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A-Z Python Bootcamp(2021)-Basics to Data Science (50+ Hours) - Panter - 21.06.2021
![[Bild: x9nzkulqyyblcvrndocohldjbr.jpg]](https://abload.de/img/x9nzkulqyyblcvrndocohldjbr.jpg)
A-Z Python Bootcamp(2021)-Basics to Data Science (50+ Hours)
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 463 lectures (50h 43m) | Size: 13.1 GB
Python Basic, Data Structure, API, Scraping, Regex, Pandas, Numpy, Matplotlib, Scikit Learn, Supervised Learning
What you'll learn:
Python basic to advanced in One course
Create your first python project
Create your own data science project
Create your project using Django
Requirements
Willingness to learn Python
Decent computer configuration
Description
Learn python basics by practicing Basic syntax, Regular Expression, Data structure & Algorithm and 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 parameters and 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
Who this course is for
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
Homepage
Code:
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