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

Python Machine Learning with Scikit Learn Training

Scikit Learn is the de facto Machine Learning package for Python. It consists of classification, regression, clustering, dimension reduction, model selection, and many data preprocessing functionalities. You can do many supervised and unsupervised machine learning with Scikit Learn. This Scikit Learn training aims to equip you with basic machine learning knowledge using such as classification, regression, clustering, PCA, ensemble methods, and neural networks.

Course Highlights

  • Supervised Learning
  • Classification
  • Linear regression
  • Unsupervised Learning
  • Clustering
  • Principal Component Analysis (PCA)
  • Decision Tree
  • Basics of Neural Network

Certificate

All participants will receive a Certificate of Completion from Tertiary Courses after achieved at least 75% attendance.

Funding and Grant Applications

Click the links below to apply. Note that you need to register the course first.

For Singaporeans: SkillsFuture Credit

For Company: SSG Training Grant

Course Code: CRS-N-0033664

Course Booking

$298.00 (GST-exclusive)
$318.86(GST-inclusive)

Course Date

Course Time

* Required Fields

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.


Course Details

Module 1 Getting Started on Scikit-Learn

  • What is Scikit Learn
  • Scikit Learn Applications
  • Installing Scikit-Learn

Module 2 Classification

  • What is Classification
  • Classifier Algorithms
  • Classification Steps
  • Ensemble Classifiers
  • Save and Load Models
  • Confusion Matrix
  • Classification Metrics - Precision, Recall, F1 Score

Module 3 Regression

  • What is Regression
  • Regression Algorithms
  • Linear Regression
  • Multivariate Regression

Module 4 Clustering

  • What is Clustering
  • Clustering Algorithms

Module 5 Dimension Reduction

  • Principal Component Analysis

Module 6 Neural Network

  • What is Neural Network?
  • Multi Layer Perceptron Classifier
  • Activation Functions and Solvers

Course Admin

Prerequisite

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

Software Requirement

Please download and install the following software prior to the class

Who Should Attend

  • Data Analysts
  • Data Scientists
  • Financial Analytics
  • Engineers
  • Digital Marketers

Trainers

Scikit Learn TrainerWesley Goi is currently in his final year of his PhD in Bioinformatics at National University of Singapore (NUS) where he previously received his degree in Molecular Biology at NUS (Honours 2nd Uppers). He was the TA for Introductory Bioinformatics LSM2241. He specialises in analysing high throughput DNA and RNA sequencing data of complex microbial communities using network analyses and various functional analyses. In his previous projects he has applied machine learning methods to vaccine discovery.

Scikit Learn 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.

Scikit Learn 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.

Python Scikit Learn TrainerLisa Lee has her degree in Finance at the Illinois Institute of Technology. Prior to returning to Singapore, she worked as a financial analyst in a US-start up that sells business intelligence to dental offices. She was on the winning team for the Chicago Quantitative Alliance (CQA) Investment Challenge in 2015.Her core specialisation skills are R, Python, Machine Learning, Statistical Analysis, and Data Visualisation in Tableau and Qliksense. She currently works as a Data Science Instructor at a local university.

Scikit Learn 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.

Scikit Learn Machine Learning 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.

Python Scikit Learn TrainerJohnson Ang has a Masters in IT Analytics from SMU and is certified and a member of GARP, CQF andFSM. He has more than 8 years of working experience, of which 4 years of experience in the Banking Wide Operations and has been particularly involved in mega IT Analytic banking projects within the Risk Management and Financial Instrument sphere.

He can offer varied solid perspectives and has experience working with folks from all sorts of background, such as Developers, Traders/Dealers, CxOs, Programmers, Project Managers, Auditors, Head/Country Directors, Regulators, RMs, which is particularly during his stint in the Front, Middle and Back Office, as well as industry such as Real Estate, FMCG, Construction and Education Sector.

Not only he is familiar with typical banking software, but also has also been acquainted with popular tools such as SAS, JMP, Oracle, VBA, Access, Python, R, C, Java and many more. He has also developed a strong passion for Mathematics, Trading and Computing at a young age and has been a self-professed Algo-Trader having a Sharpe ratio of >3 and a passionate Math Tutor having taught over hundreds of students from Primary to University level.

Python Scikit Learn TrainerDr. Yongxin (Steve) has more than five years of solid industrial and research experiences in data analytics. He held PhD 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.

Python Scikit Learn TrainerAng Ming 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

Scikit Learn TrainerSunny Prakash is a Big Data Architect with Programming Background . He has around 7 years of IT experience. He has worked on Various Enterprise level solution. He is skilled in Cloud computing and Big Data Solution building in various Industrial sector and domain.

With an Strong background in Coding skills, he has a strong grips on Java,Python ,Scala ,HTML,JavaScript, Node Programming. Data Science is another specification where he has worked with larger Enterprises for finding their Data Insight and building Machine Learning mode

Scikit Learn TrainerDr Zheng Zejun has seven years’ experience in the data-mining field. Zejun worked as a (Sr.) bioinformatics scientist for six years and currently works as a data scientist manager. Dr. Zheng;s expertise covers machine learning, statistics, algorithm design, bioinformatics and high performance computing. He has published three machine learning algorithms on well-recognized academic journals together with the open source software (CUDA-CRISY, FSOM, DYSC). Zejun is professional with an extensive set of programming languages, including C/C++, Python, R, JAVA and flask for data driven analytics and scalable computing. He has also a broad knowledge of algorithms and mathematical models in the data-mining field.

Customer Reviews (56)

Will Recommend Review by Course Participant/Trainee
1. Do you find the course meet your expectation?
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3. How do you find the training environment
. (Posted on 9/26/2019)
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Trainer was easy to follow and explained the examples well. (Posted on 9/26/2019)
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. (Posted on 9/26/2019)
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The trainer is good. She was able to explain difficult concepts (Posted on 9/26/2019)
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More opportunities to practice (Posted on 9/26/2019)
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. (Posted on 9/26/2019)
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3. How do you find the training environment
. (Posted on 9/26/2019)
Will Recommend Review by Course Participant/Trainee
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3. How do you find the training environment
/ (Posted on 9/26/2019)
Will Recommend Review by Course Participant/Trainee
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3. How do you find the training environment
. (Posted on 9/25/2019)
Will Recommend Review by Course Participant/Trainee
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more time for deep learning with keras (Posted on 9/25/2019)
Will Recommend Review by Course Participant/Trainee
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3. How do you find the training environment
. (Posted on 9/25/2019)
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3. How do you find the training environment
. (Posted on 9/20/2019)
Might Consider Review by Course Participant/Trainee
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. (Posted on 9/20/2019)
Might Consider Review by Course Participant/Trainee
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2. Do you find the trainer knowledgeable in this subject?
3. How do you find the training environment
. (Posted on 9/20/2019)
Will Recommend Review by Course Participant/Trainee
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It will be good to make it as a two days course, 1.5 days for theory and 0.5 days for practical work on actual data that we intend to work on (Posted on 7/24/2019)
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. (Posted on 6/20/2019)
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3. How do you find the training environment
. (Posted on 6/20/2019)
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3. How do you find the training environment
. (Posted on 6/20/2019)
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