The "Statistics for Data Science" value-added course successfully equipped participants with a strong foundation in statistical techniques and their practical applications in data science. By the end of the course, learners gained a deeper understanding of key concepts such as probability distributions, hypothesis testing, regression analysis, and data visualization, which they applied to real-world datasets through hands-on exercises and projects. Participants were able to effectively analyze, interpret, and draw meaningful insights from data, enhancing their ability to build predictive models and make data-driven decisions. The course not only strengthened their statistical knowledge but also improved their confidence in using tools like Python and R for data analysis, empowering them to pursue careers in data science or enhance their current professional roles.
KPRIET – An AI Integrated Campus
Preparing future-ready engineers with AI-integrated teaching and learning. KPRIET integrates Artificial Intelligence across teaching, learning, research and innovation to create a smarter, future-ready campus experience for students and faculty.
