Python Data Analysis
Introduction to Scripting in Python,
This course will continue the introduction to Python programming that started with Python Programming Essentials and Python Data Representations. We'll learn about reading, storing, and processing tabular data, which are common tasks. We will also teach you about CSV files and Python's support for reading and writing them. CSV files are a generic, plain text file format that allows you to exchange tabular data between different programs. These concepts and skills will help you to further extend your Python programming knowledge and allow you to process more complex data. By the end of the course, you will be comfortable working with tabular data in Python. This will extend your Python programming expertise, enabling you to write a wider range of scripts using Python. This course uses Python 3. While most Python programs continue to use Python 2, Python 3 is the future of the Python programming language. This course uses basic desktop Python development environments, allowing you to run Python programs directly on your computer.
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| Rating | 4.5★ based on 62 ratings |
|---|---|
| Length | 5 weeks |
| Effort | This is a four week class with an expected workload of 5-7 hours per week. |
| Starts | Jul 3 (43 weeks ago) |
| Cost | $49 |
| From | Rice University via Coursera |
| Instructors | Scott Rixner, Joe Warren |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Science Data Analysis Software Development |
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What people are saying
final project
Final project is way more difficult than what they explain in the course.Final project is not only difficult and long but also due to the amount of extra files and lack of explanation on how to start is very frustrating.Some concepts like "list comprenhentions" are used by instructors in the course, but not explained and instructor just adviced to go to Python.org and learn it there.
The final project is rewarding, requiring relatively little code but a clear understanding of the underlying data structures.Compared to the Fundamentals of Computing specialization (which later moves towards developing efficient algorithms), the series so far seems to be geared towards developing practical skills for applying Python for data science.
You will feel very satisfying when you complete the final project.
Challenging final project.
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very good
Very good course.
This is a very good course.
Very good online course!
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figure out
The practice assignments in particular are riddled with horrible grammatical errors that make it hard to figure out what is being asked of you, especially when the author seems to be trying to be overly concise in their explanations.
It felt like every assignment just told me to read page after page of documentation and figure out what parts were relevant on my own.
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practice assignments
The learning curve is gradual so make sure you follow instructions and complete all the practice assignments in order.
The disconnect between the practice assignments and the graded assignments also caused a lot of issues with regards to flow.
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| Rating | 4.5★ based on 62 ratings |
|---|---|
| Length | 5 weeks |
| Effort | This is a four week class with an expected workload of 5-7 hours per week. |
| Starts | Jul 3 (43 weeks ago) |
| Cost | $49 |
| From | Rice University via Coursera |
| Instructors | Scott Rixner, Joe Warren |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Science Data Analysis Software Development |
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