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Tema: Python Bootcamp For Data Science And Ai For Beginners - 2022

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    Predeterminado Python Bootcamp For Data Science And Ai For Beginners - 2022

    AJJYSOM - Python Bootcamp For Data Science And Ai For Beginners - 2022
    Python Bootcamp For Data Science And Ai For Beginners - 2022
    Last updated 2/2022
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 3.55 GB | Duration: 8h 21m
    Learn to use Python Like a Data Scientist. Including tutorials on Numpy, Pandas, Matplotlib , Seaborn and a lot more!!
    What you'll learn
    You will first learn how to Install Python and Jupyter on your desktop/laptop
    Programming Languages and Computation
    Programming in Python
    Python Commands
    Python Data Structures - Lists
    Python Data Structures - Dictionary and Tuple
    Functions and Scope
    Classes and Methods
    Python Comprehensions in Lists and Dictionaries
    List and Dict Comprehensions
    File IO in Python
    Handling CSV files in Python
    CSV Reading and Writing
    JSON Reader and Writer in Python
    Pandas in Python
    Pandas in Python Notebook
    Seaborn visualisation in Python
    Data pre processing using python
    Learn how to analyze, retrieve and clean data with Python - Data cleaning
    You will understand and learn the basics of For Loops and Advanced For Loops
    You will understand Why foundations Modify Lists and Dictionaries and Functions
    Data Cleaning and Preparation for Machine Learning
    Requirements
    No programming experience needed , you will be taught everything from scratch up to a professional level
    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 VariablesData PrimitivesData Structures (Collections) Control Flow Scope Teaching Week 2. FunctionsList/Dict ComprehensionsLibrariesPython ModulesObject Oriented PythonTeaching Week 3. Coursework IntroductionNumpy and N-Dimensional MatricesFile Input/outputError-handling / Exceptions Teaching Week 4. Introduction to Pandas libraryVisualization of Data with Python Coursework Real Application. Customer Data Pre-Processing
    Overview
    Section 1: Introduction and Installations
    Lecture 1 Python and Jupyter Notebook Installation
    Section 2: Week 1
    Lecture 2 Programming Languages and Computation
    Lecture 3 Programming in Python
    Lecture 4 Python Commands
    Lecture 5 Python Data Structures - Lists
    Lecture 6 Python Data Structures - Dictionary and Tuple
    Lecture 7 Workshop 1 Tasks - Unsolved
    Lecture 8 Workshop 1 task - Solved
    Section 3: Week 2
    Lecture 9 Functions and Scope
    Lecture 10 Classes and Methods
    Lecture 11 Playing with cats
    Lecture 12 List and Dict Comprehensions
    Lecture 13 Workshop 2 Tasks - Unsolved
    Lecture 14 Workshop 2 Tasks - Solved
    Section 4: Week 3
    Lecture 15 File IO in Python
    Lecture 16 Handling CSV files in Python
    Lecture 17 JSON Reader and Writer in Python
    Lecture 18 Workshop 3 Tasks - Unsolved
    Lecture 19 Workshop 3 Tasks - Solved
    Section 5: Week 4
    Lecture 20 Pandas in Python Notebook
    Lecture 21 Seaborn visualisation in Python
    Lecture 22 Workshop 4 Tasks - Unsolved
    Lecture 23 Workshop 4 Tasks - Solved
    Section 6: Real Application - Customer Data Preprocessing
    Lecture 24 Customer Data Preprocessing - Unsolved
    Lecture 25 Customer Data Preprocessing Solved
    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
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