Python has long been one of the best-known object-oriented programming languages (OOP), but today it’s among the most popular languages in the world. Along with Java and C, Python is a favorite among Data Scientists and Web and Software Developers alike.

While Python is considered an easy-to-learn programming language, how to learn it is another question altogether. A student’s approach to learning Python often depends on how and where it will be used. For example, Python Developers may take an entirely different tack than Software Engineers, and Data Analysts typically learn Python in a much different context than Back End Developers.

Beginner-Friendly But Lucrative

The U.S. Bureau of Labor Statistics reports an annual salary of around $109,000 for Data Scientists, most of whom need strong Python skills. Web development and even entry level programming jobs offer attractive salaries, too, so there are plenty of opportunities to use Python in numerous positions.

Because so many industries demand Python skills, it’s worth reviewing different approaches to learning this key programming language. As a beginner, you should develop a solid plan for learning, especially if you’ll need to master multiple additional languages as well. Whichever way you decide, researching Python through online resources should come first.

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The Data Science Approach

Data science is a broad field. Tech professionals who study this discipline can find work in sectors as diverse as healthcare, retail, and digital marketing, but there are many others that require Python. Some of the most common titles for data science positions include:

  • Data Scientist
  • Data Engineer
  • Data Science Engineer
  • Data Analyst
  • Business Intelligence Developer

While you might assume a degree program is required for any data science role, this isn’t always the case. You can become a skilled Python programmer through an online or in-person bootcamp, and in a much shorter time frame.

Noble Desktop offers a comprehensive Data Science Certificate, and it’s open to beginner level students. The course covers Python programming fundamentals, libraries like Pandas and NumPy, and training in how to build machine learning models. This program can be completed in three weeks full-time or three months part-time, and it provides mentoring from an experienced data science professional.

Included as part of the Data Science Certificate program is a Python for Data Science Bootcamp. This 30-hour course can also be taken separately, though students save by taking it as part of the Data Science Certificate. The bootcamp is an excellent introduction for students who want to transition into Python from other data-focused positions.

The Specialist Approach

Not everyone who studies Python becomes a Data Scientist or Data Analyst. Web and software development professionals are just as likely to learn Python, as well as multiple other programming languages.

If development is more your area of interest than data science or analysis, you might want to work in one of the following capacities:

Many development positions require expertise in Python, the Django REST framework, and tools like SQL and Git. Noble Desktop’s Python Developer Certificate is an appropriate program to master these essentials. It includes three weeks of full-time training, covering Python fundamentals, Django REST, VS Code, and GitHub, among other subjects. Students interested in this program should have basic HTML and CSS knowledge prior to enrollment.

Another specialized area is that of software engineering. An even more intensive program than the Python Developer Certificate, Noble’s 384-hour Software Engineering Certificate includes training in areas like Python, HTML/CSS, JavaScript, and Django, to name a few.

Other bootcamps for those interested in Python as part of a wider curriculum include a Data Analytics Certificate,Python Data Science & Machine Learning Bootcamp, and a separate FinTech Bootcamp.

Top Tools for Python Users

Since Python is required for positions ranging from Developers to Data Scientists, finding tools essential to all Python users can be a challenge. The following is a short list of libraries and frameworks popular among Python pros.

  1. Scikit-Learn - Beloved by both Data Scientists and Python Developers, Scikit-Learn is an open-source library for tasks like classification, clustering, and regression. If you learn Python, you’ll want to know more about Scikit-Learn.
  2. Selenium - One of the most prevalent automation testing tools, Selenium allows you to run tests on major browsers and operating systems. 
  3. SciPy - For mathematical and scientific programming tasks, SciPy is a free, open-source library known to data science and development pros alike.
  4. Keras - Another open-source software library, Keras is integrated into the well-known machine learning platform TensorFlow.
  5. Beautiful Soup - Type the uniquely named Beautiful Soup into a search engine, and you’ll see Python pop up immediately. This library helps programmers save time by extracting data from HTML or XML files.

Numerous other frameworks and libraries are available for Python development and data science professionals, many of them taught through Noble Desktop bootcamps. These include plotting libraries like Matplotlib, interactive apps like Jupyter Notebook, and Python-centric tools like Pandas.

Getting Certified

A growing number of Python professionals in fields of all types are finding professional certification extremely beneficial. Not only can you gain meaningful knowledge sitting for a particular certification, but you may also be able to leverage it to find better-paying positions.

Depending on their field, data science pros may want to consider some of the following certifications:

  • Microsoft Certified: Azure Data Scientist Associate - Microsoft certifications are popular, and this one focuses on machine learning (ML), predictive analytics, and other data science subjects. Addtional Microsoft certifications for data science include Azure AI Fundamentals. 
  • Certified Analytics Professional (CAP) - Data science and analytics professionals alike may benefit from this certification offered by the Institute for Operations Research and the Management Sciences (INFORMS).
  • SAS Certified Professional: Artificial Intelligence & Machine Learning - Machine Learning Engineers and other data pros demonstrate their mastery of model forecasting and optimization, natural language processing (NLP), and computer vision with this designation.

Web development professionals who use Python include not only Python Developers but also Full Stack Developers and Back End Developers. Here are a few of the most popular certifications among developers.

  • Certified Entry-Level Python Programmer (PCEP) - The first designation a Python programmer can be awarded by the Python Institute, this is the perfect place to begin showing your expertise.
  • CIW Web Development Professional - While you must pass multiple certification exams to attain this level, the Certified Internet Web Professional programs are highly respected around the world.
  • Certified Software Development Professional (CSDP) - The Institute of Electrical and Electronics Engineers (IEEE) offers this advanced certification, which demonstrates proficiency in software engineering requirements, design, construction, and testing.

Whether you get into cybersecurity, data science, or software engineering, your mastery of Python will likely be a requirement. Finding the best way to learn this top programming language is the beginning of an educational adventure that can pay off for many years to come.