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Introduction to Data Science in Python WEEK 1 Quiz Answers Coursera | by University of Michigan
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Introduction to Data Science in Python WEEK 1 Quiz Answers Coursera | by University of Michigan
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.
This 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.
~~SKILLS YOU WILL GAIN~~
* 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
~Course Link:
#Coursera
#datascience
#COVID19
#eLearning
#UniversityofMichigan
#python
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🌟𝗣𝗹𝗲𝗮𝘀𝗲 𝗹𝗲𝗮𝘃𝗲 𝗮 𝗟𝗜𝗞𝗘❤️ 𝗮𝗻𝗱 𝗦𝗨𝗕𝗦𝗖𝗥𝗜𝗕𝗘 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝗔𝗠𝗔𝗭𝗜𝗡𝗚 𝗰𝗼𝗻𝘁𝗲𝗻𝘁! 🌟
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.
This 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.
~~SKILLS YOU WILL GAIN~~
* 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
~Course Link:
#Coursera
#datascience
#COVID19
#eLearning
#UniversityofMichigan
#python
-----------------------------------------------------------------------------------------------------------------------
🌟𝗣𝗹𝗲𝗮𝘀𝗲 𝗹𝗲𝗮𝘃𝗲 𝗮 𝗟𝗜𝗞𝗘❤️ 𝗮𝗻𝗱 𝗦𝗨𝗕𝗦𝗖𝗥𝗜𝗕𝗘 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝗔𝗠𝗔𝗭𝗜𝗡𝗚 𝗰𝗼𝗻𝘁𝗲𝗻𝘁! 🌟
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