Michigan University Introduction to Data Science in Python
★★★★★
(3 customer reviews)Overall the good introductory course of python for data science but i feel it should have covered the basics in more details especially for the ones who do not have any prior programming background.
I recommend this course to anyone interested in Data Science and who already has a basic knowledge of Python.
Specification: Michigan University Introduction to Data Science in Python
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Modules | 1. Introduction to the field of data science with python. 2. Data cleaning and processing – Pandas 3. Merge DataFrames, generate summary tables, group data into logical pieces, and manipulate dates. 4. Statistical techniques such a distributions, sampling and t-tests |
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Subtitle | Chinese, English, Hebrew, Portuguese (Brazilian), Vietnamese |
3 reviews for Michigan University Introduction to Data Science in Python
3.7 out of 5
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Expert Score 6.5
Course Content
6.5
Learning Experience
6.5
Course Price
8.5
Credibility
9
Flexibility
10
PROS:
- The University of Michigan is a fantastic university.
- Great introductory course to python.
CONS:
- The material the lectures covered rarely showed up in the programming assignments.
- The speaker is so dull, and the way he speaks doesn't motivate one to learn the things
- The autograder is more or less broken.
- Huge disparity between the course videos and the assignments provided.
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Michigan University Introduction to Data Science in Python
Angello Fallas –
New year, new learning path! 💡
Just completed “Introduction to Data Science in Python” by University of Michigan on Coursera.
The course covered data cleaning, data processing and basic hypothesis testing, with pandas and numpy.
This is the first course of the “Applied Data Science with Python” Specialization by University of Michigan.
#datascience #python #coursera #learning
Pranit patil –
Completed an online course Introduction to Data Science in Python on Coursera offered by University of Michigan. The course introduced with various data manipulation and cleaning techniques using #pandas and #numpy library. It also introduces 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.
#datascience #dataanalysis #python #coursera #machinelearning #universityofmichigan
Bashir Abubakar –
I completed Introduction to Data Science in Python with a 95.3% grade from University of Michigan on Coursera.org.
https://lnkd.in/g6U9FHj the course wasn’t an easy task because basically I had to do apply a lot of research. In the end I was able to complete an hypothetical testing with t-test from scikit-learn library to determine the ratio of mean price of houses in a geographical region the quarter before the recession starts compared to the recession bottom. Working with tuples, sets and dictionaries alongside series have been really exciting for me in this course. #datascience #statistics #datavisualisation #pandas #python3 #pythonprogramming #statisticalanalysis #dailycoding #dataanalyst #jupyternotebook #businessintelligence #sklearn Many thanks to Filip Jankovic & Christopher Brooks