Python Programming Machine Learning Python Beginner- Advance

Python Programming Machine Learning Python Beginner- Advance

Python Programming Machine Learning Python Beginner- Advance

Learn Complete Python programming Data Science Data Analysis Deep Learning Machine learning Python & python django core

Language: english

Note: 4.6/5 (326 notes) 39,728 students

Instructor(s): Homework Helper Proz

Last update: 2022-03-05

What you’ll learn

  • Learn python from begging to adavance
  • Use Python for Data Science and Machine Learning
  • You’ll go from being a complete novice to a competent Python coder in no time.
  • Make ten real-world Python applications (no toy programs) Throughout the course, you may improve your abilities by participating in extra practice exercises.
  • Create a completely Python-based personal website.
  • Data analysis and Data visualization
  • Learn basic machine learning
  • Learn about OOP (Object-Oriented Programming)
  • Understand graphical user interfaces (GUIs) (Graphical-User Interfaces)
  • Learn to use Pandas for Data Analysis

 

Requirements

  • Interested and motivation to learn python
  • Any computer

 

Description

Looking to master Python for your job or as a career enhancement?

Take this course to land your first Python developer job!

We also provide you with a FREE textbook!

Goals of this course:

  • Be completely ready to get a full time Python Developer Course at the end of the Course

  • Have projects to impress your Employer and land that dream job!

Go from beginner to advance in Python Programming! Apply your knowledge in Machine Learning Data Science & Data Analysis in this intensive course!

Python is the most widely used programming language on the planet. In the United States, the average pay for a Python developer is $116k. That’s almost $30k more than the competition!


This course (Python Programming Beginner to Advance + Machine Learning) will help you reach your dreams!


Python, Machine Learning, Data Science and Data Analysis is utilized by large corporations like as Google, Facebook, Dropbox, Reddit, Spotify, Quora, and others.


Its clear and beautiful syntax appeals to mathematicians, scientists, engineers, and developers.


It’s the most popular language for AI and machine learning, and it’s also the best language for novices to learn. Much less difficult than C++ or JavaScript! It is also used for various lucrative fields such as Machine Learning, Data Science and Data Analysis.


This course covers all Python has to offer, from the fundamentals to more advanced subjects.


A great blend of theory and practice, jam-packed with real-world examples, exercises, and step-by-step answers – devoid of “fluff” and long explanation!


Learn how to use Python to automation, web development, and machine learning.


You will learn the following:


Introduction to Python course:


Intermediate Python- Functions, Modules, Classes and Exceptions


Introduction Data Analysis in Python


Applied Data Analysis in Python – Machine learning and Data science


Introduction to Deep Learning – Tensorflow for image analysis


Machine learning specialized libraries and frameworks are available in a large number of Python distributions, making the development process easier and decreasing development time. Python’s straightforward syntax and readability enable it to be used for fast testing of complicated algorithms while also making it accessible to those who are not programmers.


Data science with Python is made simpler by the availability of a plethora of libraries, such as NumPy, Pandas, and Matplotlib, which facilitate data cleaning, data analysis, data visualization, and machine learning activities.


In data analysis using python python’s ability to create and manage data structures quickly, for example, is one of the most common applications of the language in data analysis — Pandas, for example, provides a plethora of tools for manipulating, analyzing, and even representing complex datasets — and this is one of the most common applications of Python in data analysis.


We had a team people editing and marketing the course, the editing was done by Mohammad Chowdhury and the marketing was done by Mohammad Fahmid Chowdhury.

The course was created by professors with years of Python experience. The course content was created by Matt Williams, he is a professor with years of Python and Data Science experience, under the CC Attribution license.


Attributions:

Editing: Mohammad Chowdhury

Music: from Bensound

Thumbnail: Image by Manuel Alejandro Leon from Pixabay

Content creator: Matt Williams from University of Bristol

Created under CC attribution license

 

Who this course is for

  • Anyone interested in learning Python

 

Course content

  • Learn the beginner of Python
    • Join the Community
    • FREE Textbook
    • Download Anaconda and JuperLAB on your system
    • Setup Python and Run your first program (Basic/ Beginner Python)
    • How to access content in this section?
    • FREE TEXTBOOK (Complete Python Text with Machine Learning Python)
    • Types of Data (Basics/ Beginner Python)
    • Python Variable
    • Python Calculations
    • Python Error Message
    • Python Lists
    • Python loops
    • Python Conditional Statement
    • Python Dictionaries
    • Python files
    • Next lecture
    • Complete Video of Section 1
  • Intermediate Python- Functions, Modules, Classes and Exceptions
    • Introduction
    • Accessing the content for this course
    • IPython Console
    • String Formatting with Fstrngs
    • Python Functions
    • Python Modules
    • Testing Using Python Data Analysis
    • Classes in Python Data Analysis
    • Class Method In Python Data Analysis
    • Handling Errors Python Data Analysis
    • Next lecture
    • Intermediate Python- Functions, Modules, Classes and Exceptions
  • Introduction Data Analysis in Python
    • Introduction
    • Accessing the content for this course
    • Jupyter Notebook Python with Data Analysis
    • Pandas for Data Analysis
    • Pandas Series for Data Analysis
    • Pandas Data Frames in Data Analysis
    • Reading CSV Files
    • Plotting Data
    • Next lecture- What to expect
    • Introduction Data Analysis in Python
  • Applied Data Analysis in Python – Machine learning and Data science
    • Introduction
    • Accessing the content for this section- Python Course
    • Fitting Data
    • Machine Learning
    • Correlation
    • Clustering
    • Clustering images
    • Summary of Applied Data Analysis in Python
    • Next lecture
    • Applied Data Analysis in Python – Machine learning and Data science
  • Introduction to Deep Learning – Tensorflow for image analysis
    • Introduction
    • Accessing the content for this section- Python Course
    • What are Neural Network
    • Training Network
    • Classifying Irises
    • Imagine analysis
    • Convolution Neural Networks
    • Handwriting Recognition
    • Ethics of Machine Leanring
    • What to expect in the next lecture?
    • Introduction to Deep Learning – Tensorflow for image analysis

 

Python Programming Machine Learning Python Beginner- AdvancePython Programming Machine Learning Python Beginner- Advance

Time remaining or 900 enrolls left

 

Don’t miss any coupons by joining our Telegram group 

Udemy Coupon Code 100% off | Udemy Free Course | Udemy offer | Course with certificate