Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
21 Hour(s) 5 Minute(s)
Language
English
Rating
1 views
Course Overview
Learn python and how to use it to analyze,visualize and present data. Includes tons of sample code and hours of video!
This course will give you the resources to learn python and effectively use it analyze and visualize data! Start your career in Data Science!
You'll get a full understanding of how to program with Python and how to use it in conjunction with scientific computing modules and libraries to analyze data.
You will also get lifetime access to over 100 example python code notebooks, new and updated videos, as well as future additions of various data analysis projects that you can use for a portfolio to show future employers!
By the end of this course you will:
- Have an understanding of how to program in Python.
- Know how to create and manipulate arrays using numpy and Python.
- Know how to use pandas to create and analyze data sets.
- Know how to use matplotlib and seaborn libraries to create beautiful data visualization.
- Have an amazing portfolio of example python data analysis projects!
- Have an understanding of Machine Learning and SciKit Learn!
With 100+ lectures and over 20 hours of information and more than 100 example python code notebooks, you will be excellently prepared for a future in data science!
Please make sure you read the entire page to understand if the course is the correct version for you.
Course Content
- 15 section(s)
- 110 lecture(s)
- Section 1 Intro to Course and Python
- Section 2 Setup
- Section 3 Learning Numpy
- Section 4 Intro to Pandas
- Section 5 Working with Data: Part 1
- Section 6 Working with Data: Part 2
- Section 7 Working with Data: Part 3
- Section 8 Data Visualization
- Section 9 Example Projects.
- Section 10 Machine Learning
- Section 11 Appendix: Statistics Overview
- Section 12 Appendix: SQL and Python
- Section 13 Appendix: Web Scraping with Python
- Section 14 Appendix: Python Special Offers
- Section 15 BONUS SECTION: THANK YOU!
What You’ll Learn
- Have an intermediate skill level of Python programming., Use the Jupyter Notebook Environment., Use the numpy library to create and manipulate arrays., Use the pandas module with Python to create and structure data., Learn how to work with various data formats within python, including: JSON,HTML, and MS Excel Worksheets., Create data visualizations using matplotlib and the seaborn modules with python., Have a portfolio of various data analysis projects.
Skills covered in this course
Reviews
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JJoseph Alexander guerrero
Yes, after the first section of scalars i started to get the hang of it.
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CChris Bennett
Okay, so overall the course does a reasonable job of teaching about performing data analysis in Python, with reasonable coverage of Pandas, Numpy, seaborn and matplotlib and some coverage of machine learning. Overall, I think that this course improved my comfort level with these areas, and I think that in general the instructor does a decent job of explaining things. However, in many cases, and particularly later on in the course it felt as though he was literally copying and reciting code and examples from elsewhere, which made it difficult to determine how much of this material he should be credited for himself... however with over 200,000 students, and over 10 years old, it is possible others have adapted it in some cases? The largest problem with the course is that it is considerably outdated and although it says it was last updated a few years ago, much of the code does not work and I had to spend a lot of time finding workarounds or updating the code to be compatible, which became a continual source of annoyance and frustration. Many of the comments and questions have not been answered for years by the instructor (essentially abandoned?), although given the large number of students, often the students have posted their own answers, solutions and updates. However, since the goal of me taking the course was to increase my comfort levels with these modules, and it was successful, I am still trying to give the course a decent rating.
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CChristo Diedericks
Nice step at a time with good examples... I am really enjoying the way you train...
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PPercy Manuel Huancoillo Ticona
Excelente¡¡¡
