Woolf Library

Courses at Woolf typically include all the materials required for successful completion. Further digital resources are valuable for students supplementing their examination essays, students undertaking advanced studies, or faculty designing new courses.

Open access journals, books and videos

[01

**CORE**](https://core.ac.uk/)

[02

**Internet Archive**](https://archive.org/)

[03

**Academia.edu**](https://academia.edu/)

[04

**Directory of Open Access Journals**](https://doaj.org/)

[05

**ResearchGate**](https://researchgate.net/)

[06

**OAPEN**](https://oapen.org/)

[07

**SpringerOpen**](https://springeropen.com/)

[08

**VideoLectures.NET**](https://videolectures.net/)

[09

**Bielefeld Academic Search Engine**](https://base-search.net/)

[10

**OpenAIRE**](https://explore.openaire.eu/)

[11

**Paperity**](https://paperity.org/)

[12

**Open Access Button**](https://openaccessbutton.org/)

[13

**Open Library of Humanities**](https://openlibhums.org/)

[14

**JSTOR**](https://jstor.org/)

[15

**Directory of Open Access Books**](https://doabooks.org/)

[16

**OpenDOAR**](https://v2.sherpa.ac.uk/opendoar)

[17

**arXiv.org**](https://arxiv.org/)

[18

**Scholarpedia**](https://scholarpedia.org/)

[19

**Google Scholar**](https://scholar.google.com/)

[20

**Journals Gateway**](https://direct.mit.edu/journals)

[21

**OAIster**](https://oaister.worldcat.org/)

[22

**MIT**](https://openlearning.mit.edu/)

Special subject resources

Subject areas

[01

**Classics Resources**](https://classicsresources.info/)

[02

**SSRN**](https://ssrn.com/)

[03

**Internet History Sourcebooks Project**](https://sourcebooks.fordham.edu/)

Digital editions

[01

**Dig-Ed-Cat**](https://dig-ed-cat.acdh.oeaw.ac.at/)

[02

**InteLex Past Masters**](https://nlx.com/)

[03

**Nietzsche Source**](https://nietzschesource.org/)

Manuscripts

[01

**International Dunhuang Project**](https://idp.bl.uk/)

[02

**Digitised Manuscripts**](https://bl.uk/)

[03

**Early printed books**](https://bl.uk/)

[04

**Medieval and early modern British literary manuscripts**](https://bl.uk/)

Blogs & activities

[01

**Google AI**](https://blog.google/technology/ai)

[02

**IBM Research Publications**](https://research.ibm.com/publications)

[03

**Deloitte Insights**](https://deloitte.com/)

[04

**Databricks**](https://databricks.com/resources)

[05

**Machine Learning Mastery**](https://machinelearningmastery.com/blog)

[06

**Analytics Vidhya**](/content/about/technology#/index.html)

[07

**Data Science Dojo**](https://tutorials.datasciencedojo.com/)

[08

**Revolutions**](https://blog.revolutionanalytics.com/)

[09

**District Data Labs**](https://districtdatalabs.silvrback.com/)

[10

**Pete Warden**](https://petewarden.com/)

[11

**FlowingData**](https://flowingdata.com/)

[12

**KDnuggets**](https://kdnuggets.com/)

[13

**Towards Data Science**](https://towardsdatascience.com/)

[14

**Accenture Research**](https://accenture.com/us-en/blogs/accenture-research)

[15

**HackerRank**](https://hackerrank.com/)

[16

**Stack Overflow**](https://stackoverflow.com/)

Papers

[01

**International Journal of Data Science and Analytics**](https://springer.com/journal/41060)

[02

**Harvard Data Science Review**](https://hdsr.mitpress.mit.edu/)

[03

**Papers with Code**](https://paperswithcode.com/)

[04

**Nature Machine Intelligence**](https://nature.com/natmachintell)

[05

**arXiv**](https://arxiv.org/)

Documentation

[01

**MongoDB**](https://docs.mongodb.com/)

[02

**SAS**](https://support.sas.com/)

[03

**Beautiful Soup**](https://crummy.com/software/BeautifulSoup)

[04

**BigQuery**](https://cloud.google.com/bigquery/docs)

[05

**Microsoft SQL**](https://learn.microsoft.com/en-us/sql)

[06

**Dask**](https://docs.dask.org/)

[07

**SageMath**](https://sagemath.org/)

[08

**TensorFlow**](https://tensorflow.org/learn)

[09

**Apache Kafka**](https://kafka.apache.org/documentation)

[10

**Qlik**](https://community.qlik.com/)

[11

**Selenium**](https://selenium.dev/documentation)

[12

**Altair**](https://altair-viz.github.io/)

[13

**SymPy**](https://sympy.org/)

[14

**scikit-learn**](https://scikit-learn.org/stable)

[15

**NumPy**](https://numpy.org/doc)

[16

**Power BI**](https://docs.microsoft.com/en-us/power-bi)

[17

**Matplotlib**](https://matplotlib.org/)

[18

**R Project**](https://r-project.org/other-docs.html)

[19

**PyPI**](https://pypi.org/)

[20

**Plotly**](https://help.woolf.education/hc/en-us/articles/Python%20plotly.com/python)

[21

**Apache Spark**](https://spark.apache.org/)

[22

**Apache Cassandra**](https://cassandra.apache.org/doc/latest)

[23

**OpenCV**](https://docs.opencv.org/)

[24

**Keras**](https://keras.io/)

[25

**Tableau**](https://tableau.com/learn/articles)

[26

**Data-Driven Documents**](https://github.com/d3/d3/wiki)

[27

**MySQL**](https://dev.mysql.com/doc)

[28

**Python**](https://docs.python.org/)

[29

**SciPy**](https://scipy.org/)

[30

**PyTorch**](https://pytorch.org/docs/stable/torch.html)

[31

**statsmodels**](https://statsmodels.org/stable/index.html)

[32

**PostgreSQL**](https://postgresql.org/docs/current)

[33

**pickle**](https://docs.python.org/3/library/pickle.html)

[34

**seaborn**](https://seaborn.pydata.org/)

[35

**Oracle Database**](https://docs.oracle.com/en/database/oracle)