Introduction to Python | Real Estate Analytics
In this module, we will cover introduction to Python. The purpose of this module is to provide an overview of Python and its benefits. The topics we will review include why learn Python, and the best method to digest learning Python.
Ariel Herrera 0:00
In this module, we will cover introduction to Python. The purpose of this module is to provide an overview of Python and its benefits. The topics we will review include why learn Python, and the best method to digest learning Python. Why learn Python? For one, Python is one of the easiest programming languages to learn. It's considered to be beginner friendly, since it prioritizes readability, making it easier to understand and use over other languages. Python is relatively fast. Due to being an interpreted and dynamically typed language. Python allows for extremely fast prototyping speeds. There are even some websites that are built off of Python. Python is also object oriented. It is a computer programming model that organizes software designed around data are objects rather than functions and logic. For us in a data analytics space. We work with a lot of data, especially in Excel and pandas data frames, which you'll see later, which is why using Python is a preferable language, Python is also strongly typed. This means the object doesn't change in unexpected ways, like an integer becoming a string. And lastly, Python is widely used and portable, we can code on Python without having to install it on our machines. For this course, we will use Google collab as our work environment. And the number one reason to learn Python. If you're looking to grow your career and data analytics, and Python is the number one language that is used across the industry. You can develop web apps, automate processes, and manipulate data all with the same programming language. You can see from the slide that there are major companies that use Python. Note this is widespread across industries from tech, finance, space, and more. The best way to learn Python is to learn through real world examples. real world examples are a problem you are currently facing and you want to solve through code. This will force you to make real connections from the concepts you learn to practical Python. A lot of courses out there will teach you in a very abstract way, you will learn Python with examples like counting the number of bananas in a basket. This is not useful. When I learned Python, I found the best sources to be examples that were related to real world problems I faced at work. In this course, you will learn Python through real world examples that relate to real estate. That is why this Python course is unique from any other Python course out there. You will absorb Python even faster since all topics will tie back to real estate, such as calculating cash flow, mortgage, looking at property information. It's all there. Now you know reasons to study Python and the best methods to learn. Meet me in the next lesson where we will cover Python for beginners, starting with data types want full access the introduction to real estate Data Analytics course. Then sign up for the course in the link below. You will learn Python programming all with real estate related examples. This includes web scraping, retrieving data from sources like Zillow, realtor, Redfin, Yahoo Finance, US census, and more. If you haven't already, check out the introduction video to the course on YouTube to get a full understanding of what the course has to offer. Also, members of the free tech and real estate group on Facebook receive a 20% off the course seeing the next lesson.
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