Python is a powerful programming language and yet easy to learn for those seeking a career in software engineering and development. The language has gained substantial popularity due to its easy-to-understand syntax and ability to be used in Machine Learning, Data Science, Web Development, Artificial Intelligence, and more fields. This course is designed to tutor you python in the easiest way possible.
Where is Python used?
Python is literally everywhere! Below are some of the areas where Python is implemented:
Visualizations and data analysis
Python can create various data visualizations, including line and bar graphs, pie charts, histograms, and three-dimensional plots. Additionally, Python provides libraries like TensorFlow and Keras that help programmers create data analysis and machine learning applications more rapidly and effectively.
Python Programming Language is a fantastic option for developing computer applications. It is an excellent language for prototyping because development requires less time and effort. Python’s cross-platform capabilities make app development simple, just like they do for websites. Because of its solid frameworks and real-time testing, Python has recently gained popularity, particularly in the quickly expanding industries of Blockchain and Gaming Development.
Machine learning and Data Science
Python has established itself as a standard in Data Science, allowing data analysts and other experts to utilize it to perform intricate statistical computations, design machine learning algorithms, and handle and analyze data, among other activities.
Fintechs and financial analysis
Python is a straightforward but powerful programming language that aids in creating cutting-edge financial applications. Python is ideal for traders and analysts because it has outstanding data analysis and modeling capabilities. Algo trading is used in many Python-based FinTech projects today to comprehend stock price movements better.
Python development is quite strong for applications in finance and Fintech. Due to its effective utilization of data, it is used in Fintech. After C and Java, Python is currently the third most used programming language.
Search Engine Optimization and Marketing (SEO, SEM)
Python is about automating tedious activities so that you may focus more on other Search Engine Optimization (SEO) initiatives. Python might save you a ton of time and work, but not many SEOs use it to solve problems, for instance, Preparation for data, data extraction, Deep Learning, etc.
What will you learn in this course?
This course is designed for beginner programmers with little to no programming experience. The fundamental concepts are covered in the first few lessons. There are some advanced topics towards the end of the course, such as object-oriented programming langue with Python.
When was Python developed, and who is the Founder of Python?
Guido Van Rossum created Python in the late 1980s. In honor of the well-known comic series, he named this language “Monty Python’s Flying Circus” (not after Python-the snake). At that time, Python development got underway. Soon after, in December 1989, at the Netherlands-based Centrum Wiskunde & Informatica (CWI), Guido Van Rossum started working on application-based projects. He initially started it as a hobby project since he sought something fun to do over the holidays. The programming language that Python is supposed to have outperformed is called ABC Programming Language; it contained exception handling and interfaced with the Amoeba Operating System.
In 1991, the language was eventually made public. When it was first introduced, it had more than enough power to offer classes with inheritance, many fundamental data types, exception handling, and functions. Compared to Java, C++, and C, it required much less code to describe the concepts when it was first published.
Python Tools and Frameworks
The following is a collection of crucial programs and frameworks for creating various Python applications:
- Web Development: Django, Pyramid, Bottle, Tornado, Flask, web2py
- GUI Development: tkInter, PyGObject, PyQt, PySide, Kivy, wxPython
- Scientific and Numeric: SciPy, Pandas, IPython
- Software Development: Buildbot, Trac, Roundup
- System Administration: Ansible, Salt, OpenStack