You’ve probably heard that data science is one of the most important professions – and that professional development pathways are one of the most promising you can make. With the demand for talent far outstripping supply and the looming importance of companies to effectively harness their data to remain competitive, it’s a great time to learn.

I’ve spent more than a decade learning almost every subfield of data science, from data mining to classic AI, machine learning, statistics (both Bayesian and frequentist), software development, recommender systems, neurocomputing and more. And with each new development, I find it even more fascinating.

Probably, one of the most exciting parts of being a data scientist is the opportunity to work on very diverse and impactful projects. As the famous statistician, John Tukey said:

“The best thing about being a statistician is that you get to play in everyone’s backyard.”


Which couldn’t be more true for the field. One year you may be working with a large retailer on a recommendation engine, and then the next, you might be using neural networks to generate artworks – the variation is immense and opens doors to companies you hadn’t considered.

But this is just the start. The world’s organisations have increasingly recognised the value of data-based decision making and that it has a very real role to play. The new competitive advantage of organisations over the next 10 years will be how they understand and utilise their data.

The antagonistic relationship between new tech disruptors and industry incumbents has shown that the differentiating factor is data – so yes, the field is very important.




What I’ve come to understand is that there should be a way for someone with the right technical background (perhaps software developer or mechanical engineer) to easily convert to a ready-to-work data scientist. It’s a form of upskilling that I believe will have immense implications on innovations around the world.

But I also know that undertaking this journey is daunting, particularly without any signposting.

There are many resources online both free and paid for learning data science, but many are simply not complete and have the wrong focus. Why? Because the modern data scientist needs to combine various skills, which not many courses do not cater for.

The complete data scientist, first of all, needs to know about both machine learning and statistics; knowledge of either R or Python (ideally both) is a must; some coding skills ideally from software development to databases; and, finally, a data scientist needs to possess good business acumen including to be able to communicate with key stakeholders.


Following tutorials in R, Python or deep learning will not turn you into a data scientist overnight. Similarly, taking part in Kaggle competitions can help you improve your skills, but it won’t give you the necessary business or communication skills required to be the master of your game.

And then there’s the right mix of study materials, teaching methods and flexibility to take into consideration. Courses that offer the crucial mix of remote study with personalised and tailored topics are hard to come by – especially with online courses.

A personalised course to make data science relevant to you but without sitting in a classroom all day? This is surely the right fit.

The right kind of data science course


We’ve worked to find that right balance of personalised learning with flexibility built-in, with the aim of employability at its centre.

The result: Datalyst Academy

It’s a data science course specifically designed to turn you into a data scientist in just 12 weeks, but can be completed at your own pace. You can even pick and choose a particular subject you’re interested in. It’s holistic at its core and approach as it touches upon all the subjects that a complete data scientist needs to know. But at the same time specialises in all the things a new data scientist is usually called upon to do in real-world projects.

The course combines practical exercises, lecturing, self-driven study and projects on real-world use cases that can be used to build your portfolio. This combines the best of both worlds: breadth and depth all whilst maintaining the flexibility of an online course.

We have painstakingly pulled together a syllabus that’s full of exercises, based on real-world use cases. This is accompanied by teaching one the most popular libraries in data science (Keras, scikit-learn, the tidyverse and many more).

The course has a strong focus on the job market, helping you build a portfolio of projects which is an important inclusion to your CV. At the end of the program, we will host a job fair where prospective data scientists will have the opportunity to showcase their talent and go through job interviews.

But the most important aspect behind Datalyst academy is that it is optimised for the working professional and busy student with flexibility in mind. The courses are taught in the evening, are flexible and there is remote and online support from myself.

I support you every step of your data science journey, honing the course to fit your needs, interests and priorities – it’s up to you.

Get in touch below to learn more about how Datalyst Academy can work for you.

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