Data Science is the future of Artificial Intelligence. As the world entered the era of big data, handling it was the main challenge and concern for the enterprise industries until 2010. All the ideas which you see in Hollywood sci-fi movies can actually turn into reality by Data Science. Unlike data in the traditional systems which was mostly structured, today most of the data is unstructured or semi-structured. A Data Scientist, according to Harvard Business Review, “is a high-ranking professional with the training and curiosity to make discoveries in the world of Big Data”. Therefore it comes as no surprise that Data Scientists are coveted professionals in the Data Analytics and IT industry. With experts predicting that 40 zettabytes of data will be in existence by 2020, Data Science career opportunities will only shoot through the roof! Shortage of skilled professionals in a world which is increasingly turning to data for decision making has also led to the huge demand for Data Scientists in start-ups as well as well-established companies. More than 50,000 jobs in the Data Science and Machine Learning are lying vacant in India, for lack of skilled professionals. A McKinsey Global Institute study states that by 2019, the US alone will face a shortage of about 190,000 professionals with deep analytical skills. To meet this need of the hour The NorthCap University is stepping towards inculcating the required skills in our students to be the future Data Scientist, Data Engineer or Business Analyst.
Learning outcomes of this track:
- To extract, transform and load data and use visualization techniques to derive actionable insights to positively influence a desirable outcome
- To utilize statistical methods in the data driven decision making process
- To use statistical methods to develop and maintain predictive models
- To process large amounts of data using big data technologies
- To leverage BI tools to develop business data processing and visualization pipelines
- To create predictive models using AI and Machine Learning techniques
- Data Analyst
- Data Engineers
- Machine Learning Engineer
- Data Scientist
- Data Architect
- Business Data Analyst
- Data and Analytics Manager
Programme Educational Objectives (PEOs)
- To provide technical expertise in Computer Science & Engineering and infuse soft skills in our students to facilitate them professionally.
- To transform graduates into industry-ready professionals and competent researchers.
- To imbibe high standard of ethical and professional conduct, positive attitude, team spirit and societal responsibilities.
- To up skill our students and tune them for performing efficiently in various roles of their social, professional and ethical obligations.
Programme Outcome (POs)
- Scholarship of Knowledge: Acquire in-depth knowledge of specific discipline or professional area, including wider and global perspective, with an ability to discriminate, evaluate, analyse and synthesise existing and new knowledge, and integration of the same for enhancement of knowledge.
- Critical Thinking: Analyse complex engineering problems critically, apply independent judgement for synthesising information to make intellectual and/or creative advances for conducting research in a wider theoretical, practical and policy context.
- Problem Solving: Think laterally and originally, conceptualise and solve engineering problems, evaluate a wide range of potential solutions for those problems and arrive at feasible, optimal solutions after considering public health and safety, cultural, societal and environmental factors in the core areas of expertise.
- Research Skill: Extract information pertinent to unfamiliar problems through literature survey and experiments, apply appropriate research methodologies, techniques and tools, design, conduct experiments, analyse and interpret data, demonstrate higher order skill and view things in a broader perspective, contribute individually/in group(s) to the development of scientific/technological knowledge in one or more domains of engineering.
- Usage of Modern Tools: Create, select, learn and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modelling, to complex engineering activities with an understanding of the limitations.
- Collaborative and Multidisciplinary Work: Possess knowledge and understanding of group dynamics, recognise opportunities and contribute positively to collaborative-multidisciplinary scientific research, demonstrate a capacity for self-management and teamwork, decision-making based on open-mindedness, objectivity and rational analysis in order to achieve common goals and further the learning of themselves as well as others.
- Project Management and Finance: Demonstrate knowledge and understanding of engineering and management principles and apply the same to one’s own work, as a member and leader in a team, manage projects efficiently in respective disciplines and multidisciplinary environments after consideration of economical and financial factors.
- Communication: Communicate with the engineering community, and with society at large, regarding complex engineering activities confidently and effectively, such as, being able to comprehend and write effective reports and design documentation by adhering to appropriate standards, make effective presentations, and give and receive clear instructions.
- Life-long Learning: Recognise the need for, and have the preparation and ability to engage in life-long learning independently, with a high level of enthusiasm and commitment to improve knowledge and competence continuously.
- Ethical Practices and Social Responsibility: Acquire professional and intellectual integrity, professional code of conduct, ethics of research and scholarship, consideration of the impact of research outcomes on professional practices and an understanding of responsibility to contribute to the community for sustainable development of society.
- Independent and Reflective Learning: Observe and examine critically the outcomes of one’s actions and make corrective measures subsequently, and learn from mistakes without depending on external feedback.
Programme Specific Outcome
PSO 1 Acquire deep knowledge of Computer Science & Engineering with specialized areas of Data Science and Cyber Security.
PSO 2 Identify research areas and provide solutions to complex engineering problems for the advancement of society.
PSO 3 Enable the students for premium National/International jobs, pursue research career, entrepreneurship and to become responsible global citizens.