How to Learn Python for Big Data

For a relatively new language, Python has quickly taken over the data science field. Since 2016, Python has been the programming language of choice for data scientists. In this guide, we will discuss resources to learn Python for big data as well as statistics, covering job placement, salary, and growth. 

What You Need to Know About Big Data Python

Big Data Python differs from Python in that it uses data libraries alongside advanced data techniques. Data science libraries include pandas, NumPy, Matplotlib, and scikit-learn. NumPy and pandas are libraries that facilitate working with data, while Matplotlib helps you create charts with data. Finally, scikit-learn is a machine learning library. 

Below are some concepts you should familiarize yourself with before diving into these libraries. 

  • Python Fundamentals: You should learn Python first, including core concepts such as data types, functions, and conditional statements, to name a few. 
  • Command Line Interface: Using the CLI with Python allows you to run scripts faster and work with more data. 
  • Web Scraping: Web scraping allows you to collect data from the web. Building small Python projects around consuming APIs and web scraping will help you understand how to collect and work with data. 

Skills Needed to Learn Big Data Python

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The above list covers some basic technical concepts to understand. By contrast, the list below addresses what is known as “soft skills”; that is, mindset and personality traits to cultivate in order to make the most out of your Python journey. 

  • Willingness to keep learning: Technology is always evolving. In order to stay relevant in any field, it is important to always keep up with the latest trends. 
  • Curiosity and persistence: In programming, you will get stuck; that’s just a fact. Overcoming this requires curiosity to understand why the error occurred and persistence to solve it. Whether scanning docs or reading articles in forums, a lot of your time will be spent debugging. 
  • Flexibility: It’s easy to get caught in doing things a certain way. However, there are often cleaner or more conventional ways of writing the same code. Having the flexibility to adapt your code will give you more experience before the job search. 

Why You Should Learn Big Data Python

As mentioned earlier, Python is the most popular programming language for data science. If you intend to work in the data science field, learning Python is a must. Below is a list of more specific reasons to learn Python. 

  • Python is the industry standard: Python is the most used programming language for data science. As the field grows, Python grows with it; the language is here to stay. 
  • The data science field is growing: As with other tech roles, data science is an ever expanding field. These jobs will continue to be in demand for the foreseeable future. 
  • Versatility: Python is versatile and has many uses. It’s accessible to learn and has a supportive community. 

How Long Does it Take to Learn Python for Big Data?

Learning Python from scratch can take anywhere from a few months to a year with consistent practice. To this, you should add an extra three to six months for tackling the advanced concepts and libraries required to handle big data. As with all programming languages, the time it takes will vary from individual to individual. It’s far more important to master the concepts rather than focus on speed. 

Learning Big Data Python: A Study Guide

There are many ways of learning Python today, including online courses, tutorials, and community boards. You’ll find a wealth of knowledge to guide you on your way to becoming a data scientist. Below are resources to consider while you take the first steps on your path to mastering Python. 

2021 Complete Python Bootcamp from Zero to Hero by Jose Portilla

  • Resource Type: Online course
  • Price: From $19.99
  • Audience: Beginner

This Udemy course teaches beginning and advanced concepts through more than 100 lectures and 22 hours of coursework. As the title indicates, no previous programming experience is required. Instructor Portilla takes you from the fundamentals to advanced methods of working with real data. 

Learn Python 3 by codecademy.com 

  • Resource Type: Online course
  • Price: From $19.99 per month
  • Audience: Beginner 

In 30 hours of coursework and project building, you’ll go from the classic “Hello World” exercise to working with data from files. This course features three projects to get your portfolio off the ground. No previous experience is required. 

Python Tutorial by w3schools.com

  • Resource Type: Tutorial 
  • Price: Free
  • Audience: Beginner

Free tutorials are a way to test the waters before committing to an online course. The W3Schools tutorial offers well-organized and succinct explanations and exercises. Sections include instructions on how to get started working with files and user input. 

The Python Tutorial by python.org

  • Resource Type: Tutorial 
  • Price: Free
  • Audience: Beginner

In modern programming languages, the official documentation will often include tutorials. The official Python docs start with simple concepts and gradually get into advanced territory. This is also a good resource to address specific errors or issues in a project you’re working on. 

Learning Python by Mark Lutz

  • Resource Type: Book
  • Price: From $36.62
  • Audience: Beginner

This bestselling tutorial book by Mark Lutz is for complete beginners to programming or professional programmers looking to upskill. Learning Python comes complete with exercises, quizzes, and helpful diagrams to help you become proficient in this language. 

Communities for People Learning Python

Python Community

This is the official community space for python.org. Here, you’ll find a Getting Started section as well as links to the Discord and Slack communities. Sign up for the Python Weekly newsletter while you’re here. 

Full Stack Python

Full Stack Python is a community-based resource guide. It includes basic Python tutorials, guides to using different frameworks and libraries, and several educational blog posts. This community is a wealth of contemporary Python practices and conventions. 

Python Forum

This is a traditional forum consisting of moderated discussions and posts. Topics are organized by categories and address common concepts as well as troubleshooting. This forum also features a job board. 

How Hard is it to Learn Python for Big Data?

Compared to most programming languages, Python boasts great accessibility. The general consensus is that Python is relatively simple to learn, read, and write. This does not mean, however, that learning Python is easy. Learning to program, in general, is not easy, but Python is nonetheless considered a user-friendly language. 

Will Learning Big Data Python Help Me Get a Job?

If you’re passionate about data and want a career in data science, learning Python may help you get the job of your dreams. It is the most popular, most widely-used programming language for data science. Below are some stats to drive this point home:

  • Salaries: According to indeed.com, the average base salary for people with Big Data Python skills is $121,340 annually. 
  • Job Openings: At the time of writing, ZipRecruiter lists 280,664 job openings for Python developers. 
  • Job Growth: According to the US Bureau of Statistics, the data science field is projected to grow 28% through 2026. That will amount to about 11.6 million jobs. 

Conclusion: Is It too Late to Learn Big Data Python?

With the rapid rate of technology advancement, it seems like things are becoming rapidly obsolete. Some languages go out of style fast, with new ones taking over the spotlight. However, the resources and statistics presented in this article suggest that will not be the case with Python.

Python is a robust, popular, and community-driven language built on conventions. It has only been en vogue since 2016, but it is projected to keep growing; now is a great time to get started learning Python!

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