Master Python in 14 Days- Numpy, Pandas, Seaborn, RegEx, OOP

Master Python in 14 Days: Numpy, Pandas, Seaborn, RegEx, OOP, available at $19.99, has an average rating of 4.65, with 57 lectures, 7 quizzes, based on 30 reviews, and has 5913 subscribers.

You will learn about Python basics Numpy Pandas Matplotlib Different types of arrays Loops, Conditions and Functions How to join, split and re-shape arrays This course is ideal for individuals who are Beginner Python programmers or Machine learning enthusiasts or Experienced professionals looking for conceptual clarity or Students It is particularly useful for Beginner Python programmers or Machine learning enthusiasts or Experienced professionals looking for conceptual clarity or Students.

Enroll now: Master Python in 14 Days: Numpy, Pandas, Seaborn, RegEx, OOP

Summary

Title: Master Python in 14 Days: Numpy, Pandas, Seaborn, RegEx, OOP

Price: $19.99

Average Rating: 4.65

Number of Lectures: 57

Number of Quizzes: 7

Number of Published Lectures: 57

Number of Published Quizzes: 7

Number of Curriculum Items: 77

Number of Published Curriculum Objects: 77

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will Learn

Python basics

Numpy

Pandas

Matplotlib

Different types of arrays

Loops, Conditions and Functions

How to join, split and re-shape arrays

Who Should Attend

Beginner Python programmers

Machine learning enthusiasts

Experienced professionals looking for conceptual clarity

Students

Target Audiences

Beginner Python programmers

Machine learning enthusiasts

Experienced professionals looking for conceptual clarity

Students

Python is a high level dynamic programming language founded in 1991. The inspiration for the name ‘Python’ was from the comedy television show Monty Python’s Flying Circus. Today, Python is a very popular programming language which is extensively used in many organizations around the world and is one of the top programming languages in the software industry today.

Notably, Python has emerged as the No. 1 Programming language of choice across domains like artificial intelligence, data science, mobile applications, web development and machine learning.

Hence, learning python has become a necessity for those aspiring for a career in software industry and for those who are already in the IT industry. Even if you are new to programming, this course is a good starting point.

A key aspect of the course is the use of google cloud based development environment – colab. You may wonder what is the big deal. Well, for starters, you don’t need to download anything to get started. You will use a development environment that can be accessed on your browser using your email id. As more and more companies embrace cloud in a big way, it has become imperative for programmers to gain knowledge and expertise to code in cloud.

The course covers the following concepts:

· Variables

· Operators

· Conditional statements

· For and While Loops

· Functions

· Four types of Arrays – List, Tuple, Set and Dictionary

· NumPy

· In NumPy, we will cover, how to shape arrays, iterate arrays, joining arrays, splitting arrays, searching arrays and sorting arrays.

· Pandas

· We will also explain data analysis using pandas

· Data visualization using matplotlib, seaborn, altair, dash, bokeh

. Regular Expressions (RegEx)

. Different functions like recursive, lambda functions in addition to regular functions

. OOP (Object Oriented Programming) – Basic & Advanced OOP concepts

. User defined or Extended Data Structure

But what are the features that make Python so easy to use?

One of the biggest advantages Python has over other programming languages is its readability and large standard library that makes coding easier. It is portable and interactive across various operating systems and has user friendly data structures that can be easily implemented. Moreover, Python also supports object oriented programming and has applications that varies across several different fields.

Applications of Python

Python’s popularity has made it a very useful tool to develop many applications. The wide selection of libraries and frameworks available makes it one very useful in the field of data analysis and machine learning. These libraries can be used for various purposes such as natural language process, speech synthesis, complex data analysis and so on. Python is also used in prototyping and scripting which helps in the development of embedded applications. Thus, the popularity of python is greatly beneficial for applications that require easier code maintenance and efficient versatility.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Day 1: Getting Started, Variables and Operators

Lecture 1: Day 1: Introduction to Colab: Google Cloud Development Environment

Lecture 2: Day 1: Getting Started with Python

Lecture 3: Day 1: Variables

Lecture 4: Day 1: Operators

Chapter 3: Day 2: Conditions, Loops and Functions

Lecture 1: Day 2: Conditions

Lecture 2: Day 2: Loops

Lecture 3: Day 2: Functions

Chapter 4: Day 3: Arrays | Built in Data Structures

Lecture 1: Day 3: Arrays

Lecture 2: Day 3: List

Lecture 3: Day 3: Tuple

Lecture 4: Day 3: Set

Lecture 5: Day 3: Dictionary

Chapter 5: Day 4: Strengthen Your Understanding 1 | Five Projects

Chapter 6: Day 5: NumPy

Lecture 1: Day 5: Getting Started with NumPy

Lecture 2: Day 5: Shape in Arrays

Lecture 3: Day 5: NumPy: Iterating Arrays

Lecture 4: Day 5: NumPy: Joining Arrays

Lecture 5: Day 5: NumPy: Splitting Arrays

Lecture 6: Day 5: NumPy: Searching and Sorting Arrays

Chapter 7: Day 6: Pandas

Lecture 1: Getting Started with Pandas

Lecture 2: Data analysis using Pandas

Chapter 8: Day 7: Data Visualization

Lecture 1: Data Visualization using Matplotlib

Lecture 2: Data Visualization Using Seaborn, Altair

Lecture 3: Additional Visualization with EDA Libraries – Klib, Sweetviz

Lecture 4: Interactive Scatter Plot Using Bokeh

Lecture 5: Interactive Violin Chart Using Dash

Lecture 6: Heatmap + Cluster in a single visual

Chapter 9: Day 8: Strengthen your understanding : Numpy, Pandas, Data Visualization

Chapter 10: Day 9: Regular Expressions

Lecture 1: Regular Expressions

Chapter 11: Day 10: Different Types of Functions

Lecture 1: Eight types of functions

Lecture 2: Lambda Function

Lecture 3: Recursive Function

Lecture 4: Higher Order Function

Lecture 5: Nested Functions

Lecture 6: Generator or Lazy Functions

Chapter 12: Day 11: Object Oriented Programming (OOP)

Lecture 1: Evolution of Programming

Lecture 2: Objects & Classes

Lecture 3: Attributes and Methods

Lecture 4: Inheritance

Lecture 5: Encapsulation

Lecture 6: Polymorphism

Chapter 13: Day 12: Advanced OOP Concepts

Lecture 1: Meta Classes

Lecture 2: Descriptors

Lecture 3: Mixins

Lecture 4: Composition over Inheritance Principle

Chapter 14: Day 13: User Defined/Extended Data Structures

Lecture 1: Stack

Lecture 2: Queue

Lecture 3: Tree

Lecture 4: Linked List

Lecture 5: Graph

Lecture 6: Hash Map

Chapter 15: Day 14: Concurrency and Parallelism

Lecture 1: Threading

Lecture 2: Asyncio

Lecture 3: Multi Processing

Chapter 16: Day 14: Error Handling

Lecture 1: Exception Handling

Lecture 2: Logging

Lecture 3: Python Debugger (pdb)

Chapter 17: Bonus Lecture

Lecture 1: Bonus Lecture

Instructors

SeaportAi .
Artificial Intelligence and Business Transformation Experts

Rating Distribution

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2 stars: 0 votes

3 stars: 2 votes

4 stars: 16 votes

5 stars: 12 votes

Frequently Asked Questions

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