Professional training, supplementary courses, online courses
Online
Regular fees: 45 - 72 EUR
Available within a Coursera Plus subscription (€54/$59 per month or €366/$399 per year)
What you'll learn
- Understand techniques such as lambdas and manipulating csv files
- Describe common Python functionality and features used for data science
- Query DataFrame structures for cleaning and processing
- Explain distributions, sampling, and t-tests
This course will introduce the learner to the basics of the python programming environment, including fundamental python programming techniques such as lambdas, reading and manipulating csv files, and the numpy library. The course will introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the Series and DataFrame as the central data structures for data analysis, along with tutorials on how to use functions such as groupby, merge, and pivot tables effectively. By the end of this course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses.
There are 4 modules in this course
- Fundamentals of Data Manipulation with Python
- Basic Data Processing with Pandas
- More Data Processing with Pandas
- Answering Questions with Messy Data
This course is part of the Applied Data Science with Python Specialization
This Introduction to Data Science in Python course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Network Analysis in Python.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
