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Students who are proficient in object oriented programming will complete 12 units of foundation coursework, 12 units of advanced coursework and the synthetic capstone course.Students who are not proficient in object oriented programming will be required to complete the Python for Data Science foundation course as part of their 15 units of foundation coursework, 9 units of advanced coursework and the synthetic capstone course.

Capstone Course

Students will complete a capstone by executing a culminating project that integrates the core skills and concepts learned throughout the program. The capstone combines the technical, analytical, interpretive, and social dimensions required to design and execute a full data science project. Students will learn integral skills that prepare them for long-term professional success in the field.

Data science as a field is interdisciplinary and is about the scientific approach in processing large data requirements. It involves several scientific techniques and theories that have been derived from various fields such as statistics, mathematics, information science, computer science, and domain knowledge.

Data democratization is transforming our world in a fundamental way. Every industry as well as governments around the world are acting on a wide variety of data sources. Businesses have undergone major transformations with insights and predictions powered by data.The aforementioned changes led to the requirement for data science professionals across various industry verticals that had rapidly shifted. Businesses are having to rethink hiring, training, and partnerships. The latest demand is for a group of professionals who are skilled in data, analytics, machine learning, and artificial intelligence.These days, data science may seem like a highly employable and appealing profession. However, instead of looking at whats trendy, it is essential to have a deep understanding of the shifting demands of the current job market.

Data Science Course Eligibility

To be able to meet the explosive demand for data scientists, higher education needs to be nimble and responsive while certifications, graduations, and executive-level programs have to be responsive to the requirements of the workforce.So, who can learn data science? The answer is simple, anyone who is willing to learn data science, be it a newcomer or an experienced professional. Engineers, software and IT professionals, and marketing professionals alike can sign up for part-time or external data science programs. Now, lets take a look at the eligibility for data science courses.

To take regular courses in data science, knowledge of basic high-school-level subjects are the minimum requirement. As data science is, loosely, an amalgamation of the concepts derived from computer science, mathematics, and statistics, learners should aspire to, first, earn a degree in one of the STEM (science, technology, engineering, and mathematics) backgrounds.Studying computer programming in high school can benefit you in the future while pursuing data science. this course can be tracked with keyword like "data science and bi training or data science and machine learning" .Based on the subject knowledge in programming, statistics, or machine learning, learners become experts in the practical implementations of data science methodologies.

Individuals from other streams, such as business studies, can study pertinent courses in data science. Likewise, anyone with a degree in business administration, such as a BBA or MBA, is also eligible for higher studies in the data science domain. These professionals can go on to work in the capacity of executives and be responsible for generating customer relationship management (CRM) reports, business-related data quality assessment (DQA), and management information system (MIS).