Free Data Science Bootcamp: Save $20K

free-data-science-bootcamp-programmer

Data science bootcamps are a great way to break into data science, BUT they are expensive. Are there cheaper alternatives? Let’s review some free alternatives to a bootcamps in data science.

The Price Of A Data Science Bootcamp

Data Science bootcamps are extremely expensive these days, reaching up to 20,000 USD for about 12 weeks of classes.

A bubble?
12-Week bootcamps typically cost 10-25,000USD.
This is more expensive than Harvard or Stanford!

The most famous data science bootcamps are highly pricey. They charge about 2.5K to 7K per month, which is more than what most Ivy League universities charge on an annualised basis.

But is it worth it?

Why Are Data Science Bootcamps So Expensive?

Data science bootcamps are so pricey because:

  1. There is a shortage of skilled data scientists. There are just not enough junior data scientists to fill the open positions.
  2. The traditional education system is too slow producing what the market requires. University graduates are not company-ready as they lack the practical experience.

While there are some good academic programs in reputed universities, the length of the program is at least 3 years or 4 to 5 years if a masters is required.

So, university degrees remain too pricey and too long (up to 160K USD and 4 years time), and thus do not solve the market squeeze problem.

Luckily, you can nowadays learn python and break into data science on your own almost for free, and much faster.

A Free Alternative To A Data Science Bootcamp

For this reason, I’ve designed a data science study plan that is FREE.

This study plan goes over the academic skills and the practical experience that you’ll require for the job and interviews.

The foundations of data science are: Math, Statistics, and Computer Science.

Data science uses statistical tools and programming to come up with valuable business insight.

Well, let’s review what we need to learn.

Free Data Science Bootcamp Syllabus:

“Data scientists know more computer science that statisticians, and more statistics than computer scientists”.

The three main building blocks of Data Science: Math, CS, and Statistics.

Knowing about business/economics will be positive but it is not strictly necessary.

  • Mathematics
    • Introduction to Mathematical Thinking (Stanford)
    • Linear Programming (Imperial)
    • Multivariate Calculus (Imperial)
    • Principal Component Analysis (Imperial)
    • Stochastic Processes (HSE)
  • Computer Science / Programming
  • Statistics
    • Basic Statistics (London)
    • Exploratory Data Analysis
    • Hypothesis testing
    • Bayesian Probability (UCSC 1, UCSC 2)
    • Inferential Statistics
    • Time Series Analysis (SUNY)
    • Causality (UPenn)
  • Machine Learning
  • Business / Marketing
    • Basic Economics
    • Basic Marketing

Online Learning Platforms

The main resources are:

It is highly recommended to get a subscription to either Codecademy or Datacamp (20$ or 30$) to help with the coding side.

Next Steps:

Get started today with a free account at Codecademy or Datacamp while you take the first Intro to Mathematical Thinking and Basic Statistics course.

Do you want to be a data scientist? Start Today!

 

Related Articles