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Overview

Approx 38 Hours To Complete Python Programming in English Language

On completion of all the modules in this course, you will be able to use Anaconda, Jupyter Notebooks, Python data structures, control flows, loops, functions, NumPy Arrays, Pandas DataFrames, and Data Visualization in Python Programming. You will become proficient in Python Programming Online.

Requirements

    Basic Knowledge of Programmings like C , C++, and basic knowledge of python.

FAQ

    Q. Who this course is for?

    A. Anyone who is interested in learning Python.

    Q. Is this course easy to learn?

    A. Yes, you can learn easily and clear all the doubts.

Syllabus

    Module1: Introduction and Environment Setup

    Topics:

    Anaconda Installation

    Creating and using Jupyter Notebook

    Advantages of Jupyter Notebooks

    Module2: Data Structures

    Topics:

    Lists

    Tuples

    Dictionaries

    Sets

    Module3: Control Flow and Loops:

    Objectives:

    If .. Else

    If .. elif ..else

    Loops

    Comprehensions

    Module4: Functions

    Topics:

    Functions

    Lambda Expressions

    Map

    Reduce

    Filter

    Module5: Python for Data Science - NumPy

    Topics:

    1. NumPy Arrays

    2. Functions to describe NumPy Arrays

    3. Slicing and Indexing in NumPy

    4. Subset of Arrays

    5. Iterating through NumPy Arrays

    6. NumPy Operations

    Module6: Python for Data Science â€" Pandas

    Topics:

    1. Series

    2. DataFrame

    3. Slicing and Indexing

    4. Merge DataFrames

    5. Append DataFrames

    6. Grouping

    7. Pivot Tables

    8. Analyse DataFrames

    Module7: I/O operations

    Topics:

    1. Reading and Writing Data from flat files

    2. Reading and Writing Data from sql tables

    Module 8: Data Visualization in Python

    Topics:

    1. What is Data Visualization?

    2. Why we need Data Visualization?

    3. Data Visualization using Matplotlib

    4. Types of plots

    5. Working with plots

What you will learn

    Module1: Introduction and Environment Setup

    Topics:

    Anaconda Installation

    Creating and using Jupyter Notebook

    Advantages of Jupyter Notebooks

    Module2: Data Structures

    Topics:

    Lists

    Tuples

    Dictionaries

    Sets

    Module3: Control Flow and Loops:

    Objectives:

    If .. Else

    If .. elif ..else

    Loops

    Comprehensions

    Module4: Functions

    Topics:

    Functions

    Lambda Expressions

    Map

    Reduce

    Filter

    Module5: Python for Data Science - NumPy

    Topics:

    1. NumPy Arrays

    2. Functions to describe NumPy Arrays

    3. Slicing and Indexing in NumPy

    4. Subset of Arrays

    5. Iterating through NumPy Arrays

    6. NumPy Operations

    Module6: Python for Data Science â€" Pandas

    Topics:

    1. Series

    2. DataFrame

    3. Slicing and Indexing

    4. Merge DataFrames

    5. Append DataFrames

    6. Grouping

    7. Pivot Tables

    8. Analyse DataFrames

    Module7: I/O operations

    Topics:

    1. Reading and Writing Data from flat files

    2. Reading and Writing Data from sql tables

    Module 8: Data Visualization in Python

    Topics:

    1. What is Data Visualization?

    2. Why we need Data Visualization?

    3. Data Visualization using Matplotlib

    4. Types of plots

    5. Working with plots

About the instructor

Raj Mesons
  • 9 Instructor Rating
  • 2 Reviews
  • 0 Students
  • 1 Courses
  • Raj Mesons

    Technical Specialist of MESONS

    Qualification : BTech

    Technical Specialist,

    Skills :Software QA,Engineering,IT And Tech,Data Science,Web Development

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    Course Features

  • Lectures 38
  • Quizzes 0
  • Duration 38 hours
  • Skill level ForAll
  • Language English

Skills You Will Acquire

  • python
  • Pandas
  • Numpy
  • LearnPython