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Nir Kaldero is a Lead Experiance Instructor for Data Science at the Genearl Assembly, San Francisco. He is also a Scholar for the Economics Department at the University of California, Berkeley, where he conducts research in Health Insurance and Information Technology (IT). He has devoted his career to applied economics research focused on leveraging Big Data in order to create market value.


Blending programming skills, economics and statistics, Nir Kaldero brings a fresh perspective to the Data Science field. He approaches data mining techniques with an emphasis on asking creative questions and developing more intuitive methodologies.


He is passionate about optimizing operational and marketing strategies based on advanced analysis methods and machine learning techniques, utilizing data to understand consumer and organization behavior, accelerate performance, increase efficiency, and enhance productivity. Above all, he strives to make Data Science exciting and accessible, and to demonstrate how anybody can harness their skills, intuition, and creativity to become a great Data Scientist.


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Python is a versatile and widely-used programming language with many applications. This workshop explores Python's place in the scientific ecosystem, and how the language, with several readily-available open-source libraries, can serve as a powerful tool for data analysis. Designed as a stand-alone introduction to the data science aspects of Python, this class is also a recommended refresher for students planning to enroll in General Assembly's upcoming Data Science course.


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The goal of this two-day workshop is to help participants learn fundamental concepts in Applied Statistics that can be used in Data Science related projects.

This workshop will help participants gain a statistical thinking mindset and intuition in order to build predictive models (in Python) that can help answer important industry related questions and make recommendations.

By developing a statistical thinking approach, participants will be able to define and create optimal operational and marketing strategies based on advanced analysis and data mining techniques. By the end of this advanced workshop, each participant will have cultivated their own Statistical thinking approach and have increased their familiarity with various modeling techniques.



  • Develop Statistical thinking approach

  • Gain the ability to leverage [Big] Data into actionable modeling power to define optimal strategies

  • Feel comfortable with approaching industry related projects

  • Gain familiarity with Applied Statistics (/Econometrics) for Data Science

  • Learn to apply statistical models in Python

  • Develop the intuition of a Data Scientist


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