• Data science is an interdisciplinary field that aims to extract knowledge/insights from data in various forms, either structured or unstructured. Data science employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, operations research, information science, and computer science.
•  Data Science professionals are experts in mining data and creating algorithms to extract meaningful information from it, which can be used by businesses to enhance their products, streamline their production lines, implement new marketing strategies, venture confidently into new markets and so much more. 

• In recent years, demand for trained data analysts has witnessed an exponential growth. Data analysis is not only essential but indispensable for meeting the challenges of making most efficient strategic as well as tactical decisions. Applications of data science take place in various domains such as government sector, agriculture, atmospheric sciences, infrastructure management, financial markets, e-commerce.
• Many businesses have started realizing this power of data and are gunning towards becoming data-driven businesses, as these actionable insights saves huge amount of cost and time which results in higher profitability and efficiency.
• However, there is a huge gap between the demand and supply of quality data engineers and hence the popularity is growing at a higher rate. This demand has given rise to the emergence of Data Science training programs all across the globe. Although it has not been widely spread in the Asian markets, but it is soon to be the most coveted giving field there is.

• Programs offered by Trinity GAC are designed and executed in association the with industry i.e. the firms working in the Data Science domain. Hence these some of of the most comprehensive and state of the art programs in this domain. These programs are blend of academic rigour and significant industry exposure equipping learners with highly advanced conceptual knowledge and futuristic skill-sets.
• Our vision is to up-skill people on high-end technologies like Deep Learning, Machine Learning, Big Data and make them employable. Every domain of computing such as data analysis, software engineering, and artificial intelligence is going to be impacted by Data Science & AI. Therefore, every engineer, researcher, manager or scientist would be expected to know Data Science.

• The programs are conducted by well-known industry partners, researches and experts from leading industry and renowned R&D organizations. For this, Trinity has worked with Industry/ R&D partners in different domains, who collaborate and work with them in conducting the training programs. This also facilitates the interaction between beneficiaries and industry experts to enable collaboration and finding opportunities for parent institutions.

• Today’s world is highly dynamic w.r.t. abundance of data and multidisciplinary research. it thus burdens the decision maker to analyse data and take meaningful decisions. With the availability of various tools and user-friendly statistical software, the ability to analyse large amount of engineering data is not only desirable, but a necessity for any professional.
• With the emergence of digital data, data-driven decision making has now been an integral part of the efficient functioning of every organization, and more generally of society at large. The programs offered by Trinity GAC are designed to help working professionals to acquire essential skills and knowledge for asking the right questions, addressing them with analysis of the right kind of data, and finally drive the decisions with the insights gained from the analysis to drive decisions. The programs thus provides a framework for transforming data into insights that are coupled into an effective business decision making process. We strongly believe that this unique blended competency is the requirement in the Analytics profession today.
• Data-driven decision making is a defining hallmark of organizations in the 21^st century. Application of data analytics is promising creative and cost-effective solutions to traditionally intractable problems in wide areas spanning the private and public sectors. This rise of data analytics application in management practice is equally matched by an acute demand for skilled analytics professionals who can deliver state-of-the-art solutions to business problems.

• The AI industry market size is projected to be $266.92 billion by 2027 at a CAGR of 33.2%*. As modern organisations turn towards Machine Learning (ML) and Artificial Intelligence (AI) for responsive and automated business solutions, skilled talent that will help them harness the full potential of these technologies, are in high demand.
• In a recent article1 based on a survey of nearly 3000 executives, MIT Sloan Management Review reported that there is striking correlation between an organization’s analytics sophistication and its competitive performance. The biggest obstacle to adopting analytics is the lack of knowhow about using it to improve business performance. Business Analytics uses statistical, operations research and management tools to drive business performance.
• Companies such as Amazon, Google, HP, Netflix, Proctor and Gamble and Capital One uses analytics as competitive strategy. Business Analytics helps companies to find the most profitable customer and allows them to justify their marketing effort, especially when the competition is very high. From Netflix to Google, world-renowned companies have multiplied their business growth with Data Science and Machine Learning (ML) applications, guided by a data-driven approach to decision-making. According to Analytics Insight (2020), around 77% of devices that we presently use are utilizing ML.

• The scope of data analysis within business is limitless. From tracking customer behaviour and input prices, to simulating road traffic and competitors’ sale strategies, a skilled Data Scientist can contribute to the success of a business in many ways. Artificial Intelligence and Machine Learning are helping leaders make informed decision in board rooms. These decisions are disrupting the business environment and creating more opportunities in every industry and function.

Some of the key benefits of using analytics in businesses are:

• Improving the decision-making process (quality and relevance)
• Speeding up data-driven decision-making process
• Better alignment with firm strategy
• Realising cost efficiency
• Responding to user needs for availability of data on a timely basis
• Improving competitiveness
• Producing a single, unified view of enterprise information
• Synchronising financial and operational strategy
• Increasing revenues
• Sharing information with a wider audience

Top Business Applications of Machine Learning:

• eCommerce: Customer Support, Product Recommendation
• Healthcare: Drug Discovery, Disease Diagnosis
• BFSI: Algorithmic Trading, Portfolio Management
• Transport: Safety Monitoring, Air Traffic Control
• Heavy Engineering: Industry 4.0, Predictive Machine Analytics