Python for Data Science - Course for Beginners (Learn Python, Pandas, NumPy, Matplotlib)
via freeCodeCamp
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247
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Overview
Syllabus
Introduction to the Course and Outline.
The Basics of Programming.
Why Python.
How to Install Anaconda and Python.
How to Launch a Jupyter Notebook.
How to Code in the iPython Shell.
Variables and Operators in Python.
Booleans and Comparisons in Python.
Other Useful Python Functions.
Control Flow in Python.
Functions in Python.
Modules in Python.
Strings in Python.
Other Important Python Data Structures: Lists, Tuples, Sets, and Dictionaries.
The NumPy Python Data Science Library.
The Pandas Python Data Science Python Library.
The Matplotlib Python Data Science Library.
Example Project: A COVID19 Trend Analysis Data Analysis Tool Built with Python Libraries.
Taught by
freeCodeCamp.org
Reviews
4.1 rating, based on 25 Class Central reviews
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this is to testify that I have gained a lot from this course of beginners , this course exposes one to the foundation of python which is a key tool of data science.
if one needs to explore in the field of data science then its almost a requirement not to miss this kind of beginner exposure with class central as the guider.
thanks I appreciate for the knowledge I have acquired and I would like to encourage others to strive to do so.
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FreeCodeCamp's Python for Data Science course is generally well-received within the programming community. FreeCodeCamp is known for offering high-quality educational content, often curated and developed by experts in the field. Here's a review base…
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Excellent Python course! 10/10.I just completed a Python course, and I couldn't be happier with the experience. The course was well-structured, informative, and engaging. The instructors did a fantastic job of explaining complex concepts in a way that was easy to understand. I feel much more confident in my Python skills now and can't wait to start applying what I've learned in real-world projects. Thank you to the entire team for providing such a valuable learning opportunity!
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Python Basics: Covers core Python concepts like variables, data types, control flow, functions, and libraries.
Data Manipulation Libraries: Introduces Pandas for data analysis and NumPy for numerical computing.
Data Visualization: Teaches Matplotlib or Seaborn for creating charts and graphs to explore data. -
It's a brilliant course for beginners who are enthusiastic about Data Science and this course takes it very efficiently throughout the python and it's libraries like Numpy, Pandas, Matplotlib and sklearn as well. Just one thing that it does not have practical projects for us to implement on our own.
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It was actually good most beginner try to find the best course to enchance their skills .this course has give me enogh knowledge to enchance and learn musch more about python used for data science.this course not teaches but also more thinking skills has ben developed
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this platform enhance my skills and help to improve my skills i learn alot from this course,numpy ,pandas, matplotlib are important library for data science and i learn from this course in easy ways...
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It's very nice one but video not well clear.
I can't see well what they typing code . But the explanation of every point is next level -
Python with data science course which I took is good one and this has good explanation and video quality is good
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python for Data Science - Course for Beginners offers an accessible introduction to the world of data science using Python. The course efficiently covers foundational Python concepts while integrating its practical application in data science. The modules are well-structured, with hands-on exercises that cater to real-world scenarios. For beginners, the course provides a clear and engaging roadmap to mastering essential tools and techniques. The instructors are knowledgeable, and the course materials are up-to-date. While it's tailored for newcomers, even those with a slight background in Python can benefit from the data-centric approach.
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This course helped me gain deeper insight in Python, especially in functions, modules etc. The Projects and assignments are of very good standard. Projects will make you apt in using functions and also be helpful in OOP. You will learn a lot while doing the Projects, mark my word. And last but not the least Standard Teaching
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a Python for Data Science course for beginners is a great starting point for anyone looking to learn how to use Python for data analysis. It covers the basics of Python programming and popular data science libraries like Pandas, NumPy, and Matplotlib. With this knowledge, you will be able to start working with data and drawing insights from it.
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Information is better but explanation must be still more deep than this. But I didn't got the source file of or Data of Covid. Anyone reply me how can I get it. However I understood the concept.
Thank You -
Godd course for basic understanding of pandas , numpy and matplotlib. One can definitely go through this course before buying expensive courses as this will help understanding the paid courses well.
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It was a very nice course to learn from. Appreciate the hardwork whoever has made this course for the beginners. It's a boon for every beginner who want to transit their career to data science.
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It is nice i learned more than i tink it is nice come and learn i love it i give it 3 b/c the language is not clear English that why i give it 3 star
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Neat and clear for beginners. It was very useful to learn. The videos are easily understandable. Explained everything clearly from basics.
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Very effective learning for beginners. The explanation Canberra more in depth. Otherwise the full learning concept is very explanatory.
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I hopefully enjoyed this course. It is very helpful for the beginners who wants to learn python from the scratch.
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I've learned the basics of python, from the importance of using python programming language to manipulating data through pythons extensive library.
This course helped me understand coding skills as well as data science and data analysis. I can declare variables, write functions and manipulate data structures.
I understand how to analyse data through the various libraries as pandas etc
Thanks for the opportunity and challenge.