Program M.S. in Data Analytics and Visualization Katz School of Science and Health Yeshiva University

M.S. in Data Analytics and Visualization

Amerika Serikat

5

Apa yang akan saya pelajari?

Organizations are collecting more data than ever - and acting on less of it. Executives face dashboards they don't trust and AI-generated summaries they can't evaluate, and they need analysts who don't just produce analysis but know how to drive decisions with it. A flawed forecast shapes a budget. A misleading visualization drives a product decision that takes a year to unwind. The Katz School's master's in data analytics prepares you to be the analyst organizations depend on, someone who finds the signal in complex data, builds analytics that hold up under scrutiny, and communicates with clarity and credibility. You'll develop the analytical and visual intelligence that drives consequential decisions at every level of an organization. You'll interrogate complex datasets, build and validate predictive models, architect analytics pipelines, design compelling visualizations, and present findings to technical and executive audiences alike. Along the way, you'll build technical fluency across Python, SQL/NoSQL, Tableau, Power BI, and cloud and Lakehouse platforms including AWS, Snowflake, and Databricks - and the judgment to know not just how to run an analysis, but which one will matter most.

Saya termasuk departemen apa?

Katz School of Science and Health

Pilihan kuliah

Purna Waktu (21 bulan)

Biaya kuliah
US$24.771,43 (Rp 388.168.288) per tahun
Registration Fee Per Semester: $65
Tanggal mulai

Januari 2027

Tempat

Beren Campus

245 Lexington Avenue,

New York,

10016, Northeast, United States

Purna Waktu (21 bulan)

Biaya kuliah
US$24.771,43 (Rp 388.168.288) per tahun
Registration Fee Per Semester: $65
Tanggal mulai

Januari 2027

Tempat

Wilf Campus

500 West 185th Street,

New York,

10033, Northeast, United States

Persyaratan masuk

Untuk mahasiswa internasional

Bachelors degree - with typical majors in computer science, data science, engineering, physics, mathematics, statistics and quantitative sciences as well as economics, finance, psychology with prerequisites. Prerequisites - one university course in each of the following: high-level programming, probability and statistics/statistics and calculus.

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