Course Content
Why Should You enroll?
0/3
What is Python ka Chilla 2024?
10:16
Python seekh len Python ka Chilla is back #pythonkachilla
06:24
Enroll in LMS of Python ka Chilla 2024-25
05:52
Resources for the Course
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Books for the course
00:00
GitHub Repository for the course
00:00
Day-1
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Course content in this course
05:50
Registration is still open
00:20
Know your instructor
04:52
Class Timings
00:00
Important Rules for the course
06:05
Turn on Video during meetings
01:36
What is Python?
03:23
LMS (Learning Management System) for the course
09:26
Zoom Meeting Questions and Answers
27:26
Day-2
0/5
Installing different software to use Python for Data Science
12:43
VScode profile, extensions and themes for Python
06:31
Files and Folders management in VScode
09:36
GitBash and miniconda | Integration | Solutions
07:35
miniConda | Environments and Installations | A complete Guide
22:06
Day-3
0/9
What we have learned so far and updates about the course
06:34
Python for Data Science and popularity of python
14:22
Important Logins to make for Python for Data Science
13:09
Access GitHub student or teacher developer pack
00:55
Naming conventions and rules for Python for Data Scientists
16:20
Ads in videos and Website
00:59
Jupyter notebooks | .ipynb vs. .py files
13:27
Jupyter Notebooks or .ipynb files for Data Scientists
07:31
MarkDown Language in 72 Minutes
01:11:23
Day-4
0/4
Variables in Python
19:38
Types of Variables in Python
23:47
Type casting in Python (1/2)
23:41
Type Casting in Python (2/2)
09:03
Day-5
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Commenting in Python is important
04:58
git bash in vscode and conda in gitbash
03:44
Screen-casting mode in VSCode to show keyboard
02:29
Debugging is an art you need to learn
06:45
Day-6
0/5
Google Your Errors and Answers to most common errors
10:00
Alternatives to GitHub copilots for VScode | Blackbox and codeium
03:05
Activating GitHub copilot while in the university
01:17
Do not share any link to anyone Plzzzzzzz
00:58
Zoom Meeting (Recording) for Python ka chilla 2024 on 06 10 2024
01:11:42
Day-7
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Windows screenshots and Screen Recording tool free
03:49
When to use which variable or data structure in python
10:49
Data Structures in Python | Complete Guide
35:50
Day-8
0/5
AI Pioneers Win Nobel Prize in Physics 2024: Revolutionizing Machine Learning and Neural Network
13:08
Sequences in python
21:57
Indexing in Python
25:10
Slicing in Python
06:02
Mutable elements in Python
06:04
Day-9
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Range Function in python
02:25
TWO Nobel Prizes to AI
19:06
gitbash as default terminal in vscode
01:44
Day-10
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Maslay hal kar deay gaye hyn
03:54
Control Flow Statements in Python
20:06
Audience desi examples of Control Flow Statements
03:08
If else and elif control flow statements in python
17:35
Conditional and relational operators | nested if statements
21:56
Assignment alert To be submitted before next class
01:03
Questions and answer session | Zoom Meeting
05:07
Day-11
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for and while loops
15:15
break, continue and pass statements
08:45
Infinite loop in python | Beware of infinite loops
10:00
Try, Except and finally statements
05:16
Summary of control flow statements and assignment
02:34
Day-12
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Convert notebook to pdf | step by step guide with error handling (uncut version)
23:29
Functions in Python
26:22
Day-13
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Lambda Functions in python
22:32
user input in python
24:31
gitbash and conda in vscode
01:43
Day-14
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Future of Data Science | A podcast with Dr. Zeeshan ul Hassan Usmani
57:50
Day-15
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Top nine methods of using print( ) functions in python
41:55
Tip to improve communication
01:24
Generators in Python
13:34
Introductions to libraries in python
22:11
Social media presence is important for data Scientist
06:12
Day-16 (No lectures- Take Rest/Revise and enjoy the day)
Day-17
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PyPI , pip and famous libraries in python
04:25
Step-by-Step Installation of libraries in conda environments
16:33
Day-18
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Top five libraries of Python for Data Analysts
08:17
Seventeen important python libraries, I bet you did not know before
11:12
Day-19
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AI News of October 2024
07:25
Day-20
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Newsletters to access latest AI News
05:26
Using python libraries as professionals
16:34
Importing, finding, writing and Saving Data in python
19:55
Nine-step guide for Data Analysts and Data Scientists
20:17
Four dimensions of Data Handling and EDA for Data Scientists and Analysts
15:43
Day-21 (Automatics EDA-1)
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pandas profiling or y-dataprofiling for automatic EDA in python
20:50
python library for automatic exploratory data analysis for any data
14:03
Make stunning plots for EDA | like tableau for free in python
11:29
Day-22 (Automatic EDA-2)
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Sweetviz library for EDA with complete debugging uncut
36:01
Skimpy library, dealing with errors and installations (Practice)
22:43
Skimpy error resolved and working fine
04:29
lida for automatic EDA using LLM
09:54
Day-23 (Automatic EDA-3)
0/1
Low code EDA library for python | dataprep | A-Z master guide
09:42
Day-24 (AI-News and Automatic EDA)
0/5
Claude anthropic new model can use your computer
03:53
Google news Categories to search for latest AI and tech news
03:22
Lida python library for Automatic EDA using LLMs
20:23
Free AI Models available for LLM tasks, we will see in future
04:27
Account to make which are important for all
01:22
Day-25 (Pandas-1)
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Pandas Dataframes vs. datasets
14:16
Reading Data for python using pandas library from clipboard
06:24
Reading data from Excel using pandas library in python
06:41
Reading csv and tsv files in python using pandas library
12:08
Making dummy datasets in python using pandas library from dictionary
03:44
Writing data into files using pandas library in python
05:16
Assignment alert
02:05
Advance Data Import in Pandas using Excel workbook with specific paths
06:24
Excel vs. csv files in pandas data frame for python
04:59
Using absolute paths in windows for data import in pandas or python
03:19
Do not use spaces in reading files in pandas but what if?
02:06
Web scrapping using pandas library in python for table import
06:39
Read online .csv files using pandas python library
05:38
Day-26 (Pandas-2)
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Read tabular data in pandas
03:41
Read data from json file in pandas python
01:17
Elements of Pandas dataframes in python | series | df
04:19
Subset or filter the data based on rows or columns
15:38
Important methods for selecting subset of the dataframes in pandas python
03:29
Selecting known data or unknown data from dataframes in pandas python
02:24
Day-27 (Pandas-3)
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Most important tasks
01:53
Absolute vs. relative paths to files and directories in data analysis
05:30
Day-28
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loc and iloc functions for data selection in pandas pyhton library
15:48
Day-29
0/2
Fifty plus advance pandas commands for data analysis in python
01:17:07
Next Tasks for all to practice Pandas
03:00
Day-30 (Take a break and revise your previous lessons)
Day-31: Statistics for Data Science-(Part-1)
0/5
Statistics for Data Science Crash Course
01:05:18
More lectures on statistics will be coming soon
00:46
LMS will be available for you for longer time
02:12
Data Visualization is coming soon In Sha Allah
02:16
Reources to read and learn Statistics
00:00
Day-32: Statistics for Data Science-(Part-2)
0/1
Statistics for Data Science Complete Crash course
14:15:35
Day-33: Statistics for Data Science-(Part-3)
0/1
Practice the previous Crash Course on Statistics
00:00
Day-34: Statistics for Data Science- (Part-4)
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Practice Crash Course on Statistics for Data Science
00:00
Zoom Meeting Recording (Day34 Python ka chilla 2024)
12:15
Day-35: Statistics for Data Science- (Part-5)
0/3
Practice Crash course on Statistics
00:00
Codes are available here for statistics course
01:51
GitHub will be coming next
00:31
Day-36: Mathematics for Data Science and Machine Learning
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Mathematics for Data Science and Machine Learning
15:15:51
Day-37, 38, 39, 40: NumPy for Data Science
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Meditate and relax yourself before moving forward
03:41
Numpy for Data Science
34:58
50 plus commands for NumPy for Data Science and Machine Learning
57:35
Assignment and Next Tasks
01:47
Mathematics for Data Science and Machine Learning
00:00
Quizes
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Python for Data Science Quiz
00:00
Mathematics for Data Science Quiz
00:00
Day-41: Data Visualization (Part-1)
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Attempt these Quizzes
02:28
Introduction to Data Visualization
10:41
Data Visualization in python | Important Terminologies
01:04:41
Stacking vs. Concatenation in NumPy
04:27
Tasks before next lecture
00:56
Day-42: Data Visualization (Part-2)
0/2
Are you completing your assignments?
00:46
Data Visualization Theory and parts of plots
01:00:21
Day-43: Data Visualization (Part-3)
0/2
Data Visualization using matplotlib and seaborn in python
01:07:33
Next Task
00:33
Day-44: Data Visualization (Part-4)
0/1
Customization for plot parts in Data Visualization
19:28
Day-45: Data Visualization (Part-5)- Plotly Master Class-I
0/3
Plotly Master Class for Data Visualziation in Python
52:40
3D Interactive plots in Plotly
08:34
Amazing Plots I bet you have never seen | Plotly Python
29:47
Day-46: Data Visualization (Part-5)- Plotly Master Class-II
0/3
Marginal Plots in plotly
07:15
Animated Plots and saving as video files using plotly
17:10
Multiple advance plots using plotly
11:02
Day-47: Data Analysis and EDA complete project on real world data
0/2
Data Analysis Complete Project using World Bank Datasets
02:01:21
Kaggle Guide to become a Grand Master
38:44
Day-48: Data Visualization (Part-6)- GeoMaps using Plolty
0/3
Draw Geospatial Data Using Plotly
34:27
Task for Students to master Bokeh and Altair
04:40
How to upload the task on kaggle
00:34
Day-49: Data Visualization (Part-7)- Bokeh Library
0/1
Basics of Bokeh Library for Data Visualization
24:44
Day-50: Magic Commands Used in Python
0/1
Magic Commands %% used in Python
26:52
Day-51: Data Gathering and Data Scrapping
0/4
Wordbank Data Gathering Library
20:16
FAOSTAT data download using python library
17:48
EUROSTAT data download using python
19:13
Assignment Alert
00:59
Day-52: Machine Learning is Next
0/1
Machine Learning is Next
00:41
Complete Projects A-Z
0/3
Basic EDA on Titanic Dataset complete project
01:07:31
Coding Night for Data Science and Data Analytics Project
03:21:15
Save plotly animation as video for reels and YouTube videos
18:20
Python Ka Chilla 2024
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    Safi Ullah 5 days ago
    I want to learn AI,, becasue I have felt myself too far in competition.. each day, when i have some repititive task, people do it using AI, or using python, they create custom script for themselves, and they increase their productivity...I am learning AI to embrace ai, to increase my productivity, workflow...
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