Learning Python for Data Analysis and Visualization (Udemy.com)

Learn python and how to use it to analyze,visualize and present data. Includes tons of sample code and hours of video!

Created by: Jose Portilla

Produced in 2020

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What you will 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.

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Quality Score

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Overall Score : 72 / 100

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Course Description

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python Awards Best Paid Course



PLEASE READ BEFORE ENROLLING:
1.) THERE IS AN UPDATED VERSION OF THIS COURSE:
"PYTHON FOR DATA SCIENCE AND MACHINE LEARNING BOOTCAMP"
2.) IF YOU ARE A COMPLETE BEGINNER IN PYTHON-CHECK OUT MY OTHER COURSE "COMPLETE PYTHON MASTERCLASS JOURNEY"!

CLICK ON MY PROFILE TO FIND IT. (PLEASE WATCH THE FIRST PROMO VIDEO ON THIS PAGE FOR MORE INFO)
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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! Who this course is for:
  • Anyone interested in learning more about python, data science, or data visualizations.
  • Anyone interested about the rapidly expanding world of data science!

*Some courses are excluded from this sale. Coupon not working? If the link above doesn't drop prices, clear the cookies in your browser and then click this link here.
Also, you may need to apply the coupon code directly on the cart page to get the discount.

Coupon Code

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Instructor Details

Jose Portilla

Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science and programming. He has publications and patents in various fields such as microfluidics, materials science, and data science technologies. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming the ability to analyze data, as well as present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Data Inc. and provides in-person data science and python programming training courses to employees working at top companies, including General Electric, Cigna, The New York Times, Credit Suisse, and many more. Feel free to contact him on LinkedIn for more information on in-person training sessions or group training sessions in Las Vegas, NV.

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Reviews

3.6

77 total reviews

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It is very Good Course for beginners and intermediate students and professionals.

Very good work on the flow of the course and the knowledge given!You have to update it for Python 3!

Not so much about data visualization as I expected. Mostly it's about numpy, pandas, an overview of ML and a little bit of everything. I wish I could see here more about visualizations for some practical reasons: dashboards, cohort analysis, etc.. And could be also more about libraries like plotly and bokeh, not even mentioned.

Awsome, Project lesson is well explain & I am able to know how to implement the code learn in previous exercise in real world example.

excellent explanation, but it was better if there were some assignments between lectures, so it wouldn't be boring some times during first lectures.

Few videos with low volume is the reason for low rating. Video 70 in project 3 has as good as no volume. Nothing to listen will lower ratings. Jos needs to replace those videos with new ones

Usually I live Jose`s courses. But this time it's not working...1- The codes are outdated. You will get a lot of troubles coding along. Without support for new codes...2- I am having a lot of trouble grasping how python works. I've being using R for sometime and for me I am not making the best of this course so far due to the lack of depth.Maybe if you have more knowledge than me you can take much more from it. But I do not recommend if you are a beginner.

Never have I seen a course with so much dated stuff. Python v2.0 all the way, when it's soon to be deprecated. Methods in sklearn and seaborn, many of them deprecated (just google catplot, no long usable) and all links to youtube referencing other additional info is no longer available. This course, although Jose Portilla *is* a respectable programmer and coder, this course in particular should have been made unavailable long ago, or at the very least, warned the customer that this aims for Seaborn < v0.2, "No module named 'sklearn.cross_validation'", Python 2.0, old code in general.

The modules are not up to date in the projects given. The content needs to be modified timely as the modules are updated frequently .(they should specify an alternative module which was replaced or atleast provide the links)

It is a very good course. It was also my first course about machnie learning which is unexpectedly the same thing I was studying 8 years previously.Course has a lot of interesting additional materials and a lot practical projects.Thank You!

It is good but the tutor could have gone in more detail on explaining how the functions work like this. For example np.empty, A*B and np.dot(A,B), webbrowser library

The course has great content. However, Python 2 is coming to EOL. Jose needs to update this course wit Python 3 and the newer versions of seaborn and matplotlib.