Mastering Software Development in R
> Advanced R Programming > Building R Packages > Building Data Visualization Tools
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Data Science Bootcamp: Pay only after you get a data science job.
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Introduction to Data Science
> Programming in R > Probability & Statistics > Exploratory Data Analysis > Data Analysis in Depth
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5 Must read books for Data Scientists
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Reinforcement Learning
> Fundamentals of Reinforcement Learning > Sample-based Learning Methods > Prediction and Control with Function Approximation
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Bayesian Machine Learning in Python: A/B Testing
> Use adaptive algorithms to improve A/B testing performance > Apply Bayesian methods to A/B testing > Understand the difference between Bayesian and frequentist statistics
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DataScience New York 2019(January 23-24)
Join us in New York, January 23-24, for this unique peer-to-peer event for top data science minds. Explore how to drive innovation within your business through a data-driven culture, build a world-class team, and utilize the latest innovation to solve some of the toughest problems facing corporate America.
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Books to learn Practical Machine Learning
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Introduction to Artificial Intelligence ( AI ) for Beginners
> Understand how to manage machine learning and deep learning projects > Manage AI projects >Estimate resources required to complete an AI project