Online or onsite, instructor-led live SciPy training courses demonstrate through interactive hands-on practice how to use SciPy to create advanced scientific computing functions with Python.
SciPy training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Singapore onsite live SciPy trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
SciPy is also known as Scientific Python.
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Testimonials
The notes given
Bertrand Chen, MINDEF
Course: Python Programming - 4 days
The virtual machines worked very well and make playing around with the code very easy. I also particularly liked having copies of all the examples being put together by the trainer to following with so I could see the end result in advance. Made it easier for me to ask more specific questions.
Stefan Kotze - Samantha Campbell, ACC
Course: Python Programming - 4 days
Trainer covered more in depth in every topic within the time given and also gave us questions to do and explained it whenever we had queries.
Praveent Thamil Mani - Bertrand Chen, MINDEF
Course: Python Programming - 4 days
Well-paced, sufficient break time so us to absorb the content
Bertrand Chen, MINDEF
Course: Python Programming - 4 days
It generated good discussion from the group
Samantha Campbell, ACC
Course: Python Programming - 4 days
Days 2 and 3. There was an absurd amount of content but Abhi handled it well, so I got real value there.
Michael Clews - Samantha Campbell, ACC
Course: Python Programming - 4 days
The trainer gave a clear and systematic teaching. He usually gave the reasoning and fundamental knowledge behind the commands. He also gave us time to do the exercises and practice.
Felicia Rezanda - Ong Lee Chiau, HP Singapore (Private) Ltd.
Course: Advanced Python - 4 Days
The trainer will illustrate the theory behind certain data structure behavior using Jamboard.
Ong Lee Chiau, HP Singapore (Private) Ltd.
Course: Advanced Python - 4 Days
The explaination
Wei Yang Teo - Ministry of Defence, Singapore
Course: Machine Learning with Python – 4 Days
The trainer took the time to answer all our questions.
Ministry of Defence, Singapore
Course: Machine Learning with Python – 4 Days
Trainer was very knowlegable and very open to feedback on what pace to go through the content and the topics we covered. I gained alot from the training and feel like I now have a good grasp of image manipulation and some techniques for building a good training set for an image classification problem.
Anthea King - WesCEF
Course: Computer Vision with Python
Apart from the content, I loved Abhi's flexibility to tweak the training based on our feedback
WesCEF
Course: Computer Vision with Python
The second day going through feature extraction was great fun. Trainer was very knowledgeable and engaging.
WesCEF
Course: Computer Vision with Python
Having some previous computer vision experience I found the second day covering feature extraction and CNNs most beneficial.
WesCEF
Course: Computer Vision with Python
Trainer was accommodative. And actually quite encouraging for me to take up the course.
Grace Goh - DBS Bank Ltd
Course: Python in Data Science
clear explanation with adequate examples.
Raphael Reynold - Bertrand Chen, MINDEF
Course: Python for Data Analysis
The trainer explains in simple terms for easier understanding of the subject.
Bertrand Chen, MINDEF
Course: Python for Data Analysis
Patience of the trainer while making sure everyone understand the lesson
Yeo Yu Xin - Ministry of Defence, Singapore
Course: Python for Data Analysis
It's very hands-on and I can follow despite the lack of calculus background.
Wei Pin Ho - Ministry of Defence, Singapore
Course: Python for Data Analysis
Very hands-on practice, engaging and good amount of breaks in between. Thus did not feel tired/lethargic.
Charles Lim - Ministry of Defence, Singapore
Course: Python for Data Analysis
possibility to check code, to ask and to verify what has been done, vast knowledge of trainer
Adrian Zieliński, Mid Ocean Logistics Poland Sp. z.o.o
Course: Python Programming - 4 days
Opisy funkcji, przedstawione przykłady, alternatywne wersje. Przesył przydatnych do pracy w Pythonie linków.
Agnieszka Jurołajć, VOLKSWAGEN POZNAŃ SP. Z O.O.
Course: Python Programming - 4 days
The communication with the Mr. Khobeib
Aref AlHosani - Ali Aljneibi, beamtrail
Course: Python Programming - 4 days
trainer was very helpful, patient, and friendly
Ali Aljneibi, beamtrail
Course: Python Programming - 4 days
The knowledge of the trainer was very high and the material was well prepared and organised.
Otilia - Gareth Morgan, TCMT
Course: Machine Learning with Python – 2 Days
I thought the trainer was very knowledgeable and answered questions with confidence to clarify understanding.
Jenna - Gareth Morgan, TCMT
Course: Machine Learning with Python – 2 Days
I did like the exercises
Office for National Statistics
Course: Natural Language Processing with Python
Learned lots of things of course.
Jonathan Rico, Nordic Semiconductor ASA
Course: Advanced Python - 4 Days
The first 2 days were very informative. it gets messy when you get into frameworks because every projects has its own goals and requirements and sometimes the 'popular' framework isn't suitable.
Raphael Treccani-Chinelli - Jonathan Rico, Nordic Semiconductor ASA
Course: Advanced Python - 4 Days
How flexible Gunnar was with what he taught. He seemed well prepared and of god knowledge in the topic.
Jonathan Rico, Nordic Semiconductor ASA
Course: Advanced Python - 4 Days
SciPy Course Outlines in Singapore
Course Name
Duration
Overview
Course Name
Duration
Overview
7 hours
This instructor-led, live training in Singapore (online or onsite) is aimed at developers who wish to use SciPy to create advanced scientific computing functions with Python.
By the end of this training, participants will be able to:
- Set up the necessary development environment to start creating scientific computing functions.
- Get the full benefit of SciPy features by performing practical examples of complex operations.
- Implement and optimize mathematical algorithms and functions to solve scientific problems.
- Design data structures and interpolation methods for visualization, processing, and analysis.
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