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Lynda - Data Science Foundations: Fundamentals (2016) - 420305
Lynda - Data Science Foundations: Fundamentals (2016)
Get a comprehensive overview of modern data science: the practice of obtaining, exploring, modeling, and interpreting data. Barton Poulson explores disciplines such as programming, statistics, mathematics, machine learning, data analysis, visualization, and big data. He explains why data scientists are now in such demand, and the skills required to succeed in different jobs. He shows how to obtain data from legitimate open-source repositories via web APIs and page scraping, and introduces specific technologies (R, Python, and SQL) and techniques (support vector machines and random forests) for analysis. By the end of the course, you should better understand data science's role in making meaningful insights from the complex and large sets of data all around us.


Table of Contents

  • Introduction
  • 1. What Is Data Science?
  • 2. Fields of Study
  • 3. Ethics
  • 4. Data Sources
  • 5. Data Exploration
  • 6. Programming
  • 7. Mathematics
  • 8. Applied Statistics
  • 9. Machine Learning
  • 10. Communicating
  • Conclusion
  • Lynda - Data Science Foundations: Fundamentals (2016)


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