Python Tutorial for Beginners | Learn Python Step By Step | Python Course

Timestamp -
00:00 Introduction
3:11 - Chapter 1:- Installing Python framework and Pycharm IDE.
5:25 - Chapter 2:- Creating and Running your first Python project.
7:27 - Chapter 3:- Python is case-sensitive
7:49 - Chapter 4:- Variables, data types, inference & type()
9:27 - Chapter 5:- Python is a dynamic language
10:21 - Chapter 6:- Comments in python
13:43 - Chapter 7:- Creating function, whitespaces & indentation
14:53 - Chapter 8:- Importance of new line
16:11 - Chapter 9:- List in python, Index, Range & Negative Indexing
19:07 - Chapter 10:- For loops and IF conditions
21:11 - Chapter 11:- PEP, PEP 8, Python enhancement proposal
24:05 - Chapter 12:- ELSE and ELSE IF
24:44 - Chapter 13:- Array vs Python
27:23 - Chapter 14:- Reading text files in Python
29:08 - Chapter 15:- Casting and Loss of Data
31:07 - Chapter 16:- Referencing external libraries
33:01 - Chapter 17:- Applying linear regression using sklearn
44:36 - Chapter 18:- Creating classes and objects.

See our other Step by Step video series below :-

Python Tutorial for Beginners
----------------------------------------------------------
Chapter 1:- Installing Python framework and Pycharm IDE.
Chapter 2:- Creating and Running your first Python project.
Chapter 3:- Python is case-sensitive
Chapter 4:- Variables, data types, inferrence & type()
Chapter 5:- Python is a dynamic language
Chapter 6:- Comments in python
Chapter 7:- Creating function, whitespaces & indentation
Chapter 8:- Importance of new line
Chapter 9:- List in python, Index, Range & Negative Indexing
Chapter 10:- For loops and IF conditions
Chapter 11:- PEP, PEP 8, Python enhancement proposal
Chapter 12:- ELSE and ELSE IF
Chapter 13:- Array vs Python
Chapter 14:- Reading text files in Python
Chapter 15:- Casting and Loss of Data.
Chapter 16:- Referencing external libararies
Chapter 17:- Applying linear regression using sklearn
Chapter 18:- Creatiing classes and objects.
Chapter 19:- What is Machine learning?
Chapter 20:- Algoritham and Training data.
Chapter 21:- Vectors.
Chapter 22:- Models in Machine Learning.
Chapter 23:- Features and Labels.
Chapter 24:- Bag of words.
Chapter 25:- Implementing BOW using SKLearn.
Chapter 26:- The fit Method.
Chapter 27:- StopWords.
Chapter 28:- The transform Method.
Chapter 29:- Zip and Unzip.
Chapter 30:- Project Article Auto tagging.
Chapter 31 :- Understanding Article auto tagging in more detail.
Chapter 32 :- Planning the code of the project.
Chapter 33 :- Looping through the files of the directory.
Chapter 34 :- Reading the file in the document collection
Chapter 35 :- Understanding Vectorizer , Document and count working.
Chapter 36 :- Calling Fit and Transform to extract Vocab and Count.
Chapter 37 :- Understanding the count and Vocab collection data.
Chapter 38 :- Count and Vocab structure complexity
Chapter 39 :- Converting CSR matrix to COO matrix
Chapter 40 :- Creating the BOW text file.
Chapter 41 :- Restricting Stop words.
Chapter 42 :- Array vs List revisited
Chapter 43 :- Referencing Numpy and Pandas
Chapter 44 :- Creating a numpy array
Chapter 45 :- Numpy Array vs Normal Python array
Chapter 46 :- Why do we need Pandas ?
Chapter 47 :- Revising Arrays vs Numpy Array vs Pandas
Chapter 47 :- Corupus / Documents, Document and Terms.
Chapter 48 :- Understanding TF
Chapter 49 :- Understanding IDF
Chapter 50 :- TF IDF.
Chapter 51 :- Performing calculations of TF IDF.
Chapter 52 :- Implementing TF IDF using SkLearn
Chapter 53 :- IDF calculation in SkLearn.

#LearnPython #PythonTutorialStepbyStep #PythonTutorialforBeginners #PythonTraining #PythonProgram

[triloksingh]

Dear Sir
I am Asst Prof in CSE Dept at Invertis university Bareilly UP. I have no words to thnaks for effort and you made computer science subjects really easy and very interesting . I enjoyed your lecture I am following you since 7 or 8 year . I have watched all your video's posted on youtube . I also learn how to teach and made subjects easy for students . I am writing this comments about you is like showing candle light to sun.i also like the way you explain and your voice is very clear and you choose your words very carefully. thanks

[mohammedgadi]

what a bullet fast python tutorial sir. Just loved it.

[priyabist]

I liked your 1 hour python tutorial.Can you explain me basics of machine learning, what are models, labels, features, bag of words, it will help me to understand the fundamentals of machine learning.

[inuniverse]

At 19:02, it should print 'test' only if -3 is 'raju'. But result is different. Could you please explain Sir.

[nabilkhanpathan]

First to view, first to like, first to comment 😁

[titumukherjee]

Hi sir, I have a question that why do we need to download pycharm ide, can jupyter which comes in- built, not used for same purpose?

[thecodingjunckyard]

Hello SHiv Sir ! Great article and i am your great fan following you since C++ and dot net 1.1 days. Well can you upload a small vedio for image tagging and image reading in AI using Amazon, i mean step by step setup and then image tagging just like an FB does. I appreciate your response on this

[NavinKotianT]

Pls post answer to question asked. Thx

[mounikaammu]

Sir.i find difficulties in finding continuous videos for the course u teach...can u help me on it..like dbms, angular courses

[aaliyah]

Please made Js course and add CC caption like this please

[sharmilaramalingam]

Hi Guys..In the 2nd part of QA, What is the answer of 1 st 3rd question?(FYI 21.02)

[MATM]

Sir, Should i python to the path in the installation process

[himalayan]

What a video, takes you straight the point. Have been a subscriber with www.questpond.com for past 10 years and never regretted.