Figuring out what to study to get into AI can seem like a huge task, there are multiple degrees and micro degrees, so what should you focus on? There are three main pathways to AI. The first pathway is the most traditional, which is University-based education undertaking an engineering or science-based bachelor and earning a junior role in a company. The next alternative education products such as short courses or study and the third pathway revolves around the transition between a similar career and developing projects and examples to use for the transition.
..this involves getting a University degree usually in math/science, but increasingly in other areas of study as well.
The authors for this article are primarily based in Australia, the context of this advice has been made general for different education systems, so feel free to change or edit terminology to suit your countries education system.
First, let’s talk about the traditional pathway, this involves getting a University degree usually in math/science, but increasingly in other areas of study as well. Here are some of the primary bachelor degrees to consider:
Considered the standard for a career in AI, CS teaches you programming, problem-solving, data structures, algorithms, etc. This degree will also cover the underlying software engineering principles, which are often underrated as a part of a data scientists toolset. These types of skills will enable you to write code that is usable in production environments. Increasingly, universities are starting to offer units specifically on AI and how to use it in business as well, which is a valuable tool.
This blends a number of aspects of physics and computer science and provides fantastic analytical skills applicable to AI problems, you may need additional programming teaching, however. Engineering has many different facets, and if you are wanting to move into AI, the best majors are:
- Computer Engineering
- Electrical & Electronic Engineering
- Biomedical Engineering
- Mechatronics Engineering
As these majors are focused on the math-heavy, electronic side of engineering which is the type of math and analytical thinking required to do AI work. If you select other majors such as Mechanical or Chemical, the core components of the course are very different and less relevant to the field of AI.
Has a fantastic blend of math and analytical skills as well as academic programming, statistics and probability. You may need to consider some extra study into more commercial programming. This is degree is usually a subset of a Bachelor of Science, which is a great generalist degree to do to get into AI. As with the Engineering degrees, stick toward majors that are more relevant to AI such as Applied Physics or Nanotechnology.
This degree provides a very solid underlying base in statistics, problem-solving and analytical thinking, add some programming courses on top and this is a fantastic degree to consider.
Whilst not purely technical degrees they offer fundamentals in analytical thinking and will help you to consider the business side of data science. Consider additional statistics, calculus, and programming classes if you are in this type of degree. It is worthing doing these types of majors as a part of a Bachelor of Commerce, instead of a Bachelor of Arts, as the fundamental Commerce degree has more relevant to business functions.
Advanced degrees – Masters & PhDs
A master or PhD is often acquired before entering data science, but it’s not essential to getting a job. The rule of thumb is to get advanced degrees for passion not employment, a masters degree may increase your earnings longer term, but you may be better off with extra years of experience (or doing a masters part-time whilst working).
A master or PhD is often acquired before entering data science, but it’s not essential to getting a job.
The advanced degree that you select matters less than having an advanced degree, having the degree enables you to get around the requirements for more senior jobs. Keeping this in mind, if you are going to pursue an advanced degree it is worth picking a subject you are truly interested or passionate in, as it can be quite a number of hard years to finish (particularly a PhD).
Online & Part Time degrees
Universities are now starting to offer various degrees in different types of delivery methods, from online to part-time type degrees. The actual content of these degrees does not often differ, with the online variants being recorded lectures of the in-person degree. However it does change the method of learning, and sometimes can be difficult to ask questions and have the professor help with your learning.
If a part-time or online degree works better for your lifestyle it is definitely worth considering
There is a stigma in industry that is rapidly fading the online and part-time degree “don’t count” as much as a regular degree, as the content is usually identical this is categorically untrue. Where this has come from is degrees such as the MBA (Masters of Business Administration) where one of the primary functions of the degree is to create a network of fellow business professionals. This applies less to a technical degree as the purpose of the degree is technical knowledge. If a part-time or online degree works better for your lifestyle it is definitely worth considering. Another thing to mention is the potential to work for a company and undertake a part-time online degree at the same time, this can get you both the degree and experience simultaneous, but be warned, it will be a lot of work!
For the next parts of this article where we dive into the other pathways, have a look at the links below!
Jeremiah is an Director at PwC leading a Data Advisory team and founder AI Specialist Blog. He has received the ACS ICT Professional of the Year (2019), Top 25 Analytics Professionals Australia (2021, 2018). He has written articles for the AFR, IBM, and LearnDataSci.
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