Learning Material

Please enable Javascript in your browser!!

Slides

You can find a download link for the slides of each video on the videos's page.
For your convenience we offer an archive of this week's slides here: Download zip

Go to overview

Week 1
- 0.0 Lecture Outline
- Important Dates and the Team
- 1.0 Lecture Overview
- Learning Material
- 1.1 Information and Knowledge
- 1.1 Information and Knowledge
- 1.2 Language and Understanding
- 1.2 Language and Understanding
- 1.3 NLP Techniques and Challenges
- 1.3 NLP Techniques and Challenges
- 1.4 Linguistic Basics
- 1.4 Linguistic Basics
- 1.5 Morphology
- 1.5 Morphology
- 1.6 Evaluation, Precision, and Recall
- 1.6 Evaluation, Precision and Recall
- 1.6 Evaluation, Precision, and Recall - Excursion
- 1.6 Evaluation, Precision and Recall - Excursion
- 1.7 Regular Expressions
- 1.7 Regular Expressions
- 1.8 Weekly Assignment
Week 2
- 2.0 Lecture Overview
- Learning Material
- 2.1 Finite State Automata
- 2.1 Finite State Automata
- 2.2 Finite State Transducers
- 2.2. Finite State Transducers
- 2.3 Language Model and N-Grams I
- 2.3 Language Model and N-Grams I
- 2.4 Language Model and N-Grams II
- 2.4 Language Model and N-Grams II
- 2.4 Language Model and N-Grams II - Excursion
- 2.5 Language Model and N-Grams III
- 2.5 Language Model and N-Grams III
- 2.6 Part-of-Speech Tagging I
- 2.6 Part-of-Speech Tagging I
- 2.7 Part-of-Speech Tagging II
- 2.7 Part-of-Speech Tagging II
- 2.8 Bonus Quiz
- 2.9 Weekly Assignment
Week 3
- 3.0 Lecture Overview
- Learning Material
- 3.1 Understanding Data on the Web
- 3.1 Understanding Data on the Web
- 3.2 Towards a Universal Data Representation
- 3.2 Towards a Universal Data Representation
- 3.3. - How to Identify and Access Linked Data
- 3.3. How to Access and Identify Linked Data
- 3.3. How to Access and Identify Linked Data - Hands On
- 3.4 Representing Facts with RDF
- 3.4. Representing Facts with RDF
- 3.5 RDF Turtle Serialization
- 3.5 RDF Turtle Serialization
- 3.6 Model Building with RDFS
- 3.6 Model Building with RDFS
- 3.7 Logical Inference with RDF(S)
- 3.7 Logical Inference with RDF(S)
- Week 3 Bonus Quiz
- 3.8 Weekly Assigment
Week 4
- 4.0 Lecture Overview
- Learning Material
- 4.1 Linked Data Principles
- 4.1 Linked Data Principles
- 4.2 Web Ontology Language OWL I
- 4.2 Web Ontology Language OWL I
- 4.3 Web Ontology Language OWL II
- 4.3 Web Ontology Language OWL II
- 4.4 How to Query RDF with SPARQL
- 4.4 How to Query RDF with SPARQL
- 4.5 Complex Queries with SPARQL
- 4.5 Complex Queries with SPARQL
- 4.6 More Complex SPARQL Queries
- 4.6 More Complex SPARQL Queries
- 4.6 More Complex SPARQL Queries - Hands On
- 4.7 Linked Data Knowledge Bases
- 4.7 Linked Data and Knowledge Bases
- Week 4 Bonus Quiz
- 4.8 Weekly Assigment
Week 5
- 5.0 Lecture Overview
- Learning Material
- 5.1 A Brief History of AI
- 5.1 A Brief History of AI
- 5.2 Introduction to Machine Learning
- 5.2 Introduction to Machine Learning
- 5.3 Evaluation and Generalization Problems
- 5.3 Evaluation and Generalization Problems
- 5.4 Basic Machine Learning Algorithms I
- 5.4 Basic Machine Learning Algorithms I
- 5.5 Basic Machine Learning Algorithms II
- 5.5 Basic Machine Learning Algorithms II
- 5.6 Unsupervised Learning
- 5.6 Unsupervised Learning
- 5.7 Deep learning
- 5.7 Deep Learning
- Week 5 Bonus Quiz
- 5.8 Weekly Assigment
Week 6
- Learning Material
- 6.0 Lecture Overview
- 6.1 Linked Data Programming
- 6.1 Linked Data Programming
- 6.2 Knowledge Mining and Information Extraction I
- 6.2 Knowledge Mining and Information Extraction I
- 6.3 Knowledge Mining and Information Extraction II
- 6.3 Knowledge Mining and Information Extraction II
- 6.4 Knowledge Mining and Information Extraction III
- 6.4 Knowledge Mining and Information Extraction III
- 6.5 Knowledge Mining and Information Extraction IV
- 6.5 Knowledge Mining and Information Extraction IV
- 6.6 Semantic Search
- 6.6 Semantic Search
- 6.7 Exploratory Search
- 6.7 Exploratory Search
- 6.8 Weekly Assignment
Final Examination
- Instructions
- Final Exam