課程信息
4.5
8,110 個評分
2,063 個審閱
專項課程

第 1 門課程(共 5 門),位於

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
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中級

中級

完成時間(小時)

完成時間大約為18 小時

建議:6 hours/week...
可選語言

英語(English)

字幕:英語(English), 中文(繁體), 巴西葡萄牙語, 越南語, 韓語, 希伯來語...

您將學到的內容有

  • Check

    Describe common Python functionality and features used for data science

  • Check

    Explain distributions, sampling, and t-tests

  • Check

    Query DataFrame structures for cleaning and processing

  • Check

    Understand techniques such as lambdas and manipulating csv files

您將獲得的技能

Python ProgrammingNumpyPandasData Cleansing
專項課程

第 1 門課程(共 5 門),位於

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
中級

中級

完成時間(小時)

完成時間大約為18 小時

建議:6 hours/week...
可選語言

英語(English)

字幕:英語(English), 中文(繁體), 巴西葡萄牙語, 越南語, 韓語, 希伯來語...

教學大綱 - 您將從這門課程中學到什麼

1
完成時間(小時)
完成時間為 3 小時

Week 1

In this week you'll get an introduction to the field of data science, review common Python functionality and features which data scientists use, and be introduced to the Coursera Jupyter Notebook for the lectures. All of the course information on grading, prerequisites, and expectations are on the course syllabus, and you can find more information about the Jupyter Notebooks on our Course Resources page....
Reading
11 個視頻(共 58 分鐘), 4 個閱讀材料, 1 個測驗
Video11 個視頻
Data Science7分鐘
The Coursera Jupyter Notebook System3分鐘
Python Functions8分鐘
Python Types and Sequences8分鐘
Python More on Strings3分鐘
Python Demonstration: Reading and Writing CSV files3分鐘
Python Dates and Times2分鐘
Advanced Python Objects, map()5分鐘
Advanced Python Lambda and List Comprehensions2分鐘
Advanced Python Demonstration: The Numerical Python Library (NumPy)7分鐘
Reading4 個閱讀材料
Syllabus10分鐘
Help us learn more about you!10分鐘
50 years of Data Science, David Donoho (optional)30分鐘
Notice for Auditing Learners: Assignment Submission10分鐘
Quiz1 個練習
Week One Quiz12分鐘
2
完成時間(小時)
完成時間為 3 小時

Week 2

In this week of the course you'll learn the fundamentals of one of the most important toolkits Python has for data cleaning and processing -- pandas. You'll learn how to read in data into DataFrame structures, how to query these structures, and the details about such structures are indexed. The module ends with a programming assignment and a discussion question....
Reading
8 個視頻(共 45 分鐘), 2 個測驗
Video8 個視頻
The Series Data Structure4分鐘
Querying a Series8分鐘
The DataFrame Data Structure7分鐘
DataFrame Indexing and Loading5分鐘
Querying a DataFrame5分鐘
Indexing Dataframes5分鐘
Missing Values4分鐘
3
完成時間(小時)
完成時間為 3 小時

Week 3

In this week you'll deepen your understanding of the python pandas library by learning how to merge DataFrames, generate summary tables, group data into logical pieces, and manipulate dates. We'll also refresh your understanding of scales of data, and discuss issues with creating metrics for analysis. The week ends with a more significant programming assignment....
Reading
6 個視頻(共 35 分鐘), 1 個測驗
Video6 個視頻
Pandas Idioms6分鐘
Group by6分鐘
Scales7分鐘
Pivot Tables2分鐘
Date Functionality5分鐘
4
完成時間(小時)
完成時間為 6 小時

Week 4

In this week of the course you'll be introduced to a variety of statistical techniques such a distributions, sampling and t-tests. The majority of the week will be dedicated to your course project, where you'll engage in a real-world data cleaning activity and provide evidence for (or against!) a given hypothesis. This project is suitable for a data science portfolio, and will test your knowledge of cleaning, merging, manipulating, and test for significance in data. The week ends with two discussions of science and the rise of the fourth paradigm -- data driven discovery....
Reading
4 個視頻(共 25 分鐘), 1 個閱讀材料, 2 個測驗
Video4 個視頻
Distributions4分鐘
More Distributions8分鐘
Hypothesis Testing in Python10分鐘
Reading1 個閱讀材料
Post-course Survey10分鐘
4.5
2,063 個審閱Chevron Right
職業方向

34%

完成這些課程後已開始新的職業生涯
工作福利

83%

通過此課程獲得實實在在的工作福利
職業晉升

11%

加薪或升職

熱門審閱

創建者 AUDec 10th 2017

Wow, this was amazing. Learned a lot (mostly thanks to stack overflow) but the course also opened my eyes to all the possibilities available out there and I feel like i'm only scratching the surface!

創建者 SIMar 16th 2018

overall the good introductory course of python for data science but i feel it should have covered the basics in more details .specially for the ones who do not have any prior programming background .

關於 University of Michigan

The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future....

關於 Applied Data Science with Python 專項課程

The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate....
Applied Data Science with Python

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