Which 3-year curriculum to choose? The 6 curricula compared

Choosing a three-year curriculum is a bit like choosing a degree. You commit for a long time, you don’t yet know the field very well, and you are afraid of getting it wrong. The six Atlas curricula were designed to make that choice clearer: they all share the same shape, which makes it possible to compare them properly.

Each one lasts three years, is split into six semesters and adds up to about 1,250 hours of courses, around ten hours a week. What sets them apart is what you learn, how hard it is, the tools you use and, in the end, what you will be able to do. Each curriculum has its own page on the site; this article puts them side by side.

Key figures

The “level” column shows the share of course hours that Coursera rates as beginner, intermediate or advanced. As for perceived quality, it is remarkably even: the average course rating, weighted by number of reviews, is 4.7 out of 5 for every curriculum except Computer Science, at 4.6.

What the figures tell us

The first thing that stands out is the difference in level between curricula. In Humanities & Social Sciences, almost every course hour is rated “beginner”. That doesn’t mean the curriculum is easy: the difficulty lies in reading, writing and the rigour of argument, rather than in technical prerequisites. At the other end, Data Science has nearly two thirds of its hours at intermediate level, and asks you to get through a whole year of mathematics, calculus, linear algebra, probability, before reaching machine learning.

General Science is the broadest of the six. With twenty-nine specializations and eighty-six courses from thirteen universities, it covers mathematics, physics, chemistry and biology. It is also the only curriculum with a noticeable share of advanced courses, in quantum physics or physical chemistry. That breadth comes at a price: it is the curriculum that demands the most regularity, because it often switches discipline and each discipline builds on the previous one.

Economics & Finance and Business & Management look alike at first. Both rely heavily on Excel and on fairly accessible courses. Then they diverge. Economics and finance move towards accounting, company valuation and financial markets, with Python and R to handle data. Business and management head towards marketing, human resources, operations and strategy: less calculation, more case studies and decisions.

Finally, Computer Science and Data Science share a common base: Python, discrete mathematics, algorithms. Then their paths split. Computer science moves on to C, Java, software engineering and security, in other words to building programs. Data science turns to statistics, machine learning and artificial intelligence, that is, to analysing and modelling data.

The three years of each curriculum

Each curriculum is organised into three main stages, which give a good idea of how it progresses:

• Data Science: Foundations; Theoretical computer science and statistics; Data, machine learning and AI.
• Computer Science: Foundations; Programming and algorithms; Software engineering and broadening.
• General Science: Foundations; Core sciences; Advanced sciences.
• Economics & Finance: Foundations; Deepening; Markets and modern finance.
• Business & Management: Foundations; Business functions; Operations, strategy and innovation.
• Humanities & Social Sciences: Foundations; Methods and societies; Today’s world and teaching.

On each curriculum’s page, a timeline shows the three years at a glance, and each semester has its own page, with its goals, the skills it builds, a project and recommended readings.

Four questions to decide

Rather than starting from the curricula, start from yourself. Four questions are usually enough to narrow things down.

What do you want to be able to do in three years? This is the most important question. If you dream of building predictive models, Data Science is the obvious choice. If you want to design and write software, it’s Computer Science. Understanding how matter and living things work: General Science. Analysing a company or a market: Economics & Finance. Leading a team or a project: Business & Management. Investigating, writing, teaching: Humanities & Social Sciences.

How do you feel about mathematics? Be honest. If they have always held you back, Business and Humanities are the most accessible curricula. If, on the contrary, you finally want to improve, General Science starts with a full, very gradual refresher. We wrote an article on exactly this: learning university-level maths on your own.

Do you already have a degree or a job? A full curriculum is not always necessary. If you already have some training and are after a specific skill, a short path of a few months will often be more effective.

Can you keep up ten hours a week for three years? That is the real condition for success, far more than the choice of curriculum itself. We offer some ideas in our method.

Start without deciding everything

Don’t worry: you don’t have to make a final decision today. The first semester of each curriculum lays foundations that are useful well beyond it: Python programming, mathematics, economics, argumentative writing. Take the first semester of the one that appeals to you most. If it doesn’t suit you, what you learned will almost always be useful elsewhere, and you will have learned something valuable about yourself.

On the budget side, we did the maths for each of the six curricula in what a 3-year curriculum on Coursera really costs.