It seems that the field of data science can overwhelm many students. With so many YouTube tutorials, free resources, and courses on machine learning, statistics, and Python, many beginners become passive learners watching others' work or reading articles on the topic. However, when entering a highly competitive American labor market, employers from Silicon Valley to…
Software engineering, in general, is experiencing one of the most massive changes in the history of the field. After the transition from punched cards to compiler languages, this domain saw another tremendous leap forward that is being driven by transformers, large language models, and agentic computing technologies. Contrary to the common vision of a programmer…
Machine Learning (ML) used to be the subject for niche academic mathematicians alone. Today, however, machine learning algorithms power a significant proportion of global companies' business operations – from fintechs using ML predictions for managing risks and spotting investment opportunities, through supply chain companies relying on machine learning to optimize logistics processes, to medical establishments…
The field of software engineering is witnessing its most dramatic change since the advent of the internet age. The era of utilizing artificial intelligence (AI) as mere advanced autocomplete inside a text editor is finally dead. Among software engineers in the United States tech industry, the entire workflow has shifted to autonomous agents and agentic…
Today, in the world dominated by digital technologies, such buzzwords as "Artificial Intelligence" and "Machine Learning" are actively used during the presentations and commercials of US companies' boards, in articles from the press. Usually, people use them interchangeably when referring to any kind of innovative technologies. This, however, is a serious misconception of the actual…
The current technology scene is experiencing a revolution of sorts. With AI automating an increasing amount of boilerplate coding, what is in demand in today's environment is solely the ability to optimize, scale up, and enhance data processing efficiency. In this regard, companies do not want to hire people who know how to use programming…
The era of mobile app development being constrained by the limitations of static programming has finally ended. Due to enormous innovations in the hardware sector and the emergence of highly specialized mobile processing chipsets, as well as the widespread popularity of multiple-service digital ecosystems, the standards required for successful mobile apps have shifted. In the…
Launching into the realm of mobile app development is a thrilling experience with vast potential. In the competitive mobile market of the US, tens of millions of applications battle for attention. While the modern technological advancements make it easier than ever to create an application, a great number of them fail in their first year…
Being able to create a mobile application that is fast, beautiful, and easy-to-use is indeed a huge achievement. But taking it beyond a mere piece of software, turning it into a sustainable business that generates income requires a carefully thought-out monetization strategy. And, according to the North American mobile market conditions, the customers there are…
The mobile development industry landscape is changing fast. The rise of cross-platform programming frameworks, the emergence of on-device AI capabilities, and the growing importance of high-performance user interfaces have made the selection of the right language to use a fundamental architecture decision. In US-based tech companies, the choice is no longer between iOS or Android…

