Course Information

  • Sessions 1 day
  • Duration 7.5 hrs
  • Level Intermediate
  • Assessment NA

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

Download Course Brochure

Certification

  • Certificate of Completion from Tertiary Courses - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Courses.

Python Machine Learning with Scikit-Learn Training

Course Code: C188

What's This Course About

Enter the dynamic realm of machine learning with our specialized Python training module using Scikit-Learn at Tertiary Courses. From understanding the core differences between supervised and unsupervised learning to hands-on engagements with classification model analysis, our curriculum promises in-depth exploration. F1 Score and AUC metrics ensure that participants gain key insights into the accuracy and performance of their ML models.

The course further delves into critical machine learning facets like multivariate linear regression, supplemented by techniques such as Ridge and Lasso regularization to counter overfitting effectively. Participants will also be introduced to Silhouette Analysis and Dendrogram methods, empowering them with clustering skills. Concluding with dimension reduction using PCA, our program ensures that attendees walk away with a well-rounded, practical understanding of Python-powered machine learning using Scikit-Learn.

Funding Options

No funding is available for this course.

If you prefer a WSQ funding, please checkout our WSQ - Basic Machine Learning with ScikitLearn Course.

Course Fee

$350.00 (GST-exclusive)
$381.50 (GST-inclusive)

Course Date

* Required Fields

Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

Post-Course Support

  • We provide free consultation related to the subject matter after the course.
  • Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Cancellation & Reschedule Policy

  • You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
  • Note the venue of the training is subject to changes due to availability of the classroom.

Course Details

Course Details

What You'll Learn

Topic 1 Overview of Machine Learning and Scikit Learn

Introduction to Machine Learning

Supervised vs Unsupervised Learnings

Machine Learning Applications and Case Studies

What is Scikit Learn

Installing Scikit-Learn

Topic 2 Classification

What is Classification

Classification Algorithms

Classification Workflow

Confusion Matrix

Binary Classification Metrics

ROC and AUC

Topic 3 Regression

What is Regression?

Regression Algorithms

Regression Workflow

Regression Metrics

Overfitting and Regularizations

Topic 4 Clustering

What is Clustering

K-Means Clustering

Silhouette Analysis

Dendrogram and Hierarchical Clustering

Topic 5 Principal Component Analysis

Curse of Dimensionality Issue

What is Principal Component Analysis (PCA)

Feature Reduction with PCA

Course Info

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you wrte us a Google review.

Minimum Entry Requirement

Knowledge and Skills

  • Able to operate using computer functions
  • Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

  • Positive Learning Attitude
  • Enthusiastic Learner

Experience

  • Minimum of 1 year of working experience.

Target Age Group: 21-65 years old

Minimum Software/Hardware Requirement

Software:

Download and Install the following software

Sign up free Google Colab account

Hardware: Window or Mac Laptops

Job Roles

Job Roles

  • Aspiring Software Developer
  • Data Analyst
  • Web Developer
  • Automation Engineer
  • Data Scientist
  • System Administrator
  • Bioinformatics Specialist
  • Research Scientist
  • Finance Professional
  • Machine Learning Enthusiast
  • GIS (Geographic Information System) Specialist
  • IT Consultant
  • Network Engineer
  • Database Administrator
  • Tech Entrepreneur.

Trainers

Trainers

Ken Yuen is an ACTA-certified adult educator specializing in STEM education, IoT systems, and programming. With a background in electrical and electronics engineering from NTU, he has conducted WSQ and SkillsFuture courses in Arduino, Raspberry Pi, micro:bit, Jetson Nano, and Python. He is also a registered MOE instructor, having taught coding and robotics programs in over 50 schools, equipping students and professionals alike with practical IoT and programming skills. In his IoT courses, Ken focuses on hands-on experimentation with microcontrollers, sensors, and automation systems. His prior experience as a Technical Consultant at Anson Engineering saw him develop IoT-based SCADA and temperature monitoring systems for industrial applications, giving him strong industry insight. By blending educational expertise with technical project experience, Ken ensures learners develop the confidence to build, test, and apply IoT solutions in real-world contexts.
CY Quah is an ACLP-certified trainer and data science professional with extensive experience in Python, NLP, and machine learning. He has led AI training programs for SAP, Temasek Polytechnic, and IMDA under the SGUnited Mid-Career Pathways initiative, and has delivered corporate workshops on text analytics, recommender systems, and chatbot development. His expertise includes applying NLP tools such as NLTK, spaCy, and Gensim for sentiment analysis, topic modeling, and text classification.

Truman Ng is a ACTA certified trainer that graduated with Bachelor Degree in Electrical Engineering from NUS in year 2002. He designed Artificial Intelligence (AI) controller for DC-DC Power Convertor by using Fuzzy Logic and Neural Network (NN) as his university Final Year Project.
Truman has over 15 years project experiences across Database & Web Design, PLC machinery, Data Center Design , Structure Cabling System(SCS) and Enterprise Network Design and Implementation. He used to be a network architect for Hewlett Packard, working with a group of virtual team from the US in handling network design and projects in the States.
Truman is the founder of Nexplore (S) Pte Ltd. He provides solutions of Cloud SaaS, IaaS & PaaS and Software Defined Network (SDN), VoIP and Internet Security. He was engaged by Huawei Global Training Center to provide 60+ consultations and trainings for Internet Service Providers(ISP) from Malaysia, Singapore, Brunei, Philipines, Australia, Poland, Iran, South Africa, Swaziland, Cote Dlvoire, Syria, Uzbekistan, New Zealand and countries over the world.As achievement, Truman has successfully completed 100+ IT network projects for Bank, Hotel and Factory within 5 years.Truman is certified in PMP, Cisco CCNP, CCIP, CCDP, HP Ase and Huawei HCNP, HCIE R&S, HCNA Cloud, HCNA Security, etc.

Marcel Leng is an ICT professional and educator with strong expertise in machine learning, cryptography, and applied mathematics. He has conducted extensive research and training in AI, data science, and quantum algorithms, and has guided learners in applying advanced computational tools to real-world security challenges.

Review

Customer Reviews (71)

Will Recommend Review by Course Participant/Trainee
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
Alfred was good, however, it would be great if he would be more receptive to questions (Posted on 8/2/2017)
Will Recommend Review by Course Participant/Trainee
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
By giving a take home real time project to try on own (Posted on 8/2/2017)
Great Review by Course Participant/Trainee
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 enjoyed the course. For a one day course the amount covered is sufficient.
Suggestions for other courses could be something focused on say, recommendation engines. (Posted on 7/9/2017)
Will Recommnd Review by Course Participant/Trainee
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 12/28/2016)
Will Recommend Review by Course Participant/Trainee
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 think one of the participant clearly did not understand what is the course he has signed up and repeatedly asked the same questions again and again. I feel the instructor should moderate such questions for the sake of time. I was early to come to the course and end up needing to go home late, so of course I must say I am not exactly happy about it. Although I understand that this is no fault of the school, but I just felt that some sensitivity is necessary. I am not sure what is the reason, but it could also be the course details did not clearly stated the requirements and expectation participants should have of the course. (Posted on 8/28/2016)

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