The Complete Python Pro Bootcamp for Data Science and AI

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The Complete Python Pro Bootcamp for Data Science and AI [TutsNode.com] - The Complete Python Pro Bootcamp for Data Science and AI 02 - Week 1
  • 007 Workshop 1 task - Solved.mp4 (285.9 MB)
  • 001 Programming-Languages-and-Computation.pdf (753.7 KB)
  • 003 Python-Commands.pdf (668.7 KB)
  • 006 Workshop1Tasks.ipynb (26.4 KB)
  • 004 Python-Data-Structures-Lists.pdf (599.8 KB)
  • 006 Workshop 1 Tasks - Unsolved.mp4 (135.0 MB)
  • 004 Python Data Structures - Lists.mp4 (95.5 MB)
  • 003 Python Commands.mp4 (85.7 MB)
  • 002 Programming in Python.mp4 (81.9 MB)
  • 005 Python Data Structures - Dictionary and Tuple.mp4 (79.5 MB)
  • 001 Programming Languages and Computation.mp4 (36.0 MB)
  • 002 Programming-in-Python.pdf (662.8 KB)
  • 005 Python-Data-Structures-Dictionary-and-Tuples.pdf (614.5 KB)
03 - Week 2
  • 006 Workshop2Tasks-Solved.ipynb (44.3 KB)
  • 004 List and Dict Comprehensions.mp4 (267.4 MB)
  • 002 Python-Classes.pdf (624.3 KB)
  • 004 L6-Comprehensions-List-and-Dict.ipynb (17.5 KB)
  • 003 Lets-Play-With-Cats.ipynb (3.5 KB)
  • 005 Workshop 2 Tasks - Unsolved.mp4 (197.6 MB)
  • 006 Workshop 2 Tasks - Solved.mp4 (185.8 MB)
  • 005 Workshop2Tasks.ipynb (30.9 KB)
  • 002 Classes and Methods.mp4 (107.6 MB)
  • 001 Functions and Scope.mp4 (82.8 MB)
  • 003 Playing with cats.mp4 (40.6 MB)
  • 001 Python-Functions-Methods.pdf (662.8 KB)
04 - Week 3
  • 003 JSON-Reader-Writer.ipynb (6.7 KB)
  • 001 long-text.txt (1.3 KB)
  • 002 sample-data.csv (0.2 KB)
  • 004 ex1-data.txt (1.3 KB)
  • 003 duck-manifest.json (0.2 KB)
  • 001 junk.txt (0.1 KB)
  • 002 another-data.csv (0.0 KB)
  • 001 my-file.txt (0.0 KB)
  • 005 Workshop 3 Tasks - Solved.mp4 (261.0 MB)
  • 001 File-IO.ipynb (31.1 KB)
  • 005 ex1-data.txt (1.3 KB)
  • 004 duck-collection.json (0.6 KB)
  • 005 duck-collection.json (0.6 KB)
  • 001 File IO in Python.mp4 (246.4 MB)
  • 004 Workshop 3 Tasks - Unsolved.mp4 (226.7 MB)
  • 002 CSV-Reader-Writer.ipynb (13.4 KB)
  • 004 Workshop3Tasks.ipynb (41.2 KB)
  • 002 Handling CSV files in Python.mp4 (110.5 MB)
  • 003 JSON Reader and Writer in Python.mp4 (62.5 MB)
  • 005 Workshop3Tasks-Solved.ipynb (6.3 MB)
  • 005 wind-data.csv (3.8 MB)
  • 004 wind-data.csv (3.8 MB)
01 - Introduction and Installations
  • 002 SampleNotebook.ipynb (1.2 KB)
  • 002 Python and Jupyter Notebook Installation.mp4 (46.5 MB)
  • 002 python-3.10.1-amd64.exe (26.9 MB)
  • 001 Introduction Talk.mp4 (10.3 MB)
  • 002 installation.pdf (5.6 MB)
06 - Real Application - Customer Data Preprocessing
  • 002 commute.json (999.6 KB)
  • 002 multivariate1.png (17.8 KB)
  • 002 univariate2.png (5.7 KB)
  • 002 processed.json (964.5 KB)
  • 001 Final-Assement.pdf (289.0 KB)
  • 002 remove-ccard.json (275.6 KB)
  • 002 univariate3.png (9.9 KB)
  • 002 Final-Assement.pdf (289.0 KB)
  • 002 univariate1.png (6.4 KB)
  • 002 retired.json (234.4 KB)
  • 002 multivariate3.png (95.7 KB)
  • 002 multivariate2.png (35.0 KB)
  • 002 Customer Data Preprocessing Solved.mp4 (141.4 MB)
  • 001 Customer Data Preprocessing - Unsolved.mp4 (120.3 MB)
  • 002 employed.json (730.1 KB)
  • 002 acw-user-data.csv (200.0 KB)
  • 001 acw-user-data.csv (200.0 KB)
  • 002 Assignment-Solved.ipynb (4.3 MB)
  • 002 FINAL-ASSIGNMENT-SOLVED.rar (1.2 MB)
05 - Week 4
  • 001 iris.csv (3.9 KB)
  • 002 iris.csv (3.9 KB)
  • 003 Workshop 4 Tasks - Unsolved.mp4 (212.2 MB)
  • 003 titanic.csv (63.6 KB)
  • 004 Workshop 4 Tasks - Solved.mp4 (209.3 MB)
  • 003 Workshop4Tasks.ipynb (43.0 KB)
  • 001 Pandas-Lecture.ipynb (26.1 KB)
  • 001 Pandas in Python Notebook.mp4 (136.7 MB)
  • 002 Seaborn.ipynb (202.1 KB)
  • 002 Seaborn visualisation in Python.mp4 (113.9 MB)
  • 004 Workshop4Tasks-Solved.ipynb (202.6 KB)
  • TutsNode.com.txt (0.1 KB)
    • .pad
    • 0 (0.1 KB)
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    • 3 (3.0 KB)
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    • 5 (11.5 KB)
    • 6 (17.3 KB)
    • 7 (2.2 KB)
    • 8 (107.8 KB)
    • 9 (9.2 KB)
    • 10 (61.9 KB)
    • 11 (44.2 KB)
    • 12 (8.6 KB)
    • 13 (109.4 KB)
    • 14 (123.4 KB)
    • 15 (229.6 KB)
    • 16 (532.4 KB)
    • 17 (318.0 KB)
    • 18 (173.7 KB)
    • 19 (132.9 KB)
    • 20 (529.9 KB)
    • 21 (491.6 KB)
    • 22 (551.5 KB)
    • 23 (431.7 KB)
    • 24 (27.6 KB)
    • 25 (129.4 KB)
    • 26 (54.6 KB)
    • 27 (84.3 KB)
    • 28 (399.6 KB)
    • 29 (150.2 KB)
    • 30 (217.2 KB)
    • 31 (217.2 KB)
  • [TGx]Downloaded from torrentgalaxy.to .txt (0.6 KB)

Description


Description

This module teaches students to program in Python and is scheduled to start their career in Artificial Intelligence and Data Science.

If you want to enter the domain of Data Science and are from a different discipline or career path then this module is for you to enroll in .

You should prepare for the practical workshops by watching the lecture videos, reading the written material including the assigned practical tasks, and prepare some of the initial practical tasks so you are ready for the days work.

The format of this module is a 4-week intensive module which is designed to teach you the necessary programming skills to excel throughout the remaining of your exciting program. I understand that you come from a variety of different backgrounds and encourage you to engage and communicate with us about your learning where possible; whether you are completely new to programming or whether you’ve dabbled in it before. Programming is a skill which takes time to master, and the more you practice these skills the better you will become.

The first two weeks contain many smaller topics which are fundamental to programming understanding, with later weeks utilizing these for more advanced applications.

All of the programming part will take place in Jupyter Notebook and relevant python version installation and usage will be shared in this course.

Week 1.

Environments
Variables
Data Primitives
Data Structures (Collections)
Control Flow
Scope Teaching

Week 2.

Functions
List/Dict Comprehensions
Libraries
Python Modules
Object Oriented Python
Teaching

Week 3.

Coursework Introduction
Numpy and N-Dimensional Matrices
File Input/output
Error-handling / Exceptions Teaching

Week 4.

Introduction to Pandas library
Visualization of Data with Python Coursework

Real Application.

Customer Data Pre-Processing

Who this course is for:

Beginner python developers curious about Data Science
Beginners
New to the Domain
Python developers and Machine Learning engineers
Everybody who wants to learn more about the joint field of AI and Data science
Students who wants to switch to Data Science

Requirements

No programming experience needed , you will be taught everything from scratch up to a professional level

Last Updated 2/2022



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The Complete Python Pro Bootcamp for Data Science and AI

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Download torrent
3.6 GB
seeders:38
leechers:15
The Complete Python Pro Bootcamp for Data Science and AI

Torrent hash: 9F0B8BAD0D3053B2C72813DBBB479FCAAAE6EE89