General Introduction to Data Science

This lecture provides a general introduction to Data Science, covering topics such as Python, Numpy, Pandas, Matplotlib, and Scikit-learn. It also includes an overview of the lab structure, assessment methods, and the team involved. The course is designed as a hands-on journey with practical exercises, group work, and multiple instructors per session. The lab modules cover various aspects of Data Science, including Python, distributed data wrangling, machine learning with Apache Spark, real-time data processing, and collaborative data science. The assessment includes continuous evaluation during the semester and a final project presentation.