Learn Python from zero to professional with projects

Can become a MATSER in python in very short period of TIME

For a beginners in Programming you might confused to start what course first, but now it is time to say GOOD BYE  to all your confusions………

What you’ll learn

  • Python.
  • Programming.
  • making projects.

Course Content

  • Introduction to Python –> 4 lectures • 47min.
  • Datatypes –> 3 lectures • 24min.
  • Builtin Functions –> 2 lectures • 26min.
  • Loops –> 4 lectures • 28min.
  • Lists and Tuples –> 3 lectures • 25min.
  • Arrays –> 2 lectures • 32min.
  • Dictionaries and Operators –> 3 lectures • 18min.
  • Calculator Project –> 1 lecture • 19min.
  • Modules –> 2 lectures • 10min.

Learn Python from zero to professional with projects

Requirements

  • Basic Computer.
  • Will to learn.

For a beginners in Programming you might confused to start what course first, but now it is time to say GOOD BYE  to all your confusions………

Because, now we are going to start PYTHON…

It is as Easy as Efficient while learning Python..

* In this course first you are going to learn all the basics about Python.

* From the basics we will go to the Advanced level of Python.

* In Advanced Python we are going to learn how the actual A.I (artificial intelligence) works.

* After that more deeper we will learn about Machine Learning.

* Then about DJANGO and WEBDEV using django.

* Also we will learn, how to do some projects in python.

* Will also make you a master in programming.

* After this course you will be ready with all your stuff for any coding interview.

* Our course will contain all the basic level of Python programming and the Ecosystem combined with Python .

* All the IDE’s used to run our python code.

Often, programmers fall in love with Python because of the increased productivity it provides. Since there is no compilation step, the edit-test-debug cycle is incredibly fast. Debugging Python programs is easy: a bug or bad input will never cause a segmentation fault. Instead, when the interpreter discovers an error, it raises an exception. When the program doesn’t catch the exception, the interpreter prints a stack trace. A source level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and so on. The debugger is written in Python itself, testifying to Python’s introspective power. On the other hand, often the quickest way to debug a program is to add a few print statements to the source: the fast edit-test-debug cycle makes this simple approach very effective.