SRM University (SRMUH) 
Data Science and Artificial Intelligence (AI) are two of the most rapidly growing fields in today’s technology-driven world. The global Artificial Intelligence market is expected to reach $266.92 billion by 2027, growing at a CAGR of 33.2% from 2020 to 2027, as per Allied Market Research. Not only this, the global big data market is expected to grow from $138.9 billion in 2020 to $229.4 billion by 2025, at a CAGR of 10.6%, as per MarketsandMarkets.
The numbers are big indeed, no two ways about that!
Though these two different arenas seem different from each other, would you believe if we say that these fields are intertwined and have a strong connection? In this blog, we will explore the connection between Data Science and Artificial Intelligence and provide aspiring students with an overview of how these fields are related.
What is Data Science?
Data Science is a multidisciplinary field that involves the extraction of insights and knowledge from structured and unstructured data. It encompasses a range of techniques, tools, and methodologies from various fields such as statistics, mathematics, computer science, and information science. The goal of Data Science is to identify patterns, trends, and insights from data and use them to solve complex problems in various domains.
What is Artificial Intelligence?
Artificial Intelligence is the development of computer systems that can perform tasks that typically require human intelligence. These systems can learn, reason, and make decisions using algorithms and machine learning models. AI systems can also interact with the environment and perform complex tasks with minimal human intervention.
The Connection between Data Science and Artificial Intelligence
Data Science and Artificial Intelligence are closely related, and one can argue that Data Science is the backbone of AI. AI systems require data to learn, reason, and make decisions. Without data, AI systems cannot operate, and this is where Data Science comes in. Data Science provides the tools and techniques to collect, process, and analyze data, which is then used to train AI models.
In other words, Data Science is responsible for preparing the data for AI models. It involves tasks such as data cleaning, data preprocessing, feature selection, and feature engineering, which are essential for building accurate and robust AI models. Data Science also plays a critical role in evaluating and testing AI models to ensure that they are effective and reliable.
The relationship between Data Science and AI is bidirectional. AI can also be used to enhance the capabilities of Data Science. For example, AI models can be used to automate data processing and analysis, enabling Data Scientists to focus on more complex tasks.
SRM University, Delhi-NCR- The Centre For A Futuristic Career
The B.Tech CSE programme with AI and Data Science specializations from SRM University, Sonepat offers an unparalleled opportunity for students to become the next generation of tech leaders. With course collaboration with IBM, Xebia and other renowned names, the cutting-edge curriculum, state-of-the-art facilities, and expert faculty, students are equipped with the knowledge and skills needed to tackle the most complex challenges in AI and Data Science.
One unique aspect of the programme is its focus on innovation and entrepreneurship. Students are encouraged to develop their own AI and Data Science solutions and turn them into viable businesses. The university provides ample support for aspiring entrepreneurs, with access to mentors, incubation centres, and funding opportunities.
Moreover, the programme at the best university in Delhi NCR offers international exposure and collaboration opportunities with leading universities and research institutions around the world. This allows students to gain a global perspective and collaborate with peers from diverse backgrounds, preparing them to excel in the global marketplace.
SRM University Sonepat also offers industry-focused projects, internships, and placements, giving students practical experience working on real-world problems in collaboration with leading companies. The university has established partnerships with major tech companies, enabling students to work on cutting-edge projects and gain valuable industry experience.
In addition to the academic curriculum, students are encouraged to participate in extracurricular activities such as hackathons, coding competitions, and conferences. These events provide opportunities for students to showcase their skills, network with peers, and learn from experts in the field.
Final Say
As these fields of AI and data science continue to grow and evolve, the connection between them will become even more critical, and students who master both fields will be well-positioned for success in their careers.
