Data Science Ph.D Program

Prerequisites: TIM 8500

Tools and Languages: R programming and R studio

Machine Learning methods will be introduced

Prerequisites: TIM 8501

Tools and Languages: R programming and R studio

Traditional Methods for Statistical Modeling in Data Science

Prerequisites: TIM 8521

Tools and Languages: Python programming and Jupyter Notebooks

Machine Learning Regressors are covered

Prerequisites: TIM 8555

Tools and Languages: SQL Language

Relational Databases and implemented databases

Prerequisites: TIM 7020

Tools and Languages: SQL Language

Prerequisites: TIM 8555

Tools and Languages: Python or R programming

Machine Learning methods and theory, Introduction to Neural Networks

DDS 8515 Multivariate Analysis

Prerequisites: DDS 8536

DDS-8536: Advanced Data Science Techniques. 

This course is a crucial part of your journey through the Technology and Innovation Management specialization, preparing you to tackle real-world data challenges using advanced machine learning techniques. In this course, you will expand your ability to analyze complex data and make informed decisions, positioning you to lead in a data-driven world. The skills you'll gain here are critical for roles in industries such as finance, healthcare, marketing, and technology, where data science plays a transformative role. 

During this course, you will explore foundational and cutting-edge topics in data science, focusing on both theory and practical application. You’ll develop skills that will allow you to evaluate and implement advanced data analytics methods, ensuring you're equipped to handle the complexity of modern datasets. This course will build on the knowledge from earlier courses, pushing you to apply these techniques in more sophisticated ways. 

Prerequisites: TIM 8131

Prerequisites: DDS 8536

Prerequisites: DDS 8150

Prerequisites: 8510

Prerequisites: TIM 7211

Prerequisites: DDS 7250

Prerequisites: DDS 7255

Prerequisites: ALL Core and Research courses completed.