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Does the answer to Cape Town's water crisis lie with data nerds

Academic‚ social and financial solutions have all been thrown at the worsening water crisis in Cape Town – but now it’s the chance of data science to try to find an answer.

The Explore Data Science Academy‚ which launches in the city in January‚ will make Cape Town’s water problem the first project its 100 new recruits aim to tackle.

One of the academy’s founders‚ Aidan Helmbold‚ said that they want to get students coming in and working on problems that have an impact in the real world and will lead to change there.

“We want to start with problems that are massive and topical and show how the skills of data science can be used to help understand [social] problems better and find solutions to them‚” Helmbold said. “That’s why we picked the water crisis in Cape Town.”

The year-long course is a work-based skills programme in a field Helmbold believes “is going to become very valuable in corporate SA in the next few years”.

 Applicants won’t be required to pay for the course‚ which is funded by Telkom’s Business Connexion (BCX)‚ and stipends will be available for those who take part.

More than 3‚300 applications have already been received from those eager to join the academy‚ from which only 100 will be selected. Applicants‚ who must be aged between 17 and 35‚ need not have any experience in data science and the course is perfect for those “with an aptitude for solving problems‚ working hard and writing programs”‚ according to the academy website.

Helmbold said: “Everyone thinks of it as the sort fancy algorithms and number crunching. But we’ve developed a curriculum that to be able to answer data science questions you need to be able to gather‚ analyse‚ visualise and communicate with data. So we’re building it more on a practical level like that.”

The course is in the process of getting accredited through a work-based skills SETA organisation‚ and Helmbold said other data science projects they hoped to work on included next year’s soccer world cup and building models around the classification of people [by] using data.

“We hope that the programme and the practical nature of it will allow the students to be able to implement the solutions when they go into the work place‚ and that’s actually more important to us than whether they get a certificate.”