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Berkeley Global
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
- 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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Fall enrollment opens on June 20!