Python for Data Science Full Course | Data Science Tutorials for Beginners in 2022 | Great Learning

Great Learning's "Python for data science” course is all about learning exciting ways of understanding the process of analyzing data and getting to know more about open libraries.
Python for data science with python course aims to let our learners explore the multiple arenas of how to read data from multiple sources, which can be CSVs, Excel, and SQL.
It's high time to learn and upgrade yourself with the art of processing data with the aid of NumPy Pandas and articulate the act of visualization with the aid of Matplotlib and other software.
Learn how to read data, process it, visualize and create reports. We also have our primary focus on Python to help you have your biggest leap into Data Science.

Elevate your career with an Online PG in Data Science & Business Analytics. Enroll now and power ahead in your career!

🏁 Topics Covered:
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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[greatlearning]

🔹 Topics Covered:
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

[gauravvijaykaple]

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

[sudhirkumarverma]

This is one of the best video to understand the very basic concept of data science. The way he teaches is very well explained, audio quality is awesome ..!!!
No doubt 'one of the best videos for Data Science'
Thank you so much for this video.

[abhishekmahajan]

The way he started the python journey,
The way he makes python easy,
The way he tells python as a story,
The way he makes project easy in such a
I thought his way is truly
I can make a bet for freshers who never understood a single word of python ....please keep patience and learn from this video and makes notes properly...
I cam bet you will think why you haven't got this video before....
And thank you soo much for providing this content for free❤️❤️❤️❤️❤️❤️❤️

[NitishSharma-ziqr]

Amazing content presented by sir,
one little thing want to add, it would be more effective for the learners if the data used in the video would be attached with the video description!!

[riteshtripathi]

I my self had attended PKV sir's class in 2017 chennai, trust me, this professor is an awesome mentor, whenever i see any picture of him in any of your videos, without wasting another second, i go through that video. The way he showed Statistics, i doubt if i have seen any of videos by other professors so far in clarity . i would appreciate if you bring his videos more oftenly and include Bhardwaj Sir's any of his classes/videos.

[upendrachaube]

I must say you are one of the great trainers... loved the way you articulated every topics in an effective and simplistic way 👍🏻

[poojabehera]

This is explained briefly indeed...the projects includes only EDA/ did not found outliers/NAN value/model didnt build up, accuracy is not defined. hope we would get to see end-to-end DS project in coming days.

[deepakbhatlavande]

Dear Team,
would like to request you to make a special course regarding "how to export data in Python | how to preprocess and clean it for further process | with different libraries which are used like numpy etc. | specially for beginners.

[sketchpen]

This sir's explanation is awesome ..

[Goldy_Kumar_]

29:01 variable's name can start with an underscore. You should have read that carefully that it is written (except underscore).

[aanchalsachdeva]

Have gone through half of the course yet! But just loving it. Its so useful. Thank You Great Learning @Great Learning :)

[stconqueror]

Hats off to all "Great Learning" teaching staff ! Excellent Teaching 👍😊

[rumanaafrose]

One of the best videos I have ever seen on Python, great work!!! 💯

[shilpisinha]

Your way of explaination is mindblowing Sir, its a humble request to enhance the font size, we can understand properly

[ArnavMishra-sfxh]

It would be great if you could provide the links for the datasets that you have used in the projects!!

[ShuddhaSanatan-cxyw]

Didn't knew that writing the table of 2 would be so exiting!!!

[nidhisharma]

Many Thanks to Great Learning for this video!!!
I was struggling in understanding lot of Regression ML topics earlier, this served as a life savior. Various boring concepts of statistics too explained in such an interesting manner. This video is a great reference for python and Data science hands-on.
Truly appreciate the Trainer for the efforts!

[VishalKumar-xpnl]

great learning is really great sir. Sir itna mehnat sayad he ye pure youtube mein kisine kiya hoga. wow 👍👍

[lumbinisardare]

Hats off to the teacher one of the best explained tutorial for python complex things made easy .