Hello there! Recently, we had the pleasure of talking to Aleksandra Gjinovska, Head of Technology at IT Labs, in order to gain a deeper understanding of AI, and the opportunities and challenges it brings to the future. Enjoy reading our interview with Aleksandra and learn why including AI in your professional development is the right choice!
1. What is artificial intelligence and how does it differ from traditional computer programs?
– What are the basic components and principles of AI? How is intelligent behavior achieved in systems using AI?
AI and traditional computer programs are 2 different methods for solving problems in the field of computer science. Traditional computer programs execute explicit instructions and are used in web application development, data processing and software development. Traditional computer programs have played a significant role in the process of digitalization of different business processes and streams. But the main limitation of traditional programming is that it is deterministic and can only solve problems that it is specifically programmed to handle, meaning that every change in the business model should be reflected in enhancing the code with additional instructions to reflect the business flow.
On the other hand, artificial intelligence harnesses machine learning, neural networks, natural language processing to simulate human-like reasoning, enabling it to adapt, learn and improve, while making context-aware decisions. The main engine of AI is the data. Massive amounts of data, in speech, text or image form, are collected and applied to mathematical models, or algorithms, to recognize patterns and make predictions in a process known as training.
Artificial intelligence aims to provide machines with similar processing and analysis capabilities to humans.
2. What are the most significant benefits that artificial intelligence offers in the IT world?
– Which industries use AI technology the most? How can AI help solve complex problems and automate processes?
AI is pushing the known limitations of machine-enabled functionalities. This cutting-edge technology enables machines to act with a degree of autonomy, which results in effective execution of iterative tasks. By automating the repetitive and time-consuming tasks, without the need for human interaction, a significant increase in efficiency is achieved. With the adoption of predictive analytics and maintenance, AI helps in optimization of operations and processes, while reducing cost and time, as seen in supply chain management and energy consumption. Predictive analytics is particularly valuable in industries like healthcare, finance, marketing, and advertising where, with the adoption of sentiment analysis, user’s behavior can be predicted, and customer satisfaction can be improved. A great example of adopting AI technologies, are Netflix, YouTube, Tik Tok, Spotify with their personalized recommendation systems.
With the recent introduction of Generative AI and the ability to generate brand new content, in the form of text, images, music and even code – the impact was seen in multiple industries like marketing and Advertising, pharmaceutical – speeding the discovery drug process, fashion, and education – with personalized learning materials based on the individual cognitive skills and progress.
3. What can be expected from artificial intelligence in the future?
– What are the most promising directions for the development of AI? What new AI technologies or applications might we see in the next 5-10 years?
Artificial intelligence holds significant importance due to its transformative impact on various aspects of our lives. It has already revolutionized how we work, live, and engage in activities.
The pace at which Generative AI is being developed is extremely fast, so the expectations are that the adoption of Gen AI in multiple industries will happen sooner rather than later. AI is expected to revolutionize healthcare by making true personalized treatment. Advances in AI will likely continue to help in the development of autonomous vehicles. AI in education will change the way humans of all ages learn. Banks and financial institutions will leverage AI even more for a range of applications like detecting fraud. AI is expected to play a crucial role in combating climate change by optimizing energy usage.
The integration of AI with quantum computing is expected to lead to breakthroughs in processing power and speed, while solving complex problems that are currently intractable for classical computers.
On the other hand, in front of us it is not only the potential of AI, but also the need for robust frameworks to manage social and ethical implications.
4. Is artificial intelligence currently the most attractive program in the IT world, and if so, why?
– What are the indicators that make AI so attractive to students and professionals? How does it compare to other IT trends such as blockchain or cyber security?
According to the World Economic Forum’s report, the future of Jobs Report 2023, most of the fastest growing roles reshaping the global workforce are technology-related roles. Artificial Intelligence and Machine Learning Specialists top the list of fastest growing jobs, followed by:
- Artificial Intelligence and Machine Learning Specialists – This role is at the forefront of technological innovation, with a projected growth rate of 39% through 2027. The rise of artificial intelligence is transforming various industries, creating a high demand for specialists who can develop and manage artificial intelligence systems
- Business Intelligence Analysts – With the explosion of data in every industry, the need for analysts who can interpret and use this data for strategic decisions is growing, with an expected increase of 32%.
- Information Security Analysts – As cyber threats become more sophisticated, demand for information security professionals is expected to grow by 31%, making it a critical role in protecting organizational data.
- Data analysts and scientists – These roles are expected to see a growth rate of 30% as organizations rely more on data-driven insights for their operations.
Even though the hype around AI might look familiar with some of the previous disruptive IT trends, like Blockchain, we can be sure that AI is here to stay. The advantage of AI and the diverse areas of AI, from computer vision, to NLP, deep learning – make it eligible for wide usage in a wide range of fields, from autonomous vehicles to healthcare diagnostics, to customers service and personalized recommendations.
The impact of AI is broad and transformative, enhancing automation, decision-making speed and accuracy, and personalization services. It is central to developing smarter systems that can learn and adapt over time.
5. Why is it good for students to choose an artificial intelligence program at a technology academy?
– What are the key skills and knowledge that students will acquire? How does the program prepare students for the labor market and future career opportunities?
By choosing one of the streams on the Growth Labs AI Academy, the students will have the possibility to acquire necessary skills and knowledge for one of the most demanding professions globally. Therefore, they will be able to be concurrent on the global job market. The curriculum is made to provide foundation knowledge about the concepts in mathematics like regression, statistics, data science and feature engineering, to prepare the data and find meaningful patterns. The program will be followed with practical hands-on projects where theoretical knowledge will be applied.
The curriculum is divided into 3 streams: Data Analysis, Data Engineering and ML/Data Science.
Following the data analysis stream, the students will gain skills for transforming raw data into impactful reporting and visualizations, that will lead to data driven decisions. By focusing on skills like Excel and utilizing tools like Python and Power BI.
The data engineering program is designed to teach students how to efficiently handle, process, and manage large sets of data. The program covers the fundamentals of data storage, data processing techniques, and the architectures used for efficient data retrieval and management. Students learn about the tools and technologies needed to build robust data pipelines, perform data integration, and ensure data quality and security. The goal is to prepare graduates to design and maintain systems that allow for effective data analysis, helping organizations make data-driven decisions.
The final stream will equip participants with skills and knowledge in machine learning, deep learning, natural language processing (NLP), large language models (LLMs), general AI, and computer vision. It will also cover practical business applications for these technologies.
