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STEM Can Kickstart Your Career In Data Science, But Relying Solely On MOOCs Can’t, Says Babak Beheshti, NYIT

STEM Can Kickstart Your Career In Data Science, But Relying Solely On MOOCs Can’t, Says Babak Beheshti, NYIT

When we look at the evolution of artificial intelligence and deep learning through the years, AI and neural networks have been inching closer to human-level performance. The era we live in has been witnessing a rise in different sectors and the one common thread among them all has been the adoption and deployment of AI and analytics. Data science isn’t only limited to AI, it finds applications in many fields because the world is overflowing with data which is waiting to be processed. 

The increased interventions by AI and analytics have started a technological race worldwide. Many governments and private companies are in a never-ending race among their respective competitions to become the supreme in technological power. With so many advancements in technology, India isn’t far behind. India is among the top three ecosystems for developers, and its startups have been going international.

Along with its many other plans of introducing AI in healthcare and agriculture, India plans to take advantages of IoT and 5G to build better infrastructure and smart mobility and India does not show any signs of slowing down. 



With the technological revolution starting to reach its peak, we got in touch with someone who has a great understanding of the international technological scenario — Babak Beheshti, IEEE Member, professor and dean at College of Engineering and Computing Sciences, New York Institute of Technology.

Can you tell us about your role as Dean at NYIT and what does it entail? 

As the Dean of College of Engineering and Computing Sciences, I have the distinct honour to serve more than 80 full time and adjunct faculty, staff and approximately 1,500 students (enrolled in one of 6 undergraduate or 8 graduate degree programs), as we continue our transformation in a highly dynamic landscape of technological innovation. In this capacity, I am charged with creating an environment that will support the development, implementation, growth, and expansion of disciplinary and interdisciplinary opportunities for our faculty and students. I am therefore responsible for overseeing and enhancing the teaching, research and service goals of the College; providing effective management of the College’s fiscal policies, financial resources and budgets; supervising staff personnel and managing promotion and tenure processes, and facilitating collaboration with other academic and non-academic units within the university.

It is a responsibility that I take seriously, but one that is tremendously rewarding. The success of any individual student, staff or faculty member takes us one step forward towards the continued stated goals of the College.

There is a tremendous buzz about the role of AI and analytics and how the talent gap is widening. We see a lot of people joining the field without any quantitative background. In your view, can anybody become a data scientist? What are the baseline attributes one should have to make the cut? 

A minimum knowledge base is required to be effective in the use of data to make decisions. Since decisions made based on data analytics can be mission-critical, business-focused or health-focused and safety-related, the use of available tools without a fundamental understanding of concepts is highly risky for any organisation.

Data analytics knowledge base acquisition can be broken down into two major groups:

  1. Undergraduate or graduate degree programs in data analytics intended for business-related majors. These programs cover the underlying statistical and mathematical concepts, with a focus on the usage of available tools and techniques to make data-driven decisions.
  2. Graduate (MS) degree programs in data science that delve deeply into the science and mathematics of data analytics. These programs provide the learners with a strong and deep mastery of the underlying algorithms, such as the graduates of these programs can serve as analysts, data analytic system designers, and tool developer. These programs require a more technical focused background including computer science and mathematics.

As an academician can you talk about the role of MOOCs and how it has democratised education especially in AI, data science field?

Since the initial boom of MOOCs in 2012, some of the fundamentals have changed. For example, the initial vision was that MOOCs would be free – making online education affordable for masses. But now, as we head towards 2020, most MOOC providers do charge some sort of fee.

While the number of people who have utilised MOOCs is impressive (The number of individuals who had taken at least one MOOC exceeded 100 million), the growth rate of MOOC users is slowing down. The number of learners added last year was 20 million, and the two years prior to that the number of 23 million for each year. Having said that, the number of courses has been growing steadily. Some 900 universities are offering over 11,000 courses. The major MOOC providers have often partnered with major traditional universities to offer their courses.

So in summary, MOOCs have demonstrated to be an innovative paradigm in education, as they have provided an alternative for specialisation and gaining “micro-credentials”. On the other hand, the early predictions of MOOCs growing at a lightning speed to overturn the traditional educations have proven to be somewhat exaggerated.

Give us your take on why graduates should lean more towards STEM education? 

STEM occupations are predicted to be the fastest-growing group in the coming years. In the U.S. alone, employment in STEM occupations grew by 10.5%, between 2009 and 2015. This is in contrast to a rate of 5.2% net growth in non-STEM occupations (US Bureau of Labor Statistics). Among these STEM occupations, computer and engineering-related ones were among the highest job gains.

Additionally, the wages for STEM occupations vary vastly, but again on the average, wages for all STEM occupations are higher than the ones for non-STEM wages (almost by a factor of 2). Moreover, 93% of STEM occupations had wages higher than the national average mean wage.

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These trends are seen similarly worldwide. As a final note with the loss, or significant modification of many professions due to expansion of AI, STEM field provides individuals with the technical skillset that enables them to manage to adapt to the rapidly changing workforce environment.

How can the rise of IoT and 5G transform smart cities? How will this advancement impact India? 

Smart cities rely on sensors to provide information about various quantities that need to be measured, ranging from light to vibration, to stress in concrete structures, to air and water pollutants. To respond to the changing conditions as sensed by these sensors, the actuator would have been commanded to turn things off or on, or perform other actions. To collect the massive amount of data generated by these sensors and send them to local and central processing centres, and then to send massive amounts of data to the actuators, a high speed, high bandwidth communication network is needed. The high bandwidth would allow for scalability as the amount of data grows, and low latency through the network allows for “real-time” responses to changes detected by the sensors.

5G promises to deliver on both of these requirements. With a reduced latency of 1 millisecond, and data rates 100 times more than 4G, smart cities can rely on 5G networks to enable them to carry on their digital transactions reliably and in real-time.

In countries with large population centres such as India, the smart city concept can significantly improve the quality of life for its citizens. This is accomplished by measuring and managing pollution levels locally, managing traffic flow, lowering energy consumption by smart lighting, fleet control, safety monitoring of bridges and tunnels against corrosion and fatigue etc.

India is doubling down on the vision of smart cities, please explain how 5G can ensure low latency? Some of the areas where we see innovations happening are smart traffic management, connected cars, power grids. How can 5G revolutionise this?

Internet of Things or IoT has become a recognisable term. It refers to smart, web-enabled devices that have more of fixed functionality, as compared to general-purpose smartphones, tablets or computers. Example of IoT devices includes connected thermostat, security cameras, door locks, and connected kitchen appliances. 5G has a number of services and architectural features built-in it that makes it an enabling technology for IoT. Given that smart cities essentially will rely on IoT to function, 5G and smart cities are inextricably linked.

5G will play a critical role in allowing information gathered through sensors to be transmitted in real-time to central monitoring locations. This web of connectivity will allow for proactive maintenance of the infrastructure and manufacturing systems, as well as allowing for robust flow control, adjustment and fine-tuning of operating parameters to respond to real-time fluctuations in the environment and processes, as they occur.

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