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Python For Beginners

This course specifically created for Data Science / AI / ML / DL. It covers BASICS PYTHON ONLY

  • Free tutorial
  • Rating: 4.7 out of 54.7 (2,389 ratings)
  • 78,333 students
  • 3hr 55min of on-demand video
  • Created by Vinoth Rathinam
  • English

What you’ll learn

  • Acquire the prerequisite Python skills to move into specific branches – Data Science(Machine Learning/Deep Learning) , Big Data , Automation Testing, Web development etc..
  • Have the skills and understanding of Python to confidently apply for Python programming jobs.

Requirements

  • Passion to learn alone is enough to start this course
  • A Laptop/Computer- Windows, Mac, and Linux are all supported. Setup and installation instructions are included in the video course
  • Access to the internet. Of course all the videos are downloadable . You can study in offline mode also.
  • Recommended : Laptop/Computer the best way to learn this course. Because after completing each topic , practicing it simultaneously in Jupyter notebook makes you to remember each topic easily

Description

This course specifically created for A.I Aspirants ( Data Science/Deep Learning/Machine Learning students). It covers all the PYTHON BASICS topics. But still this course can also be learnt by other fields aspirants like Automation, Chatbots, WebDevelopers etc. Because for all the fields this course will create basic knowledge and with this you can self learn python library easily.

Note: Very soon Python Libraries such as NumPy, Pandas and Matplotlib courses will be launched. But for all these advanced course , this “Python For Data Science” course  will be the basement for it.

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” 9 main reasons to Learn Python !!! “

1. Python’s popularity

When compared to all other programming language, python is extremely simple, easy to learn, interpret and implement. Due to this reason it became very popular and trending programming right now.

2. High salary

The job demand for python programmers are high. Python engineers have some of the highest salaries in the industry.

The average Python developer salary in the US is $110,021 and $123,743 per year according to the survey conducted by Gooroo and Indeed respectively

3. Python is used in Data Science

There are plenty of Python scientific packages for data visualization, machine learning, natural language processing, complex data analysis and more. All of these factors make Python a great tool for scientific computing and a solid alternative for commercial packages such as MatLab. The most popular libraries and tools for data science are Pandas, matplotlib, NumPy, scikit-learn, Mlpy, NetworkX, Theano, SymPy and TensorFlow

4. Python is used in Automation

IT industries are now moving towards Artificial Intelligence in Automation. So Python with Robot framework combination is the best alternative for Selenium Webdriver with Java as it is easier road map with no programming background.

5. Python used with Big Data

Pydoop is a Python interface to Hadoop that allows you to write a MapReduce program in Python and process data present in the HDFS cluster.

Its features such as a rich HDFS API; a MapReduce API that allows to write pure Python record readers / writers, partitioners and combiners, transparent Avro (de)serialization, and easy installation-free usage.

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6. Chat Bots

A chat bot is an artificial intelligence-powered piece of software in a device (Siri, Alexa, Google Assistant etc), application, website or other networks that try to gauge consumer’s needs and then assist them to perform a particular task like a commercial transaction, hotel booking, form submission etc.

NLTK(Natural Language Toolkit) library is a leading platform for building Python programs to work with human language data.

7. Python in Web Development

Python has a wide range of frameworks for developing websites. The most popular frameworks are Django, Flask, Web2Py, Turbo Gears, etc. These frameworks are written in Python, so it’s easier to implement and use it for web development.

8. Computer Graphics in Python

Python is largely used to build GUI and desktop applications. The Python Computer Graphics Kit is a generic 3D package that can be useful in any domain where you have to deal with 3D data of any kind, be it for visualization, creating photorealistic images, Virtual Reality or even games

9. Game Developer

Python libraries such as PyGame, Pyglet , PyOpenGL etc. are used to develop 2D, 3D games with easy coding. Learning any one of these package can able to create rapid game prototyping or for beginners learning how to make simple games.

Who this course is for:

  • Data Science / Artificial Intelligence/ Machine Learning / Deep Learning Aspirants
  • Chat Bots Developer
  • Automation Testers
  • Big Data Aspirants
  • Web Development Aspirants
  • Game Developers
  • People interested in programming who have no prior programming experience
  • Anyone who wants to learn BASIC PYTHON
  • Existing programmers who want to improve their career options by learning the Python programming language
  • Students taking a Python class in school who want a supplementary learning source
  • Note 1 : SPECIFICALLY CREATED FOR DATA SCIENCE / AI / ML / DL ASPIRANTS AND COVERS BASICS PYTHON ONLY
  • Note 2: This course is NOT for experienced Python programmers
  • Note 3: All the videos are explained in Indian English Slang. In case if you think, its tough to understand my pronunciation and also for Non-English speaking students, I enabled the Auto Caption now. But still the text won’t 100% accurate.
  • Note 4: Based on students interest and request , I will be adding few more python topics to this course
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Course content

6 sections β€’ 29 lectures β€’ 3h 55m total lengthCollapse all sections

Python Introduction5 lectures β€’ 39min

  • Introduction to Python06:55
  • How to choose Python IDE and Installation Steps08:12
  • Overview of Jupyter Notebook and Python Programming Basics08:20
  • Identifiers and Keywords09:09
  • Python Variables06:31
  • Python Introduction9 questions

Python Operators4 lectures β€’ 31min

  • Python Numbers and Arithmetic Operators09:49
  • Arithimetic Operators5 questions
  • Comparison and Logical Operators05:47
  • Assignment and Bitwise Operators08:17
  • Identity and Membership Operators07:09
  • Operators5 questions

Python Flow Control5 lectures β€’ 33min

  • if and if else Statement05:42
  • if..elif..else and nested if Statement04:58
  • Control Statement5 questions
  • Python While Loop Statement04:58
  • Python For Loop Statement10:10
  • For Loop6 questions
  • Python Break and Continue Statement07:05
  • Looping Statement6 questions

Python Data Types String and List6 lectures β€’ 53min

  • Python String Part 109:28
  • Python String Part 208:12
  • Python Strings5 questions
  • Python Strings Methods09:53
  • String Methods5 questions
  • Python Lists09:27
  • Python List5 questions
  • Python Lists Methods Part 108:01
  • Python Lists Methods Part 208:16
  • Python List Methods5 questions

Python Data Types Tuples and Dictionary5 lectures β€’ 48min

  • Python Tuples08:24
  • Python Tuple Methods09:35
  • Tuples5 questions
  • Python Dictionary08:37
  • Python Dictionary Deleting and Looping09:49
  • Python Dictionary Methods11:18
  • Python Dictionary5 questions

Python Functions4 lectures β€’ 31min

  • Creation and Execution of Functions08:32
  • Python Functions with Return Value05:23
  • Python Function Arguments10:33
  • Python Function5 questions
  • Python Recursive Function06:40

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