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Python for Data Analysis and Scientific Computing

COMPSCI X433.3

17545604
Discover the power and flexibility of NumPy, SciPy and Matplotlib when dealing with heavy mathematical, engineering or scientific problems. Explore the concise and expressive use of Python’s advanced module features and apply them in probability, statistical testing, signal processing, financial forecasting and other applications. You study mathematical operations with array data structures, optimization, Probability Density Function, interpolation, fast Fourier transform, basic signal processing and other high-performance benefits.

Prerequisites:

Required

  • Proficiency in Python programming. Need to fulfill this prereq? Take a course in:
    • Programming Python COMPSCI X434
       
  • Knowledge of calculus. Need to fulfill this prereq? Take a course in:
    • Calculus I MATH X11

Course Outline

Expand or collapse section

Course Objectives

  • Solve more complex engineering, financial, mathematical and scientific problems.
  • Develop complex functions and scripts to perform complicated calculations and to visualize the results of these calculations.
  • Attain deeper understanding of the mathematical toolkit provided by the powerful core packages in this course.
  • Acquire in-depth hands-on experience.

What You Learn

  • NumPy
  • SciPy
  • Matplotlib
  • Operations with arrays and scalars
  • Indexing, slicing
  • Reductions
  • Broadcasting
  • Shape manipulation of arrays
  • Data sorting
  • Advanced data types
  • Type casting
  • Dealing with polynomials
  • Text and media files
  • Random numbers
  • Linear algebra operations
  • Input/Output
  • Fast Fourier transforms
  • Histograms
  • Probability density function
  • Interpolation
  • Signal processing

How You Learn

  • Lectures and in-class discussions
  • Homework problems

Is This Course Right for You?

This course is geared to those who need an introduction to numerical computing and visualization using the Python environment. Technical staff who want to enhance their Python programming skills can also benefit from this course. Engineers, scientists and software engineers who aspire to become Python power users will gain a suite of knowledge tips.

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Summer 2025 enrollment opens on March 17!

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Notes

Departmental contact: extension-techeng@berkeley.edu

Instructional Types

Live Online
Live Online courses provide an interactive learning experience with scheduled synchronous online sessions held via Zoom video conferencing (Pacific Time). Learn more about the Live Online format.
Online, Start Anytime
Continuous enrollment course begins when you enroll. You have a minimum of 90 days and a maximum of 180 days to complete the course.
Online, Fixed Date
Enroll in this course by its start date and complete it by its specified end date. There are no live sessions, but plenty of opportunities to collaborate with your classmates and instructor.
Classroom
Take classes in-person at one of our buildings or partner locations.

English Language Proficiency Requirements

All of our courses are taught in English. If English is not your first language, please use the following test scores as guides in order to be successful:

  • TOEFL: 90
  • IELTS Academic Format: 7
  • DAAD: C1
  • TEM-4 or TEM-8: Level 70
  • Duolingo: 125

Note: You do not need to submit test scores.

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