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Python Programming

0 Ratings
  • Easy to Learn and Use
  • Versatile Applications
  • Large Library Ecosystem
  • Cross-Platform Compatibility
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Python Programming
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Overview

Python is a powerful and versatile programming language known for its simplicity and readability. It is widely used in areas such as web development, data analytics, artificial intelligence, machine learning, and automation. With a vast ecosystem of libraries and frameworks, Python enables developers to build scalable applications, automate tasks, and solve complex problems efficiently across various industries.

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Data Science Course Syllabus

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Python Environment Setup and Essentials

Preview
  • Introduction to Python Language
    00:00:00

    Introduction to Python Language

  • Features, the advantages of Python over other programming languages
    00:00:00
  • Python installation – Windows, Mac & Linux distribution for Anaconda Python
    00:00:00
  • Deploying Python IDE
    00:00:00
  • Basic Python commands, data types, variables, keywords and more
    00:00:00
  • Built-in data types in Python
    00:00:00

    Built-in data types in Python 

  • Learn classes, modules, Str(String), Ellipsis Object, Null Object, Ellipsis, Debug
    00:00:00
  • Basic operators, comparison, arithmetic, slicing and slice operator, logical, bitwise
    00:00:00
  • Loop and control statements while, for, if, break, else, continue.
    00:00:00
  • How to write OOP concepts program in Python
    00:00:00

    How to write OOP concepts program in Python

  • Connecting to a database
    00:00:00
  • Classes and objects in Python
    00:00:00
  • OOPs paradigm, important concepts in OOP like polymorphism, inheritance, encapsulation
    00:00:00
  • Python functions, return types and parameters
    00:00:00
  • Lambda expressions
    00:00:00
  • Understanding the Database, need of database
    00:00:00

    Understanding the Database, need of database

  • Installing MySQL on windows
    00:00:00
  • Understanding Database connection using Python.
    00:00:00
  • Introduction to arrays and matrices
    00:00:00

    Introduction to arrays and matrices 

  • Broadcasting of array math, indexing of array
    00:00:00
  • Standard deviation, conditional probability, correlation and covariance.
    00:00:00
  • Introduction to SciPy
    00:00:00

    Introduction to SciPy 

  • Functions building on top of NumPy, cluster, linalg, signal, optimize, integrate, subpackages, SciPy with Bayes Theorem.
    00:00:00
  • How to plot graph and chart with Python
    00:00:00

    How to plot graph and chart with Python 

  • Various aspects of line, scatter, bar, histogram, 3D, the API of MatPlotLib, subplots.
    00:00:00
  • Introduction to Python dataframes
    00:00:00

    Introduction to Python dataframes

  • Importing data from JSON, CSV, Excel, SQL database, NumPy array to dataframe
    00:00:00
  • Various data operations like selecting, filtering, sorting, viewing, joining, combining
    00:00:00
  • Introduction to Exception Handling
    00:00:00

    Introduction to Exception Handling

  • Scenarios in Exception Handling with its execution
    00:00:00
  • Arithmetic exception
    00:00:00
  • RAISE of Exception
    00:00:00
  • What is Random List, running a Random list on Jupyter Notebook
    00:00:00
  • Value Error in Exception Handling.
    00:00:00
  • Introduction to Thread, need of threads
    00:00:00

    Introduction to Thread, need of threads

  • What are thread functions
    00:00:00
  • Performing various operations on thread like joining a thread, starting a thread, enumeration in a thread
    00:00:00
  • Creating a Multithread, finishing the multithreads.
    00:00:00
  • Understanding Race Condition, lock and Synchronization.
    00:00:00
  • Intro to modules in Python, need of modules
    00:00:00

    Intro to modules in Python, need of modules

  • How to import modules in python
    00:00:00
  • Locating a module, namespace and scoping
    00:00:00
  • Arithmetic operations on Modules using a function
    00:00:00
  • Intro to Search path, Global and local functions, filter functions
    00:00:00
  • Python Packages, import in packages, various ways of accessing the packages
    00:00:00
  • Decorators, Pointer assignments, and Xldr.
    00:00:00
  • Introduction to web scraping in Python
    00:00:00

    Introduction to web scraping in Python

  • Installing of beautifulsoup
    00:00:00
  • Installing Python parser lxml
    00:00:00
  • Various web scraping libraries, beautifulsoup, Scrapy Python packages
    00:00:00
  • Creating soup object with input HTML
    00:00:00
  • Searching of tree, full or partial parsing, output print
    00:00:00

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