Opinion

(Or learn anything, for that matter)

Photo by 贝莉儿 DANIST on Unsplash

🖥 Why learn to code?

Learning to code is a really valuable skill. You can use it to build things that impact the world. And it’s a desirable skill in the current job market.

But it’s not easy. It takes a long time to learn.

There are different approaches you can take, with stacks of different courses and bootcamps available.

However, I think your focus should be on self-designed projects. Here are 6 reasons why:

🥅 (1) Projects most accurately replicating the end goal

At the end of the day, what is the purpose of learning to code?

The exact end goal will vary…


Using the YouTube API and Amazon’s AWS Lambda

Photo by NordWood Themes on Unsplash

🚀 Escaping the YouTube algorithm

I love watching YouTube videos that improve my life in some tangible way. Unfortunately, the YouTube algorithm doesn’t agree. It likes to feed me clickbait and other garbage.

This isn’t all that surprising. The algorithm prioritises clicks and watch time.

So I set out on a mission: Can I write code that will automatically find me valuable videos, eliminating my dependence on the YouTube algorithm?

Here’s how it went.

🗺️ The best laid plans

I started by visualising what I wanted the tool to do. …


Why our AI needs to understand causality

Photo by Uriel SC on Unsplash

What’s wrong with correlation?

In May 2016, the COMPAS algorithm was flagged as being racially biased [1]. This algorithm was used by the US to guide criminal sentencing by predicting likelihood of reoffending. It estimated a black person was more likely to re-offend than a white person with the same other background factors.

The problem was, the algorithm was mistaking correlation (patterns of crime in the past) with causation (that being black makes you more likely to commit a crime).

This can be a problem in medicine as well. Consider the following:

100 patients are admitted to hospital with pneumonia, of which 15 also…


5 takeaways from an unconventional career transition

Photo by Marius Masalar on Unsplash

Background

3 years ago, I had just finished medical school and started working full-time as a doctor in the UK’s National Health Service (NHS). Now, I work full-time as a data scientist at dunnhumby, writing code for “Big Data” analytics with Python and Spark.

More and more people are making the transition towards data science, or related technical roles, from a variety of disciplines. So in this article I’m going to share my experiences and advice for making a (perhaps) unconventional career transition into a technical role. I can break these down into five main learnings:

(1) Find technical friends

Coming from a medical background…


(and lead to new, cheaper drugs and improved patient health)

The cost of drug discovery

The drug development process is notoriously difficult; it takes on average 10–15 years to take a drug from identifying the molecule to being used clinically, and only approximately 3% of the initial drugs will make it all the way through. The cost of bringing a drug all the way through the development pipeline, only to fail at the final hurdle, typically exceed $1 billion.

For those not familiar with the drug development pathway, here’s a useful overview:

As the diagram shows, there are numerous stages where drugs can fail. It’s far better to fail early than fail late, so any…


Using BeautifulSoup and Selenium

source: unsplash.com

Motivation

I’m currently looking for a new data science role, but have found it frustrating that there are so many different websites, which list different jobs and at different times. It was becoming laborious to continually check each website to see what new roles had been posted.

But then I remembered; I’m a data scientist. There must be an easier way to automate this process. So I decided to create a pipeline, which involved the following steps, and to automate part of the process using Python:

1. Extract all new job postings at a regular interval

I decided to write some Python code to web-scrape jobs from the websites I was…


Data Science in the Real World

And why the healthcare AI space needs more doctors

We are seeing increasing use of, and discussion about, artificial intelligence (AI) and machine learning (ML) across all sectors; healthcare included. Greater volumes of data, improved computing power and break-throughs in machine learning techniques have provided fertile soils for innovation. In healthcare, this is reflected by an exponential increase in research involving AI, and a corresponding surge in publications and academic funding.

But do doctors really need to understand machine learning? We think so, and here are our top reasons why.

Communication with patients

We are beginning to see machine learning tools used in clinical settings and with our current wave of new…


I read an article a few months ago about how Jeff Bezos banned PowerPoints from meetings at Amazon. Instead, people write a “narratively structured six-page memo” to lay out what’s being discussed.

At the time of reading the article, I was creating a PowerPoint presentation for a group of medical students. I was delivering four sessions covering machine learning principles and their applications in healthcare. However, I was finding it challenging to condense complex ideas into bullet points on the slides. I was also struggling to consolidate my knowledge while doing so.

After reading the article I switched to the…


About 3 years ago, I developed a deep interest in learning to rap well. I emphasize the word ‘developed’ because up until this point, I was waiting to passively discover a passion which would somehow carry me towards expertise.

Authenticity

The main initial ingredient — from my experience — needed to produce expertise is authenticity. Authenticity is essential because any serious undertaking of a new skill will necessarily face you up against failure and self-doubt. The new skill needs to be important enough to make this tolerable. With rap, I reached a point where I needed to know my thoughts…


“Is medicine right for me?” is a question that a lot of medics ask at some point during their career.

Perhaps you’re fed up of endless exams, not enthusiastic about working nights and weekends for the foreseeable future, or just don’t think it’s a good match for your personality.

Whatever your reasoning, there are a few points worth bearing in mind.

Important considerations

It’s worth noting that whatever your source of dissatisfaction, no career change is going to immediately solve this. It’s easy in a moment of frustration to think “screw this, my life would be so much easier if I became…

Chris Lovejoy

Data Scientist + Junior Doctor in London, Cambridge medicine grad, striving to improve healthcare through technology and education. chrislovejoy.me

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store