Python A to Z Bootcamp (2021) Basic-DataScience-API(50 Hrs)

Python A to Z Bootcamp (2021) Basic-DataScience-API(50 Hrs), available at $44.99, has an average rating of 3.35, with 464 lectures, based on 15 reviews, and has 120 subscribers.

You will learn about Python basic to advanced in One course Create your first python project Create your own data science project Create your project using Django This course is ideal for individuals who are Beginners who are willing to learn to Code or program or People willing to learn programming from scratch or Get all python related information in a single course It is particularly useful for Beginners who are willing to learn to Code or program or People willing to learn programming from scratch or Get all python related information in a single course.

Enroll now: Python A to Z Bootcamp (2021) Basic-DataScience-API(50 Hrs)

Summary

Title: Python A to Z Bootcamp (2021) Basic-DataScience-API(50 Hrs)

Price: $44.99

Average Rating: 3.35

Number of Lectures: 464

Number of Published Lectures: 463

Number of Curriculum Items: 464

Number of Published Curriculum Objects: 463

Original Price: $94.99

Quality Status: approved

Status: Live

What You Will Learn

Python basic to advanced in One course
Create your first python project
Create your own data science project
Create your project using Django

Who Should Attend

Beginners who are willing to learn to Code or program
People willing to learn programming from scratch
Get all python related information in a single course

Target Audiences

Beginners who are willing to learn to Code or program
People willing to learn programming from scratch
Get all python related information in a single course

Learn python basics by practicing Basic syntax, Regular Expression, Data structure & Algorithmand API

This course is aimed at complete beginners who have never programmed before, as well as existing programmers who pursue to increase their career options by learning Python.

Python is one of the most popular programming languages in the world – Huge companies like Google, amazon use it in mission critical applications like Google Search.

By the end of the course you’ll be able to code with confidence using Python programming. This will help you understanding the usage of python in different circumstance.

Become a Junior Python Programmer and land a job in silicon valley.

Get access to all the codes used in the course.

This course will contain all 80+ videos explaining necessary things a beginner needs to know in a programming language.

This course will get continuously updated for beginners to get learn more. I promise to get at least 1 video section to be added per quarter for the next 2 years.

Objective of the Python basic content:

Giving confidence that any student they can be a programmer.
Detailed Installation process
Covers syntax in Python.
Decision making and loops
Python basics like Data types, functions, Modules.
Excel Operation
Python file handling.
Regular Expression.
Programming with OOPS Concept.

Tools required for a Junior python developer job.

This course will teach you Python in a practical manner, with every lecture comes a full coding screen cast and a corresponding code notebook! Learn in whatever manner is best for you!

Help you in enabling processing the data from different source.

File handling from different sources.

The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming.

You will learn a lot of theory: how to sort data and how it helps for searching. How to break a large problem into pieces and solve them recursively and it makes sense to proceed greedily.

Objective of the Python data structure content:

Recursion.
Algorithm run time analysis
Arrays
Stack
Linked list
Data Structure
Binary Tree
Binary Search Tree
AVL Tree
Heap tree
Queue
Sorting
Hash Table
Graph Theory
Magic Framework
Computer Programming
Dynamic Programming

Regular expression (Regex):

Fetch the textual information from logs.
Perform the changes in the existing textual information for re-using.

API Python:

This section help you understand the working on API and how to implement the same using Python.
Here we will learn how to get and post the request using API and implement the same.
Will create a simple currency conversion calculator.
We will also cover API for website which we need to sign in. We will be using the API keys and ID to login and fetch the details.
We will explain how to structure and export the data in CSV using Pandas.

Scraping:

Fetch the dat from the URL
Get the information from Robot protected the website.
Fetch the information using pagination
Fetch the information by crawling the pages and storing it in DB.

Pandas:

Creation of Data representation
Data filtering
Data framework
Selection and viewing
Data Manipulation

Numpy:

Datatypes in Numpy
Creating arrays and Matrix.
Manipulation of data.
Standard deviation and variance.
Reshaping of Matrix.
Dot function
Mini-project using Numpy and Pandas package

Matplotlib:

Creation Plots – Line, Scatter, bar and Histogram.
Creating plots from Pandas and Numpy data
Creation of subplots
Customization and saving plots

Scikit Learn

End to end Implementation of Data science and Machine Learning model using Scikit-Learn(SKLearn)

Explained the option of improving the results by changing parametersand Hyper-parameter in a model.

Getting data ready
Choosing estimators
Fitting the data
Predicting values
Evaluation of results
Improving the results of the model
Saving the model.

Supervised Learning

Data analysis and Basic Plotting
Data Correlation in modelling
Getting data ready for modelling
Model explained in Detail
Improving the Model Randomized SearchCV
Grid Search CV

Unsupervised Learning

K-Means Clusterng
Finding Distance between Clusters
Hierarchial Clusterng
Mini-Project

Course Curriculum

Chapter 1: Python Introduction

Lecture 1: Introduction

Lecture 2: Python Introduction – Part 2

Lecture 3: History of Python

Lecture 4: Features in Python

Chapter 2: Basic Python Set-up

Lecture 1: Tools Online for coding

Lecture 2: Set-up of Python

Lecture 3: After set-up

Chapter 3: Python programming basics

Lecture 1: Hello World

Lecture 2: Python Naming convention

Lecture 3: Keywords in python

Lecture 4: Python basic Syntax

Lecture 5: Lines and identation

Lecture 6: MultiLine Statement

Lecture 7: Quotation

Lecture 8: Comments in Python

Chapter 4: Assigning in Python

Lecture 1: Assigning DataTypes

Lecture 2: Data Types and bit calculation

Lecture 3: Multiple assignment in Python

Lecture 4: Type conversion

Chapter 5: Operators in Python

Lecture 1: Arithmetic Operators

Lecture 2: Comparison Operators

Lecture 3: Assignment Operators

Lecture 4: Logical Operator

Lecture 5: Bitwise Operator

Lecture 6: Membership Operator

Lecture 7: Identity Operator

Lecture 8: Precedence of Operator

Chapter 6: Loop and Comparison using Python

Lecture 1: Decision making

Lecture 2: Nested if and Else

Lecture 3: For Loop

Lecture 4: While Loop

Lecture 5: Range in Python

Lecture 6: Nested Loop

Lecture 7: Loop control -Part 1- Break

Lecture 8: Loop control -Part 2 – Continue

Lecture 9: Loop control -Part 3 – Pass

Lecture 10: Iterators and Generators

Chapter 7: Functions in Python

Lecture 1: Numbers and Type conversion

Lecture 2: Mathematical functions

Lecture 3: Random Numbers

Lecture 4: Trignometric function

Lecture 5: Getting input

Lecture 6: Accessing Strings

Lecture 7: Updating the strings

Lecture 8: Character in String

Lecture 9: String Formatting

Lecture 10: String Operators

Lecture 11: Quotes in Strings

Lecture 12: String function

Chapter 8: List, Tuples and Dictionary

Lecture 1: List introduction

Lecture 2: List Basic options

Lecture 3: List Advanced Option

Lecture 4: Tuples Introduction

Lecture 5: Tuples Basics

Lecture 6: Tuples Advanced

Lecture 7: Dictionary Introduction

Lecture 8: Dictionary basics

Lecture 9: Dictionary Advanced

Chapter 9: Date and Time

Lecture 1: Date and time- Basics

Lecture 2: Date Modules

Lecture 3: Date Directives

Lecture 4: Calender

Chapter 10: Functions and modules in Python

Lecture 1: Function Introduction

Lecture 2: Argument in Function

Lecture 3: Function other topics

Lecture 4: Module advanced

Lecture 5: Modules

Lecture 6: Modules – How to call a module

Lecture 7: Exception and its types

Lecture 8: Exception and its usage

Chapter 11: File Handling

Lecture 1: File Handling Introduction

Lecture 2: File open and close

Lecture 3: File modes

Lecture 4: File read and write

Lecture 5: File and its directory methods

Lecture 6: OS directory – Part 2

Lecture 7: OS directory -Part 3

Chapter 12: Object Orientated Programming

Lecture 1: OOPS Introduction

Lecture 2: Class and objects

Lecture 3: Init method

Lecture 4: Constructor and self

Lecture 5: Types of variables

Lecture 6: Types of Method

Lecture 7: Inner Class

Lecture 8: Inheritance

Lecture 9: Constructor Inheritance

Lecture 10: Duck Typing

Lecture 11: Operator Overloading

Instructors

Chandramouli Jayendran
Office productivity, Data analyst and stock trader

Rating Distribution

1 stars: 3 votes
2 stars: 3 votes
3 stars: 0 votes
4 stars: 3 votes
5 stars: 6 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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