| Summary: | Master important data manipulation techniques for data science in Python by learning Python, NumPy, and Pandas About This Video Discover the basics of Python programming The most important Python libraries for data science Learn how to use Python to clean, visualize, and analyze data In Detail Data science is quickly becoming one of the most promising careers in the twenty-first century. It is automated, program-driven, and analytical. As a result, it's no surprise that the demand for data scientists has been expanding in the job market over the last few years. We will begin with a quick refresher on Python fundamentals for beginners in this course. This is optional; if you're already familiar with Python, skip to the next chapter. Data science will be the topic of the next three sections. We will start with the essential Python libraries for data science, then go on to the fundamental NumPy properties, and lastly begin with mathematics and how to use it in data science. You will learn about Python Pandas DataFrames and series after learning about data science. Following that, we will get down to business and begin data cleaning. Following that, we will learn how to use Python to visualize data and do data analysis on some sample datasets. Finally, we will cover the Time series in Python and learn how to work with and convert datasets to Time series. By the end of this course, you will be able to execute data manipulation for data science in Python with ease. Audience This course is open to students of all skill levels, and you will be able to succeed even if you have no prior programming or statistical knowledge
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