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Hey Folks! Watch this 10-hour tutorial on Python For Data Science! Python is one of the most famous programming languages in the world and is favoured in the field of data science because of it’s simple and flexible syntax, its ability to work with multiple paradigms, and the ease with which it combines with other software components. These factors have made Python be the most favoured programming with data science, which is exactly why so many people want to learn it today.
Great Learning brings you this 10-hour tutorial on Python For Data Science to help you understand everything you need to know about this topic and getting started on the journey to learn about it well. This video starts off with an introduction to Python and Python IDEs, followed by looking at data structures in Python. Then we look at object-oriented programming. Following this, we will work with some well-known Python libraries: NumPy, Pandas, Matplotlib and Seaborn. Finally, we look at linear and logistic regression, allowed by time series! This video teaches Python For Data Science and its key functions and concepts with a variety of demonstrations & examples to help you get started on the right foot.
00:00:00 Introduction
00:02:07 Agenda
00:02:59 Python, Pycharm & Anaconda Installation
00:06:21 Intro to Jupyter Notebook
00:11:15 Variables in Python
00:14:35 Data Types in Python
00:18:52 Operators in Python
00:26:43 Python Tokens: Keywords, Identifiers, Literals & Operators
00:46:14 Data Structures in Python: Tuple, List, Dictionary & Set
01:20:21 Flow Control Statements
01:44:34 Functions
01:59:32 Python Object-Oriented Programming: Class & Object
02:19:27 Inheritance in Python
02:49:55 Libraries in Python
02:51:25 Python Numpy
03:19:58 Python Pandas
03:50:03 Data Visualization with Python: Matplotlib
04:25:45 Data Visualization with Python: SeaBorn
05:26:01 Python Project on IPL Data
06:01:26 Python Project on FIFA
06:22:23 Python Project on Marvel and DC Characters
06:36:44 Introduction to Data Science
06:52:59 Machine Learning
06:56:34 Supervised Learning
07:00:40 Unsupervised Learning
07:03:25 Statistics For Data Science
07:39:11 Linear Regression
08:50:22 Logistic Regression
09:31:53 Time Series Analysis
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