This course will introduce you to the field of data science and will prepare you for the next three
courses in the MicroMasters: Statistics, Machine Learning, and Spark. First, and foremost, you'll learn how to conduct data science by learning how to analyze data.
That includes knowing how to import data, explore it, analyze it, learn from it, visualize it, and
ultimately generate easily shareable reports. We'll also introduce you to two powerful areas of
data analysis: machine learning and natural language processing.
courses in the MicroMasters: Statistics, Machine Learning, and Spark. First, and foremost, you'll learn how to conduct data science by learning how to analyze data.
That includes knowing how to import data, explore it, analyze it, learn from it, visualize it, and
ultimately generate easily shareable reports. We'll also introduce you to two powerful areas of
data analysis: machine learning and natural language processing.
Requirements
- asic knowledge of programming in any language (Java, C, C++, Pascal, Fortran, Javascript, PHP, python, etc.)
- Ability to create an assign variables
- Ability to write program with loops
- Ability to write programs with conditions
- Ability to author and use functions (methods)
Features
- The basics of conducting data science
- How to perform data analysis in python
- Python and Jupyter notebooks
- An applied understanding of how to manipulate and analyze uncurated datasets
- Basic statistical analysis and machine learning methods
Target audiences
- Programmers
- Data Managers
- Big Data Professionals
