NumPy and SciPy Essential

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Tertiary Courses 170 Upper Bukit Timah Road #05-23, #05-22, #05-19 Bukit Timah Shopping Centre Singapore 588179, Singapore, Singapore, Singapore 588179

SGD 298.00

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SkillsFuture Course - NumPy and SciPy Essential

NumPy is an open-source extension to Python that adds support for multidimensional arrays of large sizes. This support allows the desired acquisition, storage, and complex manipulation of data mentioned previously. NumPy alone is a great tool to solve many numerical computations. On top of NumPy, another open-source library to Python is SciPy. This library contains algorithms and mathematical tools to manipulate NumPy objects, with very definite scientific and engineering objectives. The combination of Python, NumPy, and SciPy has been the environment of choice of many applied mathematicians for years.

This course will covers the following topics

Numpy
Matplotlib
Scipy
SciPy Optmization Module
SciPy Linear Algebra Module
SciPy Statistics Module
SciPY Signal Processing Module
SciPY Image Processing Module

Outline

Module 1 Get Ready

Overview of SciPy Stack
Installing SciPy Stack

Module 2 Numpy

Array Creation
Array Operations
Indexing & Slicing
Shape Manipulation
Polynomial
Linear Algebra
Statistics

Module 3 Matplotlib

What is Matplotlib
Gallery
Create Plots
Colors, Markers, Line Styles
Grid Lines
Axis Labels and Title
Legend
Subplots
Other Plots
Read and show image
Pseudocolor
Grayscale

Module 4 Scipy for Numerical Analysis

SciPy Optimize Module
Curve Fitting
Finding Roots
Interpolation
Integration
ODE

Module 5 SciPy for Linear Algebra

SciPy Linear Algebra Module
Matrix Operations
Matrix Solve
Eigenvalues
Matrix Decomposition

Module 6 Scipy for Statistics

Scipy Stats Module
Basic Stats
Probability Distribution Functions
t-test for one sample
t-test comparison for 2 samples

Module 8 Scipy for Signal Processing

Scipy Signal Module
Waveforms
Fast Fourier Transform (FFT)
FFT Windowing

Module 9 Scipy for Image Processing (Optional)

Speaker/s

Dr. Cao Yongxin (Steve) has more than five years of solid industrial and research experiences in data analytics. He held PdD on operations research in National University of Singapore. After his Phd study, he worked as data analyst and scientist in manufacturing and commodity trading companies. He is specialized in analyzing, visualizing and mining complex time series data using Python tools sucha as Pandas, Numpy, Matplotlib, SK-Learn, Tensorflow etc. He did research on predictive analytics on various systems e.g., Forex and commodity trading, system performance prediction, machine maintenance, etc. Besides data analytics using Python, he also extended his expertise in Microsoft Excel VBA, Hadoop big data platforms such as AWS and Microsoft Azure. In addition, he is strong in mathematical modelling and has cross-disciplinary domain knowledge in operations research, currency and commodity trading and industrial automation.

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