Summary : On this page, we discuss the basic requirements for taking this course.

Basically, this is a beginner’s course. You don’t require any prior programming experience. We discuss basic things like variables, for loops, if statements that are common across most programming languages. We will also look at python specific data structures like lists, dictionaries, tuples, sets etc. However, if you have some level of programming experience either in another language, feel free to skip through the bulk of the course and just pick up on the specifics of python. Just make sure you have a windows or mac laptop with good internet connectivity.

A good computer

All you need to take this course is a good computer. A windows or Mac machine with decent RAM should be good enough. Also, ensure you have a decent internet connection as well.

The median salary for Machine Learning engineers in Python is $111K. That is just the median – If you are experienced enough, the sky is the limit. Look at the following snapshot from Payscale.

Python has extensive 3rd party libraries

Once again, if you are from a Java development background, you might contest this. Java is no slouch when it comes to 3rd party libraries. However, they are all limited to web development and other traditional software development areas. When it comes to Data Science, Maching learning and especially deep learning, Python outpaces all languages when it comes to native support for these. The list of top-grade libraries for Maching Learning and Deep Learning is matchless.

• Deep Learning – keras, pytorch,tensorflow, theano etc.
• Machine Learning – scikit learn, Caffe, Leaf,

The only other language that come this close is probably R.

Python is Developer Friendly

Python development is 3 to 5 time faster than other comparable languages. If you are interested, here is why Python makes the developer’s life easy

Python in Dynamically Typed

Unlike C, C++ or Java, Python is a dynamically typed language. Which means, you would not have to bother with the headache of trying to figure out the data type. That’s why in Python, you would never have to do a

String name = "Ajay Tech"

instead, you can just say

name = "Ajay Tech"

There are some advantages of static typing, but the easy of use with dynamic typing easily overrules the benefits of static typing.

Python is concise

There are very few traditional programming languages that are as concise as Python. For example, just to say “Hello World”, you would have to do this in Java.

public class Helloworld
{
    public static void main (String[] args)
    {
        System.out.println("Hello, world");
    }
}

whereas in Python, you can just say

print("Hello World)

Python is a glue language

When it comes to Data Science or Machine Learning, you would have to work with multiple 3rd party libraries. And Python is a very good glue language. It can connect multiple software components together very easily. For example, if a feature is already implemented in another programming language, say C or C++, it can just be used as-is without having to port it to Python.

Most people compare Python with other high level programming languages like Java and compare Python’s interpreter to Java’s JIT which is faster. Although there is merit to that comparison, in reality the facts are far different. For example, a very popular package for data manipulation is numpy. It is completely written in C, but just wrapped in Python. This makes it almost as fast as C to compute complex n-dimensional array manipulation that might take forever in Java or other high level programming languages.

There are some other examples of glue languages, but Python stands out among them in terms of its simplicity and popularity.