⇒ Practical Application: Emphasize hands-on learning experiences, projects, and case studies to bridge the gap between theoretical concepts and real-world applications, fostering a strong foundation for problem-solving. ⇒ Professional Development: Offer programs and resources for continuous professional development, including workshops, seminars, and networking opportunities, to ensure students are well-prepared for the evolving landscape of data science. ⇒ Student can work as a Software Engineering, Data Scientist, Data Analyst, NLP Engineer, Robotics Engineer, Big data Engineer, Research Scientist, UI/UX designer, etc. ⇒ Helps you to recommend the right product to the right customer to enhance your business ⇒ You can perform sentiment analysis to gauge customer brand loyalty It enables you to take better and faster decisions |