Learn Python: Importance, Skills, and Training Paths
Python is one of the most popular programming languages that data scientists, engineers, and web developers use. Even people who’ve never heard of Python likely use the websites and apps that rely on it, from Netflix to Google, YouTube, and Instagram.
What exactly is Python? What makes it distinct from the hundreds of other programming languages?
Python is open source: It’s free to download, use, and distribute. For those who are exploring options for learning Python and other tech skills, mastering a programming language is an invaluable capability that can lead to a range of career opportunities.
Why Learn Python?
Python is the top programming language in the world, according to Statistics Times. Programmers, engineers, and developers all over the world use it for a wide variety of applications. This didn’t happen by chance. Information technology (IT) professionals prefer Python as their programming language of choice for many reasons.
It’s Easy to Learn and Easy to Work With
Python’s developers intentionally made it an approachable language. Python is used as an introductory language for computer science students just starting out with programming languages. It’s a great precursor to learning Java or C++.
Python uses simplified syntax that mimics natural language, so the code isn’t as complex as other languages. Aesthetically speaking, the code is much cleaner, which is why so many programmers prefer it. Python also offers a vast array of functions in its standard library; this cuts way down on having to code functions from scratch.
Python Is Versatile
Some programming languages are niche and can only be used for very specific purposes. By contrast, Python is the Swiss Army knife of programming languages. Python is used in machine learning, data visualization, web and app development, automation scripts, financial technology (fintech), video game development, graphical user interface (GUI) applications, robotics, rapid application development, and embedded applications, just to name a few areas. Learning how to use Python opens up a world of possibilities.
Python Is Being Used in Several Industries
People like to keep their options open, and that’s been a major reason why they learn Python. Virtually every industry is using Python to some degree for analysis, development, or other applications. Some top industries using Python are academia, electronics, government, manufacturing, technology, marketing, finance, healthcare, and insurance. Although many Python programmers work in tech, several opportunities exist beyond that.
Hiring Managers Are Looking for People Who Know Python
Python was the second most sought-after programming language among job candidates in a recent analysis by Devjobsscanner. Python was specifically mentioned in 19% of the job postings (about 209,000 jobs) by companies looking for candidates from October 2021 to June 2022. Hiring managers have a need for this skill, and the demand for it isn’t projected to decline anytime soon.
Developing Python skills and an overall competency for the language doesn’t happen overnight. Learning Python starts by picking up the basics through study and various exercises. Python programming for beginners is an excellent place to start for those who are learning a programming language for the first time.
Basic Python Topics and Terms
Aspiring Python programmers will need to master these introductory concepts:
- Python keywords: Keywords are reserved for specific purposes and can’t be used as variables or function names. Keywords define the structure and syntax of Python’s language.
- Python identifiers: Identifiers can be a combination of lowercase letters, uppercase letters, numbers, and underscores. Identifiers are the names used for entities such as classes, variables, and functions. Remember to use names that make sense when labeling identifiers.
- Python statements: Statements iare instructions that the Python interpreter executes. Python has four main types of statements: print statements, assignment statements, conditional statements, and looping statements. Python script code consists of a series of statements, which can be multiline, compound, or simple.
- Python indentation: Python uses indentation to denote a block of code, while most programming languages use curly braces. In Python, a block of code starts with an indentation and ends with the first unindented line.
- Variables: Variables are containers for storing data values in Python. Variables can be changed at any time.
- Constants: Constants are variables with values that can’t be changed.
- Literals: Literals are raw data that’s given in a variable or constant. Literals come in different varieties, including numeric, string, Boolean, and special.
- Python functions: Functions allow users to divide code into useful blocks and give it a sense of organization. This is also how interfaces are defined, and it comes in handy when programmers want to share their code with others.
- Python conditions: Python uses Boolean logic when evaluating conditions. Boolean operators such as “and,” “or,” “in,” “if,” “is,” and “not” allow for complex expressions.
- Python loops: Python features two types of loops. “For” loops iterate over a sequence of numbers using the range and xrange functions, and “While” loops repeat as long as a specific Boolean condition is met. A loop can be exited by using the break function.
- Python numbers: Python numbers include floating point numbers, integers, and complex numbers.
- Python list: A Python list is an ordered sequence of items that can be changed.
- Python tuple: A Python tuple is a list that can’t be changed. Tuples are used to protect written data.
- Python strings: A Python string is a sequence of Unicode characters that can be represented with either single or double quotes. Strings can be set to be unmodifiable.
- Python set: A Python set is a collection of unique items in no particular order. Values are separated by commas.
- Python dictionary: A Python dictionary is a collection of key-value pairs in no particular order. They’re used to retrieve data.
- Implicit type conversion: An implicit type conversion is the process of automatically converting data of one type to another without user involvement.
- Explicit type conversion: An explicit type conversion is the process in which the user converts data from one type to another using functions such as int(), float(), or str().
- Python output: The print() function outputs a message to the screen or other output device.
- Python input: Python allows input from the user, even when variables are already defined or hard-coded into the source code.
- Python import: Python allows for the importing of modules to be stored in a directory.
- Python operators: Python operators are special symbols that perform a logical computation or mathematical command. This allows users to add, subtract, divide, and so forth using numerical values. Users can also use comparison values such as less than, more than, or equal to. Other operators include logical operators, bitwise operators, assignment operators, identity operators, and membership operators.
Advanced Python Topics
For those just beginning to learn Python, it can take weeks of practice to master the basics. When they’re ready to take on an additional challenge, they should focus on these advanced Python topics:
- Python generators: Python generators allow users to create their own iterator functions with a sequence of values.
- List comprehensions: List comprehensions create a new list based on another list in a single line of code using short syntax.
- Lambda function: The lambda function is a single-line function that can have many arguments but only one expression. It works similarly to the “def” keyword.
- Multiple arguments function: Using formal parameters in the function definition, Python can pass multiple arguments as opposed to a single argument.
- Exception handling: “Exception” is another word for “error.” In exception handling, the user identifies and resolves the portion of a script that’s causing an exception. Several different varieties of exception can occur.
- Code introspection: Code introspection is the ability for a user to examine and understand functions, keywords, and classes.
How to Learn Python
There are a few ways to learn Python, some of which are more effective than others.
A wide variety of free online resources are available that cover Python programming for beginners through advanced Python topics. Simple questions like “What is Python syntax?” and “How do basic string operations work?” can usually be answered with a quick Google search. More difficult questions may take some additional digging and problem-solving. However, self-teaching isn’t for everyone. It can be an ineffective process for those who aren’t self-motivated to study every day or who don’t have time for it. Self-teaching also lacks oversight and feedback from coding experts.
For those who are considering the traditional university route of education, many computer science degree programs teach Python, along with the foundations of computer science, C programming, and data structures and algorithms. However, the standard computer science bachelor’s degree program takes four years to complete and can cost tens of thousands of dollars in tuition. Those who want to learn Python faster without going into debt are encouraged to look at alternatives.
Another method of learning is taking courses through intensives or bootcamps. These bootcamps teach a specific coding language in as little as 12 weeks. However, most bootcamps require a significant financial investment, and they may cover a limited range of skills.
The Revature Method
Revature offers a departure from traditional methods, with some distinct advantages. Revature associates learn specific tech skills, including coding languages, during 10- to 14-week customized training programs. However, rather than charging students tuition or enrollment fees, Revature pays associates to learn. Additionally, Revature associates are placed in a job once they complete their training — no need to go through the job-hunting process. This can be the ideal solution for those who want to learn tech skills while getting compensated and immediately be placed with one of our partner companies.
Python Exercises and Quizzes
Even though Python is considered one of the easier programming languages to learn, it still takes study and practice. A great way to test new skills is by taking quizzes and engaging in practice exercises. Free online tests can assess the many different areas, skills, and competencies of Python. Here are a few examples:
- Real Python — Python Quizzes
- PYnative — Python Quizzes
- Tutorials Point — Python Online Quiz
- GeeksforGeeks — Python Quizzes
- PYnative — Practice Python Exercises and Challenges with Solutions
Python is best approached in a natural progression of modules, starting with the basics, and then steadily taking on more advanced concepts.
- Step 1: Python programming for beginners lays the foundation for more complicated tasks ahead. Learn the fundamental concepts and basic data structures. That includes variables, operations, data types, functions, conditionals, and loops. Advancing in Python requires a firm comprehension of the fundamentals.
- Step 2: Practice OOP concepts, and work on structured projects. Once users master the basics, they should be able to start designing and structuring code of their own. The code will likely have flaws, so it’s also a good opportunity to practice resolving errors (exception handling).
- Step 3: After working with Python on structured projects, users can move on to more complex projects that test their base knowledge while also introducing more advanced concepts, such as generators and iterators. By this point, users should have a firm grasp on OOP hallmarks: encapsulation, abstraction, inheritance, and polymorphism.
- Step 4: Programmers learning advanced Python topics will use different frameworks and packages to perform complex tasks. For example, Django is a high-level framework that uses Python to build reliable and secure websites on a rapid timeline. NumPy is a fundamental package that allows Python users to perform scientific computing. Built on top of the NumPy package is Pandas, which is used for data analysis and data science. Finally, machine learning, one of the most advanced concepts that Python users learn, consists of training a computer to respond a certain way to data sets that it’s given; it’ll subsequently learn from this data and start to predict the properties of new data.
Learn Tech Skills from the Best with Revature
Python programmers are among the most in-demand professionals in tech. Considering its wide usage across industries, learning how to use Python can open a range of opportunities. Those who put in the effort to learn Python and other coding languages and skills go on to become developers, data scientists, machine learning engineers, and plenty of other rewarding professions in tech and beyond.
The best way to begin a career in tech is by picking a method of learning with a track record of success. At Revature, you’ll spend 10 to 14 weeks getting paid to learn in-demand skills in an immersive virtual environment. Once your training is over, you’ll be set up with paid contract work through one of our partner organizations at locations across the U.S. including Phoenix, Indianapolis, Raleigh and Tampa.
Ready to kick-start your career? Take the first step with Revature.
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