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Yash Tiwari
Yash Tiwari

Posted on • Updated on • Originally published at Medium

Top 7 Python Skills To Advance in Python Programming

Python has steadily gained popularity as one of the most popular programming languages for a range of tasks in the industry over the past few years. It has been slowly taking over the world of software development and machine learning, and not a day passes without mentioning it in the media. This blog will look at exactly why learning python is essential and the skills you need to excel in Python.

Why Should You Learn Python?

Programmers use Python as an easy and more efficient alternative to languages like C, R, and Java for similar purposes. As a result, Python has become the language of choice for many applications.

Among its most popular uses, Python is used in Data Mining, Data Science, AI, Machine Learning, Web Development, Web Frameworks, Embedded Systems, Graphic Design applications, Games, Network development, Product development, Rapid Application Development, Testing, Automation Scripting, and so on.

Basically, free udemy courses are one of the suggested ways to learn Python. Let us now move on to the Python skills required to advance in Python Programming.

Expertise in Core Python

It is essential to master the core fundamentals of any programming language before venturing out into the world of technology. Similarly, when it comes to Python, there are a few concepts that you must be well aware of because they form the foundation of the language itself. These include:

  • Data Structures
  • Variables & Data Types
  • OOPs Concepts (Object-Oriented Programming)
  • Exception Handling
  • Iterators
  • File Handling
  • Generators

If you don't know where to start, the Internet is full of useful and worthwhile resources. Also, Core Python tutorials and reference books will offer you several details about these topics, so you can even use them to learn more.

Adequate Understanding of Python Frameworks

For developers, Python frameworks are a lifesaver. Their main advantage lies in their ability to create faster development processes by eliminating the need to worry about low-level details like sockets, protocols, and threads. There are multiple Python frameworks, including Django, Flask, Web2Py, and Bottle, that you can choose.

A great Python web developer can make a difference when using either of two web frameworks, Django and Flask. With Django, you can make your web applications look clean, logical, and pragmatic. Meanwhile, Flask is a micro-framework for Python used for building apps.

Data Science

Data science is more of an art form. Once you start digging into the same, there are some prerequisites that you should know starting from your high-school level math - i.e. basic probability, stats, etc. Other most common aspects are as follows:

  • Data Analysis
  • Good Knowledge of SQL
  • Data Visualization
  • Use of Python Packages like MatPlotlib, and NumPy for Data Science.
  • Data Wrangling and Data Cleaning

Learning Data Science will help you excel in Python programming and make you a better programmer in the long run.

AI and Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) are two technologies generating a stir in the industry. Part of the reason for this is that these two concepts are exploding, and with so many entrepreneurs moving towards them for growth and development, more businesses are springing up everywhere you look.

To stay ahead of the curve in this field, you'll need to understand key core concepts in machine learning and artificial intelligence, such as clustering, regression analysis, and perhaps how neural networks function.

Python Libraries

Python contains around 379,390 projects, according to the Python Package Index. There's a good probability that whatever you're going to make has already been done and is accessible for use, complete with documentation.

Since you will be using packages daily, you should be skilled enough as a Python developer to find, study, and properly implement packages offered by the Python ecosystem. The Python libraries cover several topics, including Artificial Intelligence, Machine Learning, Data Science, and many others. The best part is that the Python community is very active and welcoming where you will get help easily.

Deep Learning

Deep Learning also plays a crucial role similar to Machine Learning and AI. It is a part of Machine Learning, and much like the human brain, it's a system that can detect patterns incredibly well. Once you understand what Deep Learning is, you should be able to apply your newfound knowledge to create Deep Learning-powered systems like:

  • Automatic Speech Recognition -Image Recognition
  • Natural Language Processing
  • Image Restoration
  • Recommendation Systems and much more.

Object Relational Mappers

Object-Relational Mappers (ORMs) are essentially classes of libraries that facilitate transferring data between a relational database and Python objects. These libraries allow developers to directly change data in databases using Python code instead of SQL. Many ORM libraries for Python are available, including SQLAlchemy, Peewee ORM, Django ORM, PonyORM, and Tortoise ORM.

Additionally, ORM libraries can help you save enormous development time while providing the flexibility to switch to another relational database when required.


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