From finance to artificial intelligence, data science to web development, there isn't an area in which Python isn't consolidated and flourishing. So let's discuss actual salaries, skills in demand, marketplaces, and what to do in order to remain competitive.
The Job Market Today
Information technology has created an extremely varied and dynamic market, and saying "computer science" alone is something of an umbrella term now, as pretty much everything has elements of IT in it to different degrees — from the algorithms that recommend which TV series you should watch, to the code in which this page has been programmed, and even the software integrating your home appliances with your mobile.
From this wide array of areas — all of them careers in their own right — we'll pick a handful. All of them are within multi-million/billion-dollar industries that are particularly hot as of 2020, and will most probably remain active in the foreseeable future.
We are talking:
- AI
- cloud development
- cryptocurrencies and finance
- data science
- web development and mobile apps
Nearly any position in an exciting, forward-moving and profitable industry will require Python mastery. (Stack Overflow Trends very eloquently shows how Python gained traction since 2008 until becoming the most talked about programming language.)
But programming alone won't cut it. You’ll also need solid knowledge specific to the industry in which you'll be applying for before you'll be considered for the position.
Let's examine how Python has stacked up against other languages in each field during the last five years on Google Trends, and also discuss what additional knowledge will be expected from you.
Statistics Analysis and Deep Learning
Machine learning: Python compared to R and MATLAB.
It's probably not necessary to explain why Artificial intelligence (AI) it is hot right now. In fact, it seems like a formula for financial success over the past decade was:
- fund an AI startup
- successfully develop a proof-of-concept
- be funded or acquired
- collect profit.
(Man do I abuse oversimplifications!)
Machine learning is still on, but these days .the name of the game is deep learning*; and if you’d like to dig even deeper, look at convolutional neural networks.
Extra: see 5 Ways to Get Started with Machine Learning for some resources on the topic.
Math
But let's not leave it just at AI. Enter math.
Have you heard about the law of the instrument? Abraham Maslow famously said: "I suppose it is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail."
In our current situation, what that means is that if all we know is AI, whatever problem is presented at us we're going to try to find data sets 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. In other words — math.
If you’d like to go a step further and complement your AI knowledge, look into:
- descriptive statistics
- probability theory
- inference
- linear algebra (wouldn't hurt either)
Salaries
The share of jobs requiring AI skills has grown 4.5x in the last five years, with one in four of 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 (NPL) 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. (Source: Udacity.)
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 certain will keep on growing.
In the "serverless" execution model, companies are able to reduce maintenance, save costs, and effectively exchange information across all platforms.
What and Where
There are a number of cloud infrastructure providers, but to remain competitive you can focus on handling things with these three:
- Amazon Web Services (AWS)
- Google Cloud Platform (GCP)
- Microsoft Azure
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 How to Choose to further understand how these cloud providers structure their services.
Salaries
DevOps-related roles have have doubled since 2015, and there are more than 50K+ cloud computing jobs in the US alone
For a cloud specialist in the US the median salary is $146K. (Source: Udacity.)
The post How to Get Involved in the Booming Python Job Market appeared first on SitePoint.
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