Basic Machine Learning with ScikitLearn Course

Training Provider: TERTIARY INFOTECH PTE. LTD.
Course Reference: TGS-2019504643
S$375
Original: S$750
Save S$375

About This Course

Step into the transformative world of machine learning with our WSQ-endorsed Basic Machine Learning with Scikit-Learn Course. Designed to provide you with a solid foundation, this course focuses on key ML algorithms and data processing techniques using the Scikit-Learn library. Through hands-on projects and practical exercises, you'll learn how to train models, make predictions, and validate results, gaining the skills required for entry-level machine learning tasks.

By the completion of this course, you'll have a thorough understanding of the fundamentals of machine learning. You’ll be skilled in using Scikit-Learn to apply basic machine learning algorithms and prepare data for analysis. This course serves as a springboard for those aspiring to delve into more advanced topics in AI and data science, as well as professionals seeking to incorporate machine learning into their skill set.

What You'll Learn

Learning Outcomes:
understand and apply machine learning concepts
understand and apply classification methods
understand and apply regression methods
understand and apply clustering methods
understand and apply PCA methods

Course Outline:
Day 1

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
- Applications of Classification
- Classification Algorithms
- Classification Workflow
- Confusion Matrix
- Classification Performance Evaluation

Topic 3 Regression
- What is Regression
- Applications of Regression
- Regression Algorithms
- Regression Workflow
- Regression Performance Evaluation

Day 2

Topic 4 Clustering
- What is Clustering
- Applications of Clustering
- Clustering Algorithms
- Clustering Workflow
- Clustering Performance Evaluation

Topic 5 Principal Component Analysis
- Introduction to Principal Component Analysis (PCA)
- Application of PCA
- PCA Workflow

Final Assessment
- Written Assessment (Q&A)
- Written Assessment (Case Study)

Entry Requirements

Knowledge and Skills
• Able to operate computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
• 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.
• Minimum 18 years old

Course Details

Duration 16 hours
Language English
Training Commitment Part Time
Total Enrolled 42 students
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Note: To apply for this course, visit the SkillsFuture website or contact the training provider directly.

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