What are the different Job roles of a Python Developer

Learn Python and you don’t have to worry about finding a job.There are few Programming languages/skills can get you different job roles.Python is one among them.

Python is used right from scripting to constructing large websites.

There is awesome support for machine learning and data science in form of libraries like numpy, scikit-learn, pandas , mllib. Python is used in big-data / map reduce through Apache Spark.

Python is first choice for Scientific computing and is replacing matlab in many cases. Django and Flask are used for constructing powerful websites like reddit and quora that runs on python.

Python introduces new programming constructs like generators, list comprehensions, functional programming that can help in writing elegant code.

If you are interested in this, you can check out a Webinar on Creating a Chatbots using python.

Here are the list of jobs a python developer can have.

Data Scientists

Data scientists are highly educated – 88% have at least a Master’s degree and 46% have PhDs – and while there are notable exceptions, a very strong educational background is usually required to develop the depth of knowledge necessary to be a data scientist.

Their most common fields of study are Mathematics and Statistics (32%), followed by Computer Science (19%) and Engineering (16%).

Technical Skills: Computer Science

Python Coding 

 Python is the most common coding language I typically see required in data science jobs, along with Java, Perl, or C/C++.Other than Python you can learn R as well.

Hadoop Platform

Although this isn’t always a requirement, it is heavily preferred in many cases. Having experience with Hive or Pig is also a strong selling point. Familiarity with cloud tools such as Amazon can also be beneficial.

SQL Database/Coding

Even though NoSQL and Hadoop have become a large component of data science, it is still expected that a candidate will be able to write and execute complex queries in SQL.

Business Analyst

If you enjoy evaluating and analysing data, creating solutions, communicating with a variety of people and have a good grasp of information technology, a career as a business analyst could be for you.  

You’ll need to understand the current organisational situation, identify future needs and create solutions to help meet those needs, usually (but not always) in relation to information and software systems.

Machine Learning

Machine Learning is usually associated with artificial intelligence(AI) that provides computers with the ability to do certain tasks, such as recognition, diagnosis, planning, robot control, prediction, etc., without being explicitly programmed.

It focuses on the development of algorithms that can teach themselves to grow and change when exposed to new data.

In a way, the process of Machine Learning is similar to that of Data Mining. Both search through data to look for patterns.

However, instead of extracting data for human comprehension — as is the case in data mining applications — machine learning uses that data to improve the program’s own understanding. Machine Learning programs detect patterns in data and adjust program actions accordingly.

Now, are you trying to understand some of the skills necessary to get a Machine Learning job? A good candidate should have a deep understanding of a broad set of algorithms and applied math, problem solving and analytical skills, probability and statistics and programming languages such as Python/C++/R/Java.

Beyond all, Machine Learning requires innate curiosity, so if you never lost the curiosity you had when you were a child, you’re a natural candidate for Machine Learning.

Full Stack Developer

Until about a few years ago, a well-planned and perfectly functional website required just two kinds of people to be up and running: a web designer and a web developer. a full stack developer as one who can work cross-functionally on the full “stack” of technology, i.e. both the front end and back end.

Python Web frameworks include Django, Flask, Tornado. Flask is easier to get started with. Django is all batteries included framework, but has a learning curve.

For full stack development, you need to understand

Hosting systems

(the computer; the OS; and supporting services like DNS, SSH, email, and Apache)

Application stack

(web server like Apache or IIS; relational database like Oracle, MySQL, and PostgreSQL; and dynamic server-side web languages like Python, PHP, NodeJS, and Ruby)

Web applications

(model view controller framework like Agavi, Django, and Turbine; object relational modeling like Propel, SQL Alchemy, and Torque; and models, views, application logic, and front-end development including audio, video, HTML, CSS, and JavaScript).

List of my python readings

I have compiled the list of sources for python reading here

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