Python is a popular and dynamic programming language. Part of what makes this language so popular is its versatility. It can be used for software development, data science, web development, and financial analysis, among other things. Given Python’s widespread applications, it is an excellent language to learn for anyone interested in pursuing a programming career.
This language is open-sourced, meaning it’s easy to find resources online (including libraries, frameworks, and other packages). Individuals who use Python can refer to online message boards and other community groups to gain insights and troubleshoot code. Python’s open-source nature also enables both established and new programmers to share, edit, and collaborate on one another’s code.
Features of Python
Given Python’s straightforward syntax, this language is easy to learn and read. This code is made up of English keywords, so individuals who are learning how to code can quickly see how a piece of code relates to an operation or command. Additionally, its versatility makes it an excellent language for beginners.
Individuals who know how to code with Python can apply their skills to many different career paths, making it an incredibly lucrative language to know. This versatility also makes Python a good language choice for younger people who are still not confident about what they would like to pursue as a long-term career.
Some of the most popular uses of Python are listed below:
- Data analysis
- Data visualization
- Machine learning
- Automation
- Software development
- Financial forecasting
There are also numerous libraries and frameworks available for Python programmers. These libraries enable coders to quickly find and apply code to whatever project they’re working on. Libraries are particularly useful for machine learning, automation, and data visualization and are discussed in more detail in the next section.
Popular Python Libraries
Individuals who use Python for data science will appreciate libraries like Pandas, Matplotlib, Scikit-learn, and NumPy. Generally speaking, programmers can find these libraries in online repositories like GitHub. Using GitHub, programmers can easily share code and see changes that have taken place over time.
The Python library known as Pandas is used for data analysis and machine learning. Using Pandas, programmers can index large amounts of data and write data across many formats, including Microsoft Excel and SQL.
Individuals who would like to use Python for data visualization will benefit from Matplotlib. This library can be used alongside NumPy and enables programmers to build charts, graphs, and animations. The library Scikit-learn can also be used for analyzing and visualizing data. In particular, this library is particularly helpful for statistical modeling and data analysis.
Who Uses Python and Why?
Python is an incredibly versatile programming language, meaning its code can be used in a wide range of professions. In particular, this includes roles like Data Scientist, Software Engineer, Financial Analyst, and Web Developer, to name a few.
Data Scientists use Python and its related tools to clean, analyze, model, and visualize data. As mentioned above, Python’s various data science libraries make it straightforward for individuals to find and apply code to their intended usage. These libraries come with a repository of code that can be used for frequently-accomplished tasks. In doing so, Data Science can more efficiently process and analyze large amounts of data.
Both Data Scientists and Software Engineers also benefit from Python’s applications in machine learning. Machine learning is when programs “learn” by taking in large amounts of data and identifying trends and patterns. In doing so, these programs can then make more accurate predictions.
Because Python helps programmers make sense of large amounts of data, this language is also a helpful tool for Financial Analysts. Individuals in this profession can use Python to conduct analyses and build forecasts on the financial well-being of a business or organization. Similarly, Financial Analysts can use Python to make predictions and forecasts about possible financial decisions.
Web Developers typically use Python on the back end of platforms. In particular, this might look like working with a website’s servers to ensure that everything is running smoothly or even building server-side web applications. Additionally, Web Developers can use Python when working with application programming interfaces (APIs) and frameworks like Django.
Learn Python
Learning Python has never been easier. Individuals who would like to learn how to code with this language might consider enrolling in a live or in-person class through an NYIM partner school, Noble Desktop. This school offers a variety of Python courses, including learning this language for data science, machine learning, and software engineering. Classes are kept small, and some even offer 1-on-1 mentorship opportunities, making them a great option for those looking to change or grow in their careers.
Noble’s Python for Data Science Bootcamp teaches students about the basics of coding with Python, including concepts like object-oriented programming and understanding different data types. The course then moves into applying Python for data science. Students learn to use tools like NumPy, Pandas, and Matplotlib to analyze and visualize data. This course serves as a solid foundation for those interested in using Python for machine learning.
After learning the basics of Python for data science, individuals can enroll in the Python Machine Learning Bootcamp. In this class, students learn about linear and logistic regression and then move on to machine learning algorithms like k-nearest neighbors, decision trees, and random forest. This class meets for a total of 30 hours.
Noble’s Python Developer Certificate is a good option for those looking to learn Python for software development. In this course, students learn the basics of Python, including its syntax. This course also covers APIs, object-oriented programming, Django, and SQL. Like all of Noble’s courses, this is a hands-on class, and students have the opportunity to complete projects that can then be added to their portfolios.
In addition to these classes, Noble Desktop offers other Python courses for beginners to experts. You can learn more about Python classes here.
