Data Science Foundations: Fundamentals
Data Science Foundations: Fundamentals
MP4 | Video: 720p | Duration: 3:06:32 | English | Subtitles: VTT | 464.0 MB
MP4 | Video: 720p | Duration: 3:06:32 | English | Subtitles: VTT | 464.0 MB
Introduction to Data Science provides a comprehensive overview of modern data science: the practice of obtaining, exploring, modeling, and interpreting data. While most only think of the "big subject," big data, there are many more fields and concepts to explore. Here Barton Poulson explores disciplines such as programming, statistics, mathematics, machine learning, data analysis, visualization, and (yes) 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.
Topics include:
- The demand for data science
- Roles and careers
- Ethical issues in data science
- Sourcing data
- Exploring data through graphs and statistics
- Programming with R, Python, and SQL
- Data science in math and statistics
- Data science and machine learning
- Communicating with data