Introduction to Data Science, Machine Learning and Deep Learning
AI has manifested itself in all areas of our lives and is one of the most exciting and fast-growing fields of research and application in the world of data science. This course will provide an overview of using R and Python for some of the most popular machine learning and deep learning models in real-world data science applications in the cloud environment. The sessions will step through the basic theoretical concepts behind those models and mainly focus on applications. You will learn the motivation and use cases of these models through hands-on exercises. This short course's main topics are: big data cloud environment, tree-based models, regularization methods, feedforward neural network, convolutional neural network, and recurrent neural network. This course is designed for audiences with a statistics education background, and it bridges the gap between traditional statisticians and data scientists. No software download or installation is needed, and everything is done through the internet browser with hands-on sessions in Databrick's cloud environment and Colab.