How to Get Involved inside Booming Python Job Market

Information technology has created an exceedingly various and dynamic market and saying “laptop technology” on my own is something of an umbrella time period now.

Pretty much the whole lot has elements of IT in it to some degree — from the algorithms that recommend which TV collection you should watch to the code in this page, and even the software integrating your own home equipment with your mobile.

1. AI
2. cloud development
3. cryptocurrencies and finance
4. data science
5. web development and mobile apps

Nearly any position in an exciting, forward-moving and profitable enterprise would require Python mastery.

But programming alone won’t reduce it. You’ll also need solid knowledge particular to the industry before you will be considered for the role.

Statistics Analysis and Deep Learning

Machine learning: Python in comparison to R and MATLAB.

It’s probably not necessary to explain why Artificial intelligence (AI) is hot right now. In fact, it seems like a method for financial achievement over the past decade was:

successfully develop a proof-of-concept

Machine learning is still on, but these days the name of the game is deep learning. If you’d like to dig even deeper, look at convolutional neural networks.

In our current situation, what that means is that if all we know is AI, whatever problem is presented to us we’re going to try to find datasets and train algorithms for it, when surprisingly often what we needed was just a simple probabilistic model to be able to make a quick prediction.

Let’s take a look at how Python has stacked up towards other languages in each field during the last five years on Google Trends, and also discuss what additional information will be expected from you.

If you’d like to go a step further and compliment your AI knowledge, look into:

descriptive statistics
probability theory
inference
linear algebra

The share of jobs requiring AI skills has grown 4.5x in the last five years, with one in four North American companies having ML embedded in at least one enterprise function as of 2018.

Additionally, Apple, Facebook, and Google are investing in deep reinforcement learning (DRL), and AI-enabled tools are expected to generate nearly $3 trillion in business value by 2021, with the Natural Language Processing (NLP) market alone predicted to reach $22 billion by 2025.

With all this, it’s no surprise that top AI specialists are making $300–500k salaries.

Microservices and Serverless Computing

Serverless architecture: Python compared to JavaScript and Go.

This is another way of saying integrating services with the cloud — and yet it’s another field you can be most certainly will keep on growing.

In the “serverless” execution model, companies are ready to reduce maintenance, save costs, and effectively exchange information across all platforms.

There are a variety of cloud infrastructure providers, but to remain competitive you can focus on handling things with these three:

Particularly, you want to be able to implement and deploy APIs with AWS Lambda and the Amazon API Gateway — or their equivalents in Google’s Cloud Functions and Microsoft’s Azure Functions.

Extra: see a Comparison of Shared and Cloud Hosting, and the way to settle on to further understand how these cloud providers structure their services.

DevOps-related roles have doubled since 2015, and there are more than 50K+ cloud computing jobs within the US alone.

For a cloud specialist in the US, the median salary is $146K.

Blockchain and Quantitative Analysis

Blockchain: Python compared to C++ and Java.

Originally I didn’t decide to include blockchain in this listing because within the (limited and surely biased) way during which I see things, it wasn’t all that clear to me that cryptocurrencies would still be a thing just a few years down the road.

But hey, it’s a fairly active field right now with job offers everywhere place!

Originally published at https://www.epythonguru.com.