Do you want to learn Python Programming Language? Learn it from the Best Python Tutorial for Beginners, Certification, Course, and Training that you will find online. Python is a high level, general-purpose programming language. It is widely used by programmers all over the world. This object-oriented programming language has a large and comprehensive standard library. Python was first built in the 1980s and since then it has been developing. The latest version of this programming language, Python 3.0, was released in 2008. Ever since it was built, Python has been used by data scientists and programmers in every country. The best thing about Python is that it is easy to understand and adaptable with any of the operating systems. Anyone can learn Python programming language and use it to analyze data, create applications, develop web, and for many other things. It is the most in-demand programming language of this time. Python programmers get highly paid jobs for their skills. We have found the best courses you can find online to learn Python and listed those in here. These online courses will help you to shape your knowledge of Python. So, get through the list and details about those courses and chose one for yourself. Pierian Data International by Jose Portilla is presenting this online course on Python. You can go from the basics to creating your own applications and games with this course. It has a rating of 4.5 out of 5 on Udemy and over 457,000 enrolled students. This python tutorial for beginners provides 24 hours on-demand video, 19 articles and 19 coding exercises with lifetime access. This course will teach you both Python 2 and Python 3. You will learn to use Jupyter Notebook system and Object-Oriented Programming with online classes. This online course on Python programming language has over 100 lectures. It also includes quizzes, tests and homework assignments. They have 3 major projects to complete a Python portfolio.
Most aspiring data scientists begin to learn Python by taking programming courses meant for developers. They also start solving Python programming riddles on websites like LeetCode with an assumption that they have to get good at programming concepts before starting to analyzing data using Python. This is a huge mistake because data scientists use Python for retrieving, cleaning, visualizing and building models; and not for developing software applications. Therefore, you have to focus most of your time in learning the modules and libraries in Python to perform these tasks. Follow this incremental steps to learn Python for data science.
Coursera Statistics, Making Sense of Data: A applied Statistics course that teaches the complete pipeline of statistical analysis MIT: Statistical Thinking and Data Analysis: Introduction to probability, sampling, regression, common distributions, and inference. While R is the de facto standard for performing statistical analysis, it has quite a high learning curve and there are other areas of data science for which it is not well suited. To avoid learning a new language for a specific problem domain, we recommend trying to perform the exercises of these courses with Python and its numerous statistical libraries. You will find that much of the functionality of R can be replicated with NumPy, @SciPy, @Matplotlib, and @Python Data Analysis Library Books Well-written books can be a great reference (and supplement) to these courses, and also provide a more independent learning experience. These may be useful if you already have some knowledge of the subject or just need to fill in some gaps in your understanding: O'Reilly Think Stats: An Introduction to Probability and Statistics for Python programmers Introduction to Probability: Textbook for Berkeley's Stats 134 class, an introductory treatment of probability with complementary exercises.