References#

Cheatsheets#

• Foundations:
  • Python
  • SQL
  • Git
• Data Manipulation:
  • Pandas
  • NumPy
• Data Visualization:
  • Matplotlib
  • Matplotlib
  • Seaborn
  • Seaborn
• Machine Learning Libraries:
  • Scikit-Learn
  • TensorFlow
  • Keras
• Data Analysis Techniques:
  • Statistical Inference
  • Probability
  • Linear Algebra
  • Calulus
• Advanced Topics:
  • Natural Language Processing
  • Neural Networks and Deep Learning
• Big Data Technologies:
  • Apache Spark
  • Hadoop
• Other Useful Skills:
  • Regular Expressions
  • Python String Formatting
• Databases:
  • PostgreSQL
  • MySQL
  • SQLite

Books#

• Peng, R. D. (2015). Exploratory Data Analysis with R. Springer.

• Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: data mining, inference, and prediction. Springer.

• Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big Data, 1(1), 51-59.

• Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (2007). Numerical recipes: The art of scientific computing. Cambridge University Press.

• James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning. Springer.

• Wickham, H., & Grolemund, G. (2017). R for data science: import, tidy, transform, visualize, and model data. O'Reilly Media, Inc.

• VanderPlas, J. (2016). Python data science handbook: Essential tools for working with data. O'Reilly Media, Inc.

SQL and DataBases#

• SQL: https://www.w3schools.com/sql/

• MySQL: https://www.mysql.com/

• PostgreSQL: https://www.postgresql.org/

• SQLite: https://www.sqlite.org/index.html

• DuckDB: https://duckdb.org/

Software#

• Python: https://www.python.org/

• The R Project for Statistical Computing: https://www.r-project.org/

• Tableau: https://www.tableau.com/

• PowerBI: https://powerbi.microsoft.com/

• Hadoop: https://hadoop.apache.org/

• Apache Spark: https://spark.apache.org/

• AWS: https://aws.amazon.com/

• GCP: https://cloud.google.com/

• Azure: https://azure.microsoft.com/

• TensorFlow: https://www.tensorflow.org/

• scikit-learn: https://scikit-learn.org/

• Apache Kafka: https://kafka.apache.org/

• Apache Beam: https://beam.apache.org/

• spaCy: https://spacy.io/

• NLTK: https://www.nltk.org/

• NumPy: https://numpy.org/

• Pandas: https://pandas.pydata.org/

• Scikit-learn: https://scikit-learn.org/

• Matplotlib: https://matplotlib.org/

• Seaborn: https://seaborn.pydata.org/

• Plotly: https://plotly.com/

• Jupyter Notebook: https://jupyter.org/

• Anaconda: https://www.anaconda.com/

• TensorFlow: https://www.tensorflow.org/

• RStudio: https://www.rstudio.com/