45 Data Science Preparatory Programs in USA

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.

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

We live in a world increasingly driven by data. Data science is a rapidly expanding, multidisciplinary field that draws on statistics, computer science and math, with applications in a wide variety of academic disciplines and industries. We extract meaning from data to learn more about the world and society. The data science minor allows students to complement discipline-specific skills and knowledge with a deeper understanding of how to analyze and extract meaning from data to learn more about the world, society and their discipline. We prepare students to be excellent data analysts in their major disciplines and to be prepared to effectively work with data after graduation.

Students in the data science certificate will develop abilities such as data management, reproducibility, modeling strategies, and ethical considerations of data science to be paired with their knowledge gained from their major or domain area. The certificate is a great fit for students who like programming, want to learn data analysis, and seek to be high-end users of data science tools in domain areas. Data science is one of the fastest growing career sectors in Wisconsin and across the nation.

A minor in Data Science complements various majors and provides students with valuable skills in data analysis, programming, statistical modeling, and machine learning. Here are key aspects and benefits of pursuing a minor in Data Science: Foundational Data Skills: Data Analysis: Students learn how to collect, clean, preprocess, and analyze data using tools and techniques such as spreadsheets, databases, data visualization, and statistical analysis.

Data science is an emerging and exciting field that seeks to find patterns and trends in the enormous amount of data that is collected every day. Data science is used to provide professionals important insights to make critical decisions in all areas of life, including business, government, healthcare, sports and more. According to US News and World Report, GlassDoor, LinkedIn, and other job reporting organizations, the position “data scientist” is consistently ranked as one of the best jobs. These rankings consider attributes such as pay, upward mobility, and positive work-life balance. At Franklin, the data science program prepares our students for this challenging and rewarding career.

Data is everywhere. It is in every field, behind every decision by politicians, scientists, economists, etc. Modern Data Science is being used to not only understand the plethora of data that has already been collected, but also to create new data in a myriad of forms, including visual (e.g. new art forms) and audible. Data Science now includes such varied techniques as sentiment analysis of text, image recognition, word prediction, and topic modeling. Applications of Data Science are now inescapable: they range from almost every smartphone app that we use, to policy decisions of our government. It is not an overstatement to say that an understanding of Data Science is necessary for a true understanding of the way our modern world works.

The Data Science Foundations certificate program is designed to give students a solid grasp of core concepts in data science. It covers essential topics such as data analysis, machine learning, and da...