CHME 5649 — Numerical Strategies and Data Analytics for Chemical Sciences

4 semester hoursGraduateLectureusually offered: springtypical days: T/FBostonTraditional

Introduces a broad range of numerical methods for solving large-scale, data-driven problems that arise in chemical engineering, chemistry, biochemistry, and other chemical sciences. Offers students an opportunity to obtain a detailed understanding of the derivation, analysis, and use of these numerical methods and learn how these lay the foundations to machine learning techniques. Topics include numerical programming logic, linear and nonlinear algebraic equations, polynomial fitting, numerical calculus, optimization techniques, and large-scale data analysis. Applies to a broad field of chemical and biochemical sciences, where large-scale multivariate data analyses and pattern extraction are key components.

Prerequisites

• one of:
  • one of:
    • all of:
      • one of:
        • MATH 1341 (min D-)
        • MATH 21EM
      • one of:
        • MATH 1342 (min D-)
        • MATH 211M
    • all of:
      • one of:
        • MATH 2321 (min D-)
        • MATH 316M
      • one of:
        • MATH 2341 (min D-)
        • MATH 315M
  • graduate program admission

Offering history

Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.

Meeting times

Share of recent sections by weekday: M 0% · T 56% · W 0% · Th 44% · F 56%

Common patterns: TF (56% of sections), R (44% of sections) — in patterns, R means Thursday

Professors

Spring

• Srirupa Chakraborty (100% of students) · reviews

Percentages are each professor's average share of the season's enrolled students in recent terms.

Links

Official catalog (CHME course descriptions) · Student reviews on RateMyHusky · All CHME courses · Plan it at numap.app