Zorina Alliata Of Open Institute of Technology On Five Things You Need To Create A Highly Successful Career In The AI Industry
Source:
- Authority Magazine Medium, Published on September 15th, 2024.
Gaining hands-on experience through projects, internships, and collaborations is vital for understanding how to apply AI in various industries and domains. Use Kaggle or get a free cloud account and start experimenting. You will have projects to discuss at your next interviews.
By David Leichner, CMO at Cybellum
14 min read
Artificial Intelligence is now the leading edge of technology, driving unprecedented advancements across sectors. From healthcare to finance, education to environment, the AI industry is witnessing a skyrocketing demand for professionals. However, the path to creating a successful career in AI is multifaceted and constantly evolving. What does it take and what does one need in order to create a highly successful career in AI?
In this interview series, we are talking to successful AI professionals, AI founders, AI CEOs, educators in the field, AI researchers, HR managers in tech companies, and anyone who holds authority in the realm of Artificial Intelligence to inspire and guide those who are eager to embark on this exciting career path.
As part of this series, we had the pleasure of interviewing Zorina Alliata.
Zorina Alliata is an expert in AI, with over 20 years of experience in tech, and over 10 years in AI itself. As an educator, Zorina Alliata is passionate about learning, access to education and about creating the career you want. She implores us to learn more about ethics in AI, and not to fear AI, but to embrace it.
Thank you so much for joining us in this interview series! Before we dive in, our readers would like to learn a bit about your origin story. Can you share with us a bit about your childhood and how you grew up?
I was born in Romania, and grew up during communism, a very dark period in our history. I was a curious child and my parents, both teachers, encouraged me to learn new things all the time. Unfortunately, in communism, there was not a lot to do for a kid who wanted to learn: there was no TV, very few books and only ones that were approved by the state, and generally very few activities outside of school. Being an “intellectual” was a bad thing in the eyes of the government. They preferred people who did not read or think too much. I found great relief in writing, I have been writing stories and poetry since I was about ten years old. I was published with my first poem at 16 years old, in a national literature magazine.
Can you share with us the ‘backstory’ of how you decided to pursue a career path in AI?
I studied Computer Science at university. By then, communism had fallen and we actually had received brand new PCs at the university, and learned several programming languages. The last year, the fifth year of study, was equivalent with a Master’s degree, and was spent preparing your thesis. That’s when I learned about neural networks. We had a tiny, 5-node neural network and we spent the year trying to teach it to recognize the written letter “A”.
We had only a few computers in the lab running Windows NT, so really the technology was not there for such an ambitious project. We did not achieve a lot that year, but I was fascinated by the idea of a neural network learning by itself, without any programming. When I graduated, there were no jobs in AI at all, it was what we now call “the AI winter”. So I went and worked as a programmer, then moved into management and project management. You can imagine my happiness when, about ten years ago, AI came back to life in the form of Machine Learning (ML).
I immediately went and took every class possible to learn about it. I spent that Christmas holiday coding. The paradigm had changed from when I was in college, when we were trying to replicate the entire human brain. ML was focused on solving one specific problem, optimizing one specific output, and that’s where businesses everywhere saw a benefit. I then joined a Data Science team at GEICO, moved to Capital One as a Delivery lead for their Center for Machine Learning, and then went to Amazon in their AI/ML team.
Can you tell our readers about the most interesting projects you are working on now?
While I can’t discuss work projects due to confidentiality, there are some things I can mention! In the last five years, I worked with global companies to establish an AI strategy and to introduce AI and ML in their organizations. Some of my customers included large farming associations, who used ML to predict when to plant their crops for optimal results; water management companies who used ML for predictive maintenance to maintain their underground pipes; construction companies that used AI for visual inspections of their buildings, and to identify any possible defects and hospitals who used Digital Twins technology to improve patient outcomes and health. It is amazing to see how much AI and ML are already part of our everyday lives, and to recognize some of it in the mundane around us.
None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful for who helped get you to where you are? Can you share a story about that?
When you are young, there are so many people who step up and help you along the way. I have had great luck with several professors who have encouraged me in school, and an uncle who worked in computers who would take me to his office and let me play around with his machines. I now try to give back and mentor several young people, especially women who are trying to get into the field. I volunteer with AnitaB and Zonta, as well as taking on mentees where I work.
As with any career path, the AI industry comes with its own set of challenges. Could you elaborate on some of the significant challenges you faced in your AI career and how you managed to overcome them?
I think one major challenge in AI is the speed of change. I remember after spending my Christmas holiday learning and coding in R, when I joined the Data Science team at GEICO, I realized the world had moved on and everyone was now coding in Python. So, I had to learn Python very fast, in order to understand what was going on.
It’s the same with research — I try to work on one subject, and four new papers are published every week that move the goal posts. It is very challenging to keep up, but you just have to adapt to continuously learn and let go of what becomes obsolete.
Ok, let’s now move to the main part of our interview about AI. What are the 3 things that most excite you about the AI industry now? Why?
1. Creativity
Generative AI brought us the ability to create amazing images based on simple text descriptions. Entire videos are now possible, and soon, maybe entire movies. I have been working in AI for several years and I never thought creative jobs will be the first to be achieved by AI. I am amazed at the capacity of an algorithms to create images, and to observe the artificial creativity we now see for the first time.
2. Abstraction
I think with the success and immediate mainstream adoption of Generative AI, we saw the great appetite out there for automation and abstraction. No one wants to do boring work and summarizing documents; no one wants to read long websites, they just want the gist of it. If I drive a car, I don’t need to know how the engine works and every equation that the engineers used to build it — I just want my car to drive. The same level of abstraction is now expected in AI. There is a lot of opportunity here in creating these abstractions for the future.
3. Opportunity
I like that we are in the beginning of AI, so there is a lot of opportunity to jump in. Most people who are passionate about it can learn all about AI fully online, in places like Open Institute of Technology. Or they can get experience working on small projects, and then they can apply for jobs. It is great because it gives people access to good jobs and stability in the future.
What are the 3 things that concern you about the AI industry? Why? What should be done to address and alleviate those concerns?
1. Fairness
The large companies that build LLMs spend a lot of energy and money into making them fair. But it is not easy. Us, as humans, are often not fair ourselves. We even have problems agreeing what fairness even means. So, how can we teach the machines to be fair? I think the responsibility stays with us. We can’t simply say “AI did this bad thing.”
2. Regulation
There are some regulations popping up but most are not coordinated or discussed widely. There is controversy, such as regarding the new California bill SB1047, where scientists take different sides of the debate. We need to find better ways to regulate the use and creation of AI, working together as a society, not just in small groups of politicians.
3. Awareness
I wish everyone understood the basics of AI. There is denial, fear, hatred that is created by doomsday misinformation. I wish AI was taught from a young age, through appropriate means, so everyone gets the fundamental principles and understands how to use this great tool in their lives.
For a young person who would like to eventually make a career in AI, which skills and subjects do they need to learn?
I think maybe the right question is: what are you passionate about? Do that, and see how you can use AI to make your job better and more exciting! I think AI will work alongside people in most jobs, as it develops and matures.
But for those who are looking to work in AI, they can choose from a variety of roles as well. We have technical roles like data scientist or machine learning engineer, which require very specialized knowledge and degrees. They learn computing, software engineering, programming, data analysis, data engineering. There are also business roles, for people who understand the technology well but are not writing code. Instead, they define strategies, design solutions for companies, or write implementation plans for AI products and services. There is also a robust AI research domain, where lots of scientists are measuring and analyzing new technology developments.
With Generative AI, new roles appeared, such as Prompt Engineer. We can now talk with the machines in natural language, so speaking good English is all that’s required to find the right conversation.
With these many possible roles, I think if you work in AI, some basic subjects where you can start are:
- Analytics — understand data and how it is stored and governed, and how we get insights from it.
- Logic — understand both mathematical and philosophical logic.
- Fundamentals of AI — read about the history and philosophy of AI, models of thinking, and major developments.
As you know, there are not that many women in the AI industry. Can you advise what is needed to engage more women in the AI industry?
Engaging more women in the AI industry is absolutely crucial if you want to build any successful AI products. In my twenty years career, I have seen changes in the tech industry to address this gender discrepancy. For example, we do well in school with STEM programs and similar efforts that encourage girls to code. We also created mentorship organizations such as AnitaB.org who allow women to connect and collaborate. One place where I think we still lag behind is in the workplace. When I came to the US in my twenties, I was the only woman programmer in my team. Now, I see more women at work, but still not enough. We say we create inclusive work environments, but we still have a long way to go to encourage more women to stay in tech. Policies that support flexible hours and parental leave are necessary, and other adjustments that account for the different lives that women have compared to men. Bias training and challenging stereotypes are also necessary, and many times these are implemented shoddily in organizations.
Ethical AI development is a pressing concern in the industry. How do you approach the ethical implications of AI, and what steps do you believe individuals and organizations should take to ensure responsible and fair AI practices?
Machine Learning and AI learn from data. Unfortunately, lot of our historical data shows strong biases. For example, for a long time, it was perfectly legal to only offer mortgages to white people. The data shows that. If we use this data to train a new model to enhance the mortgage application process, then the model will learn that mortgages should only be offered to white men. That is a bias that we had in the past, but we do not want to learn and amplify in the future.
Generative AI has introduced a new set of fresh risks, the most famous being the “hallucinations.” Generative AI will create new content based on chunks of text it finds in its training data, without an understanding of what the content means. It could repeat something it learned from one Reddit user ten years ago, that could be factually incorrect. Is that piece of information unbiased and fair?
There are many ways we fight for fairness in AI. There are technical tools we can use to offer interpretability and explainability of the actual models used. There are business constraints we can create, such as guardrails or knowledge bases, where we can lead the AI towards ethical answers. We also advise anyone who build AI to use a diverse team of builders. If you look around the table and you see the same type of guys who went to the schools, you will get exactly one original idea from them. If you add different genders, different ages, different tenures, different backgrounds, then you will get ten innovative ideas for your product, and you will have addressed biases you’ve never even thought of.
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Life is unpredictable. While many of us have specific hopes and expectations of how our futures will turn out, things don’t always go as expected. There are many variables and unexpected incidents that can interfere and force you to alter your plans, and this is particularly true when it comes to education.
For instance, you might have had plans to study a specific subject, but had to deviate from those plans due to unforeseen circumstances. Or you may have had to enter the workforce in an occupation different from the one you sought in an effort to earn an income, a move that may not provide you with the time or opportunity to achieve your desired educational aims.
In short, every individual’s career pathway is different, and very few go exactly as we expect from the outset. Fortunately, even if you experience a few false starts or sudden twists in your pathway, there are always options available to help you get back on track.
The Unpredictable Nature of Education
In theory, the educational process seems simple. You select a course of study that interests you from the vast array of subjects and prospective professions, select the appropriate classes, acquire the knowledge and skills you need to succeed, and then embark on your profession.
In reality, however, as many people know from firsthand experience, the road to education is often far from straightforward. Here are just some of the many challenges that can take your educational path in a completely different direction:
- Life’s Curveballs: As touched on in the introduction, life is impossible to predict. Financial hardships, health issues, and family emergencies are just some of the unfortunate occurrences that might derail even the most perfectly planned educational regime.
- Changing Interests: People’s desires and preferences don’t necessarily stay the same throughout their entire lives. As you grow, learn, and have new experiences, your interests may change, and so, too, may your educational objectives.
- Pressure and Burnout: Some academic paths are particularly challenging, demanding intense levels of study and hard work. This can sometimes prove too much to bear, even for the most resilient students.
- Failures and Setbacks: Conventional education largely builds around tests and examinations, requiring students to demonstrate their competencies repeatedly. It’s a system that doesn’t suit everyone, and test failures can lead to setbacks and delays.
- Inequality: People can be born with very different privileges and levels of access to education. Those in certain parts of the world may find it much more challenging to complete their education path for financial, cultural, or even political reasons.
- Late Bloomers: People develop at different paces. Some may struggle educationally early on in their lives, forcing them to make certain concessions or sacrifices related to their studies, only to find their feet later in life once they’ve entered the world of work.
Whether you’re a late bloomer, have had your educational aspirations delayed by personal problems, desire to learn new skills and try something different, or want to begin a fresh chapter in your professional life, the Open Institute of Technology (OPIT) may be able to help.
Introducing OPIT
OPIT is an online teaching platform, making high-level technological educational programs accessible to all, no matter their age or background. Offering education in fields like computer science, artificial intelligence, and digital business, OPIT provides a curated collection of degrees. In addition, they offer classes taught by world-leading tutors imparting the wisdom and skills students need to achieve their goals and become the tech leaders of tomorrow.
Meanwhile, for those who have had somewhat tumultuous or unpredictable educational paths, OPIT offers the perfect course corrector: the OPIT Foundation Year.
The OPIT Foundation Year
OPIT’s Foundation Year is a Pre-Tertiary Certificate in Information Technology, fully aligned with MQF/EQF Level 4 standards and valued at 60 ECTS credits. Lasting just one year, this program essentially serves as a comprehensive yet accessible springboard towards higher-level education, creating a path towards degrees and careers in dynamic, flexible fields, like computer science and digital business.
Like other OPIT programs, the Foundation Year is delivered entirely online via the OPIT Virtual Learning Environment. Combining live lectures, asynchronous content, and interactive assessments, students enjoy diverse and dynamic study experiences, acquiring core skills like academic writing, mathematics, and computer literacy, and building a bedrock of knowledge and confidence before taking their next steps.
Who Is the Foundation Program For?
The Foundation Program is designed to provide a solid base upon which to build the technological education many students need. It’s the perfect choice for those who are eager and ambitious to enter professions in AI, data science, and computing, but don’t feel that they have the necessary core skills and knowledge needed to dive straight into a degree.
Entry requirements are relatively relaxed in order to allow as many students as possible to enjoy the benefits of this program. With that said, applicants should ideally hold an MQF/EQF Level 3 or equivalent qualification, with the intention of pursuing a bachelor’s degree. A minimum of B2 level of English proficiency is also required, as this is the working and studying language of the institution.
What the Foundation Year Provides
Perhaps you’ve recently graduated, are considering a career change, or finally have the opportunity to return to education after initial delays or unexpected disruptions to your original plans. Either way, the Foundation Year can help you enjoy:
- Greater Self-Confidence: Foundation Year graduates gain the fundamental skills they need to enter degree programs with much more self-belief and assuredness.
- Superior Tech Knowledge: Lasting two terms, this course explores mathematics, academic reading and writing, and provides an introduction to computer hardware and software.
- Foundational Mathematics: Mathematics literacy forms a large part of the study focus for the Foundation Year, helping students feel more comfortable with numbers and formulas.
- Flexible Learning: Unlike more rigid, conventional education environments, OPIT gives you the freedom and flexibility to study at a pace that suits you best, all from the comfort of home.
- Global Community: OPIT is an international institution, with staff and students from all around the world eager to share knowledge, exchange ideas, and help one another.
Take Your Next Steps to Success With the OPIT Foundation Year
If you’re curious about a career in technology or have always wanted to work with AI, data, and computers, but struggled to find the time and opportunities you need to acquire relevant skills and knowledge, the Foundation Program was made for people like you.
It’s the ideal entry point into the exciting world of online education, and the perfect first step towards a prestigious degree from an innovative and increasingly successful institution. Download the brochure to learn more about it, or start your online application, today.
Students today have a broader range of fields of study to choose from than ever before, but with the world becoming increasingly technological and computers increasing in influence and importance, pursuing a career in computer science often proves a smart, strategic choice.
There are numerous benefits and career paths associated with studying and working in computer science, and we’ll be listing just a few of them in this guide.
High Average Salaries
With the rising cost of living in many parts of the world, it’s unsurprising that many students are thinking several decades ahead to determine what level of starting salaries they could obtain in different career fields.
Many are also seeking professions that offer the opportunity for growth and the ability to advance up the ranks over time, thus increasing their salary and their quality of life in the process.
If a strong, stable salary with the opportunity for improved income is one of your top career priorities, computer science should be at or near the top of your list of prospective careers.
According to recent data, computer scientists earn an average of over €65,000 per year, with certain jobs, like IT project leader and data scientist, paying ever higher. Starting salaries are strong, too, with graduates earning anywhere from €46,000 to €60,000, depending on their chosen profession and level of qualifications.
There are similarly high average salaries reported around the world in computer science and related fields such as data science and AI/ML engineering. These numbers are projected to increase in the years to come, pointing to computer science as a way for graduates to get off to the best financial start of any career.
Unrivaled Flexibility
A common problem with some subjects and courses is that they only provide graduates with a narrow set of skills and a similarly narrow range of potential professions to which they can apply those skills.
That’s not the case with computer science. Graduates in this field can enjoy instant access to a remarkably diverse array of career opportunities, with even newer opportunities being created all the time as technology evolves and innovations emerge.
A few of the many industries and roles you might choose to enter in the field of computer science include:
- Healthcare: As a software developer, data analyst, or cybersecurity expert
- Finance: As a fintech engineer, blockchain developer, or security analyst
- Media: As a graphics programmer, AI developer, or game developer
- Education: As an analyst, software developer, or machine learning engineer
Guaranteed Opportunities
Some career paths are more limited than others, with relatively low numbers of opportunities, recurring risks of job loss, or difficulty obtaining employment in the first place.
Again, with computer science, this simply isn’t the case. At a time when 75% of companies plan to embrace AI and other technologies by 2027, and businesses of all sizes and industries are now relying on computers more than ever before, computer science graduates can enjoy almost unbeatable job security.
Opportunities will continue to grow for people with good computing knowledge, whether that be in the obvious fields like software and web development, engineering, and AI development, or more niche sectors.
With so many options, you’re effectively guaranteed a long, rewarding career if you put in the necessary time and effort needed to establish a strong foundation of computing skills.
Rapidly Expanding and Evolving Industries
It’s no secret that the world of technology is a dynamic and fast-moving one. In the past 20 years alone, we’ve seen the proliferation of the internet, the rapid advancement of smartphones and wearable devices, the emergence of AI, and so much more.
In the years ahead, engineers and developers will continue to explore the boundaries of modern technology’s powers and potential, driving new innovations and improvements and opening more exciting job opportunities for those already established and experienced in this field.
Getting into computer science now could therefore provide a solid foundation for a career filled with excitement as you uncover and explore new ways of working with computers in fields as diverse as healthcare, finance, education, entertainment, manufacturing, logistics, and beyond.
Start Your Computer Science Career at OPIT
We’ve discussed some of the many benefits associated with careers in computer science, from the high starting salaries to the rapidly growing array of job options available to graduates. By now, you may be eager to follow this particular career path and take advantage of the wealth of opportunities.
If you’re wondering how to start, the Open Institute of Technology (OPIT) may hold the answers you need. As an exclusively online learning platform, specializing in computer science and digital business, and staffed by some of the world’s leading tech experts, OPIT is producing the tech leaders of tomorrow.
Some of the many advantages of learning with OPIT include:
- Accessible and flexible online education that matches your learning style and schedule
- Heavy focus on real-world applications of the skills you acquire
- An international community of like-minded students from around the globe
- A top team of tutors and lecturers from varying fields and industries
- Progressive assessment of skills and understanding – not constant exams
OPIT offers a small, curated selection of courses for those seeking to gain the technological skills and knowledge to succeed in their chosen areas of expertise. That includes a BSc (Hons) in Computer Science – a six-term program, worth 180 ECTS credits.
Numerous IT industry leaders and experts helped develop this fully accredited undergraduate degree, which is online and accessible to all. Like other OPIT courses, it offers a flexible learning program, with progressive assessments, fast-track options, and the opportunity to be part of a growing community of learners and tutors.
If the benefits of doing a career in computer science interest you, download the OPIT BSc in Computer Science brochure or fill out an online application today and take your first step toward a rewarding and fulfilling profession.
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