64 Data Science Preparatory Programs in USA

Harness analytics to make more informed investment decisions.

Data is everywhere—from e-commerce sales, app downloads to a smartphone, to supply chain management or bioinformatics or connected devices. And that massive increase in the amount and variety of data being collected is translating to an exponential growth in the computer power needed to process that data.

Data Science is continually ranked as one of the most in-demand professions. The need for professionals who can manage and leverage insights from data is clearer than ever before. The curriculum taught in this program is designed to meet the expanding multi-disciplinary needs of data professionals. By covering a wide array of topics, the program addresses the wide variety of skills needed to work on successful data-based projects. Topics covered include data-driven discovery and prediction, data engineering at scale (inspecting, cleaning, transforming, and modeling data), structured and unstructured data, computational statistics, pattern recognition, data mining, data visualization, databases, SQL, Python programming, and machine learning. UC Irvine’s 3-month post-graduate level Accelerated Certificate Program (ACP) in Data Science covers a wide array of topics in data science including data-driven discovery and prediction, data engineering at scale (inspecting, cleaning, transforming, and modeling data), structured and unstructured data, computational statistics, pattern recognition, data mining, data visualization, databases, SQL, Python, and machine learning.

The Certificate in Data Science is intended for students who possess a Bachelor of Science in a Science, Technology, Engineering, or Mathematics (STEM) field, but who lack sufficient background in Data Science to be admitted to the Master of Science in Data Science.

Data science is changing how we understand and study politics, policy, and decision-making. This course introduces students to the fundamental tools of data science, including collecting, modeling, and visualizing data, and how to apply these tools to study political and policy questions.

A hands-on introduction to the methods of principles of data science. Strategies for analyzing and visualizing tabular data, including common patterns and pitfalls. Data acquisition through web scraping and REST APIs. Core principles of machine learning: supervised vs. unsupervised learning, training vs. test error, hyperparameter tuning, and ensemble methods. Introduction to data of different shapes and sizes, including text, image, and geospatial data.

This program is of interest to anyone who wants to use the powerful capabilities of relational databases in conjunction with the new "Big Data" management frameworks for data storage and retrieval, and for data analysis in support of management decision-making. Data architects, data analysts, database administrators, and information technology staff members can all benefit from this program.

Machine Learning and Natural Language Processing define the current state of the art of Artificial Intelligence. These technologies, which are a form of data mining and data analysis, continuously learn from the provided information.

A Free Course On Data Visualization & Reporting In Microsoft Power BI - With Certificate.

Introduction to key concepts from calculus (differentiation and integration), probability (discrete and continuous random variables), and linear algebra (vector spaces, matrices, and linear systems).

Free Course On Designing And Implementing Monitoring And Evaluating (M&E) Systems.

Discrete and continuous time Markov chains, Poisson processes, random walks, branching processes, first passage times, recurrence and transience, stationary distributions. Non-Statistics master's students may want to consider taking STATS 215 instead.

The Technology Studies – Data Science Option associate degree program prepares students primarily to transfer to complete a B.S. degree in Data Science or Technology Management.

The data science minor is designed for students not majoring in Informatics, Computer Information Science, or Computer Science & Information Technology. Students will be exposed to information technology and data sciences disciplines, learn how to communicate technical information clearly and explain ethical norms regarding data management and analysis.

Data science extracts meaningful knowledge from large amounts of complex data by using scientific methods, statistics and computing tools. The data science major lives at the intersection of many fields. Cross-disciplinary by definition, this major is an exercise in integration, one that brings together technical skills and domain-specific knowledge to create new pathways for learning. The data science major will prepare you to face emerging questions and challenges in the communication of data concepts and outcomes. Offering rigorous training in statistics and computer science, the major emphasizes how to be an effective, ethical and judicious consumer of data.