Learn the basics of the Python programming language.
This course teaches the foundations of computer science. This video is lecture 6 of Harvard University’s CS50 2018 course (part 7 since the lectures start at 0).
⌨️ (0:00:00) Introduction
⌨️ (0:00:50) Week 5 Recap
⌨️ (0:13:01) resize.py
⌨️ (0:16:52) Python Syntax
⌨️ (0:23:48) Interpreting vs. Compiling
⌨️ (0:26:52) hello.py
⌨️ (0:29:54) string0.py
⌨️ (0:33:02) string1.py
⌨️ (0:35:00) ints.py
⌨️ (0:38:26) floats.dpy
⌨️ (0:42:58) overflow.py
⌨️ (0:46:26) conditions.py
⌨️ (0:48:53) answer.py
⌨️ (0:50:57) cough0.py
⌨️ (0:51:40) cough1.py
⌨️ (0:52:19) cough2.py
⌨️ (0:57:01) cough3.py
⌨️ (1:01:26) positive.py
⌨️ (1:06:51) capitalize2.py
⌨️ (1:11:46) strlen.py
⌨️ (1:15:51) argv0.py
⌨️ (1:18:39) argv1.py
⌨️ (1:20:26) swap.py
⌨️ (1:22:58) list.py
⌨️ (1:27:22) struct0.py
⌨️ (1:32:38) mario0.py
⌨️ (1:33:28) mario1.py
⌨️ (1:34:45) mario2.py
⌨️ (1:35:22) mario3.py
⌨️ (1:37:57) resize.py, continued
⌨️ (1:42:36) dictionary.py
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No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas.
By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities.
Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly.
Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.
Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions.
Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events.
Simple to read and compose
Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building.
The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties.
Utilized by the best
Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player.
Massive community support
Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions.
Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking.
Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.
The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.
Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential.
The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.
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In this Data Science With Python Training video, you will learn everything about data science and python from basic to advance level. This python data science course video will help you learn various python concepts, AI, and lots of projects, hands-on demo, and lastly top trending data science and python interview questions. This is a must-watch video for everyone who wishes o learn data science and python to make a career in it.
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you’re embarking on your journey into data science and everyone recommends that you start with learning how to code. You decided on Python and are now paralyzed by the large piles of learning resources that are at your disposal. Perhaps you are overwhelmed and owing to analysis paralysis, you are procrastinating your first steps in learning how to code in Python.
In this article, I’ll be your guide and take you on a journey of exploring the essential bare minimal knowledge that you need in order to master Python for getting started in data science. I will assume that you have no prior coding experience or that you may come from a non-technical background. However, if you are coming from a technical or computer science background and have knowledge of a prior programming language and would like to transition to Python, you can use this article as a high-level overview to get acquainted with the gist of the Python language. Either way, it is the aim of this article to navigate you through the landscape of the Python language at their intersection with data science, which will help you get started in no time.
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Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?
In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.
Swapping value in Python
Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead
>>> FirstName = "kalebu" >>> LastName = "Jordan" >>> FirstName, LastName = LastName, FirstName >>> print(FirstName, LastName) ('Jordan', 'kalebu')
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