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M.S in Data Science @ Columbia University

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Current Courses:

  • Applied Deep Learning (COMS 4995 W 031)

  • Algorithms for Data Science (CSOR 4246 W 001)

  • Probability & Statistics for Data Analysis (STAT 5701 GR 002)

  • Exploratory Data Analysis (STAT 5702 GR 002)

B.S in Industrial Engineering
Minor in Computer Science
@ Purdue University

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Summary of the Relevant Courses:

1. Programming:

  • C Programming (CS 15900)

  • Object Oriented Programming  (CS18000)

  • Programming In C (CS 24000)

  • Computation In Indust Engr (IE 33200)

  • Information Systems (CS 348000)

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2. Data Structures & Algorithms:

  • Data Structures And Algorithms (CS 25100)

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3. Statistics:

  • Prob & Stat In Engr I (IE 23000)

  • Prob & Stat In Engr II (IE 33000)

  • Foundations Of Computer Science (CS 18200)

  • The Data Mine II (STAT 19000)

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  • 4. Machine Learning:

  • Intro Machine Learning & Apps (IE 49000)

  • *Computation In Indust Engr (IE 332) [Partially Covered]

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  • 5. Ethics in Data Science:

  • Ethics Of Data Science (PHIL 20800)

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  • 6. Operations & Research:

  • Stochastic Models (IE 33600)

  • Markov Chains​

  • Optimization Algorithms (IE 33500)

  • Linear Optimization and Optimization Algorithms​

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