This video on Python will take you through all the basics and advanced concepts present in Python programming language. You will learn about data types, variables, lists, tuples, dictionaries, and a lot more. You will understand how to use decision-making statements and loops in Python. You will get an idea about creating user-defined functions and learn the various object-oriented programming concepts along with threading and Python scripting. Then, you will learn the various machine learning libraries available in Python, which includes NumPy, Pandas, Matplotlib, Scikit-Learn. Finally, you will come across a few important interview questions that you could face in any Python interview. Now, let’s dive into learning Python in detail.
Below topics are explained in this Python tutorial:
- Python installation in Windows 10 (00:33)
- Jupyter Notebook tutorial (04:02)
- Python Variables (22:42)
- Python Numbers tutorial (47:00)
- Python Tuples tutorial (1:19:11)
- Strings in Python (01:39:41)
- Python Sets & Dictionaries (02:01:57)
- Python if,else statements (02:20:24)
- Python Loops tutorial (02:32:48)
- For Loop in Python (02:54:49)
- While Loop in Python (03:13:57)
- Arrays in Python (03:44:20)
- Functions in Python (03:57:20)
- Python Objects & Classes (04:12:48)
- Python Threading (04:49:08)
- Python scripting for beginners (05:03:18)
- Top 5 Python libraries (05:27:11)
- NumPy tutorial (05:42:55)
- Python Pandas (06:12:59)
- MatplotLib tutorial (06:58:18)
- Scikit-Learn tutorial (07:50:09)
- Web scraping using Python (08:33:43)
- How to become a Python developer (09:11:41)
- Python interview questions and answers (09:21:08)
We will also be looking at various inbuilt functions used with the data types in Python, functions as objects, args and kwargs keywords, constructors and even plotting different graphs. Finally, we will learn to build, train and test a random forest model using the Scikit-Learn library.
By the end of this tutorial you will learn to write programs in Python and basics of using Python for Machine learning and Data Science applications.
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