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Instructor-led Classroom Adult Training in Singapore - Modular Fast Track Skill-Based Trainings

NumPy and SciPy Essential Training

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

  1. Numpy
  2. Matplotlib
  3. Scipy
  4. SciPy Optmization Module
  5. SciPy Linear Algebra Module
  6. SciPy Statistics Module
  7. SciPY Signal Processing Module
  8. SciPY Image Processing Module

After your registered for the course, you can apply SSG grants below

Click here to apply SkillsFuture Credit for Individual

Click here to apply WSG Absentee Payroll for Company
Course Code: CRS-N-0031884

Course Booking

$298.00 (GST-exclusive)

Course Date

Course Time

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Course Cancellation/Reschedule Policy

We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
Note the venue of the training is subject to changes due to class size and availability of the classroom.
Note the minimal class size to start a class is 3 Pax.

Training Grant and Subsidy

All Singaporeans aged 25 and above can use their $500 SkillsFuture Credit from the government to pay for a wide range of approved skills-related courses. Visit the SkillsFuture Credit website to choose from the courses available on the SkillsFuture Credit course directory

Course Details

Module 1 Basics of Numpy

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

Module 2 Numerical Analysis 

  • Curve Fitting
  • Finding Roots
  • Interpolation
  • Integration
  • ODE

Module 3 Linear Algebra 

  • Matrix Operations
  • Matrix Solve 
  • Eigenvalues
  • Matrix Decomposition

Module 4 Statistics

  • Basic Statistics
  • t-test for one sample
  • t-test comparison for 2 samples

Module 5 Signal Processing

  • Waveforms
  • Fast Fourier Transform (FFT)
  • FFT Windowing

Module 6 Image Processing (Optional)

Who Should Attend

This course is for the Scientists, Engineers, Programmers, or Analysts looking for a high-quality, open source mathematical library.



This is a intermediate level course. The following prerequisite is assumed

  • Basic Python

Software Requirement

Pls download and install the following software prior to the class


Numpy SciPy TrainerDr. Alfred Ang is the founder of Tertiary Courses. He is a serial entrepreneur. He founded OSWeb2Design Singapore Pte Ltd in 2007 offering web development, e-commerce store development, graphics design, ebook publishing, mobile apps development, and digital marketing services. He established the first online gardening store in Singapore, Eco City Hydroponics Pte Ltd in 2000, offering a wide range of gardening products such as seeds, plant nutrients, hydroponics kits etc. Eco City Hydroponics has become the most popular and successful gardening store in Singapore. He founded Tertiary Infotech Pte Ltd in 2012 and transformed the business to a training platform, Tertiary Courses in 2014. Tertiary Courses offers a wide range of SkillsFuture courses for PMETs to upgrade their skills and knowledge. He also established Tertiary Courses Malaysia in 2016. He also founded Tertiary Robotics in 2015 offering Arduino, Raspberry Pi, Microbit and Robotics products

Dr. Alfred Ang earned his Ph.D. from National University of Singapore in 2000, majoring in Electrical and Electronics Engineering. He also completed an online MBA course with U21 Global based in Australia. He obtained his B.Sc (Hons) from National University of Singapore in 1992, majoring in Physics. He topped his Physics cohort for 3 consecutive years and funded his degree study with Book price, awards and tuition. He has worked in Defence, Electronics and Semiconductor Industries. His current interests include Machine Learning, Deep Learning, Artificial Intelligence, Internet of Things, Robotics and Programming.

Dr. Alfred Ang was Distinguished Toastmasters (DTM) and Senior Member of IEEE. He has published more than 20 peer reviewed papers and co-inventors for more than 20 inventions.

Numpy SciPy TrainerJoel Foo graduated with a major in statistics and minor in computer science from NUS. He is well-versed in R and Python libraries/packages and has applied knowledge of statistics in data mining, time series analysis and deep learning. As the Business Intelligence Lead in an Israeli startup, Joel has experience in using BI tools such as Tableau to perform drill downs and harness insights from data. Currently, he is the co-founder and CEO of Geboto, a chatbot centric CRM platform for hospitality and F&B.

Numpy TrainerDewin Goh is a current MSc student of Georgia Tech University (Computer Science) and holds a Bachelors of Accounting (Honours with Distinction) under NUS. Having over two years of working experience in Data Science in both Silicon Valley and Singapore-based companies, he commands a broad understanding of the big data & machine learning stack, along with the knowledge and experience of productionizing models at scale. Presently, he works as a Data Engineer at Grab. Core competencies include but are not limited to: Python, Numpy/Scipy/Scikit-learn, Tensorflow, Apache Spark & Kafka.

Numpy SciPy TrainerMarcus Lee has his degree in Computer Science and a background in Statistics from the University of Otago. Before returning to Singapore, he analysed vacation data provided by the New Zealand Board of Tourism to determine the favourite activities of Australian, Japanese, and German tourists in New Zealand. In addition to a vast number of other demographics statistics, he has been able to provide significant advice to the board on how to promote tourism in New Zealand. His core specialization skills are Java, R, Statistical Analysis, Machine Learning, NumPy, Scikit, and Network Management. He has also a fair amount of experience in C, C++, and Python.

Numpy SciPy TrainerPushparaj Murugan has more than five years of research experiences in Industrial automation. He is specialized in Python libraries such as NumPy, Pandas, Matplotlib, Seaborn, SciKit-Learn, Tensorflow, Keras, Theano, etc. He had his experience working for Caterpiller inc. in developing a user interface using Matlab programming combining finite element analysis. In addition, he also worked for ARDB (Aeronautical Research and Development Board) and DRDO ( Defence Research and Development Organisation) in India on various research projects. He is currently doing his research at Nanyang technological university for Rolls Royce intelligence manufacturing section. He is working on automation of robotic abrasive belt grinding process using deep learning frameworks such as CNN and LSTM.

Numpy SciPy TrainerDr. 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.

Numpy SciPy TrainerMing Liang is an up-and-coming developer with expertise ranging from deep learning to hardware like the raspberry pi. He specialises mostly in the area of data science and machine learning and has won several hackathons and is ranked highly in international competitions. Furthermore, he has also done projects as part of the maker community in Singapore and build his own 3D printer as well

Customer Reviews (4)

Will RecommendReview by Benson Dannie Joseph
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
More hands on practice

Instructor was knowledgeable and explained concepts in a way easy to understand (Posted on 12/20/2018)
Will RecommendReview by Ryan
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
I feel that there's a slight mismatch between the time allocated for the course and the course material. However, Joel was succinct and clear on his points that helped with my understanding. (Posted on 7/28/2018)
Great trainer and sessionReview by Ryan
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Trainer Joel was clear and succinct which made the understanding a lot faster. I feel that this is especially important due to the long list of subjects.

This course covers some basic math in codes, but was still slightly challenging for rusty peeps like me. However, Joel helped me to understand the fundamentals quickly which set a good platform for the advanced concepts.

Highly recommend to check this course out if you are doing data analytics on Python.

(Posted on 7/28/2018)
Will recommendReview by Lee Jiahe Steven
1. Do you find the course meet your expectation?
2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
Nil (Posted on 7/15/2016)

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