization
      • Pleas for Visualization
      • Fast and Simple Plots
      • Grammar of Graphics
  • Part 2: Rule-Based NLP
    • 6 Unstructured Data
    • 7 Searching Text
    • 8 Tokenizing Text
      • Filter or Sample Data
      • Clean and Normalize Text
      • Split Text Into Tokens
      • Removing Stop Words
      • Enrich Tokens
    • 9 Topic Classification
      • Deductive
      • Inductive
    • 10 Sentiment Analysis
    • 11 Text Classification
    • 12 Word Pairs and N-Grams
  • Part 3: NLP with Machine Learning
    • 13 Text Embeddings
    • 14 Part-Of-Speech
    • 15 Named Entities
    • 16 Syntactic Dependency
    • 17 Similarity
    • 18 Sentiment
    • 19 Text Classification
    • 20 Transformers
    • 21 Training a Model
    • 22 Large Language Models
  • Appendix
  • Resources
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On this page
  • Learning Objectives
  • Exercises
  • Important Terms and Concepts
  • Credits

Course Overview

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Last updated 2 years ago

Learning Objectives

Exercises

To complete this project, you must solve the exercises listed below. The project finishes with a case study that is released during the last weeks of the semester:

  • Exercise 3: NLP with Machine Learning

Important Terms and Concepts

You will notice that some words in this course are highlighted in bold with a yellow background. I use this formatting to point you to important terms and concepts that you should know and be able to explain. It is not necessarily explained in the same lesson or in this course at all. If you can't find anything here directly or in the provided literature, make sure you do your research and ask questions during sessions.

Credits

This course was written with assistance from and .

Exercise 1: Data Transformation and Visualization
Exercise 2: Search and Extract Text Data
ChatGPT
DeepL
The learning goals for this project visually explained.
Drawing