Applied Data Science Course

This course is designed for applicants who have a foundation in programming and statistical analysis and are keen to learn about data science, machine learning techniques, and predictive analytics. The course is structured around a project-based learning approach, where trainees will have the opportunity to work on real-world projects related to machine learning and predictive analytics.

Python will be the programming language of choice for this course, and the trainees will learn how to use Python to design, develop, and implement machine learning algorithms. They will also learn about the essential concepts of machine learning, such as data preparation techniques, feature engineering techniques, supervised and unsupervised algorithms, and building and validating regression, decision tree, clustering, and classification models.

Additionally, students will also have the chance to participate in data analytics hackathons, which will enable them to put their newly acquired skills to the test by solving real-world problems using data engineering techniques. They will also be able to conduct research in related fields and present their findings in a seminar.