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Data Visualization in Python for Machine Learning Engineers – Udemy

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What you’ll learn

  • You’ll learn Matplotlib and Seaborn and have a solid understanding of how they are used in applied machine learning.
  • You’ll work through hands on labs that will test the skills you learned in the lessons.
  • You’ll learn all the Python vernacular specific to data visualization you need to take you skills to the next level.
  • You’ll be on your way to becoming a real world machine learning engineer or data engineer.

Welcome to Data Visualization in Python for Machine learning engineers.

This is the third course in a series designed to prepare you for becoming a machine learning engineer

I’ll keep this updated and list only the courses that are live.  Here is a list of the courses that can be taken right now.  Please take them in orderThe knowledge builds from course to course. 

  • The Complete Python Course for Machine Learning Engineers 
  • Data Wrangling in Pandas for Machine Learning Engineers 
  • Data Visualization in Python for Machine Learning Engineers (This one) 

The second course in the series is about Data Wrangling. Please take the courses in order.

The knowledge builds from course to course in a serial nature. Without the first course many students might struggle with this one. 

Thank you!!

In this course we are going to focus on data visualization and in Python that means we are going to be learning matplotlib and seaborn.

Matplotlib is a Python package for 2D plotting that generates production-quality graphs. Matplotlib tries to make easy things easy and hard things possible. You can generate plots, histograms, power spectra, bar charts, errorcharts, scatterplots, etc., with just a few lines of code.

Seaborn is a Python visualization library based on matplotlib. Most developers will use seaborn if the same functionally exists in both matplotlib and seaborn.

This course focuses on visualizing. Here are a few things you’ll learn in the course

  • A complete understanding of data visualization vernacular.
  • Matplotlib from A-Z. 
  • The ability to craft usable charts and graphs for all your machine learning needs. 
  • Lab integrated. Please don’t just watch. Learning is an interactive event.  Go over every lab in detail. 
  • Real world Interviews Questions.

                                                           **Five Reasons to Take this Course**

1) You Want to be a Machine Learning Engineer

It’s one of the most sought after careers in the world. The growth potential career wise is second to none. You want the freedom to move anywhere you’d like. You want to be compensated for your efforts. You want to be able to work remotely. The list of benefits goes on. Without a solid understanding of data wrangling in Python you’ll have a hard time of securing a position as a machine learning engineer. 

2) Data Visualization is a Core Component of Machine Learning

Data visualization is the presentation of data in a pictorial or graphical format. It enables decision makers to see analytics presented visually, so they can grasp difficult concepts or identify new patterns. Because of the way the human brain processes information, using charts or graphs to visualize large amounts of complex data is easier than poring over spreadsheets or reports. Data visualization is a quick, easy way to convey concepts in a universal manner – and you can experiment with different scenarios by making slight adjustments. 

3) The Growth of Data is Insane 

Ninety percent of all the world’s data has been created in the last two years. Business around the world generate approximately 450 billion transactions a day. The amount of data collected by all organizations is approximately 2.5 exabytes a day. That number doubles every month.  Almost all real world machine learning is supervised. That means you point your machine learning models at clean tabular data. 

4) Machine Learning in Plain English

Machine learning is one of the hottest careers on the planet and understanding the basics is required to attaining a job as a data engineer.  Google expects data engineers and their machine learning engineers to be able to build machine learning models.

5) You want to be ahead of the Curve 

The data engineer and machine learning engineer roles are fairly new.  While you’re learning, building your skills and becoming certified you are also the first to be part of this burgeoning field.  You know that the first to be certified means the first to be hired and first to receive the top compensation package. 

Thanks for interest in Data Visualization in Python for Machine learning engineers.

See you in the course!!

Who this course is for:

  • If you want to become a machine learning engineer then this course is for you.
  • If you need to learn Python for machine learning then this course is for you.
  • If you want to learn how to use matplotlib for real world applications then this course is for you.

Course content

  • Introduction
  • Plotting in Matplotlib
  • Customizing Our Charts
  • Annotations
  • Seaborn

10 reviews for Data Visualization in Python for Machine Learning Engineers – Udemy

  1. Donny Phan

    Super practical. Lessons are catered towards anyone looking to find work in this industry. It felt very comprehensive and gave me a broad understanding of the programming spectrum

  2. Madhav raj Verma

    Thanks for your great effort. i am fully satisfied with this course the way you teach and your explanation are very clear ,The content you provide in your course no one can do this at this price.

  3. Sachin Gupta

    I really didn’t want to leave a low rating as Angela is a great teacher. The 1st half of this course was terrific. The 2nd half was terrible. Under the justification of “teaching students how to figure things out on their own”, pretty much all videos and all explanations were dropped. You were just told what to do, given links to documentation and told to figure it out on your own. I understand doing that to some degree, but to revert to that entirely for nearly half the content barely makes this a course. It’s just a list of things for you to learn, then you’re left on your own to learn them. The 2nd half was so bad, especially the data science component, that I didn’t bother finishing the course.

  4. Vincent Beaudet

    Amazing 40 days course.
    Angela is a great teacher.
    The other 60 days are all about web developement, interacting with web pages, on your own with little to no explanations. I did not expect that at all. I wanted to learn more about software and scripting.
    This left me disappointed , confused and i started to doubt myself. Not a fun experience after the amount of effort i’v put in this course.

    Exercices format and explanations for the first 40 days were worth it tho.

  5. Ben K

    Not just an introduction to python, but really helps you learn fundamental aspects of python and coding in general. Some parts may require some knowledge on the subject (data science comes to mind) and there is quite some web development in the course. So, a few areas were not completely to my liking (I would have liked to see it done differently), but this course deserves the 5 stars in my opinion.

  6. Omid Alikhel

    I found the method a bit difficult when a code is written and then changed back to something different, with no enough explanation of how something happened and where it came from or a step by step explanation of why something is happening, i have no doubt in the instructors talent, but we are beginners!

  7. Devang Jain

    The course is not updated and most of the solution codes don’t work and there are no video solutions towards the end

  8. Szymon Kozak

    I think that the course tutor is really good in giving right information to learn at the right time. Thanks to this fact, my understanding of coding in python after 29 days of learning is above my expectations.

  9. Begoña Ruiz Diaz

    Ha sido la mejor elección que podría haber hecho.

  10. Vaibhav Sachdeva

    I want to thank Angela for making such an amazing course. It really helped me explore more things with python.

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