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What makes the course unique?

Machine Learning for Humans develops the cognitive capacities in participants on how to think like a data scientist. Through the lens of data science, participants will gain a broad overview on the history of data, how to conduct a machine learning project from start to finish, the practical application of various machine learning models

MACHINE LEARNING IN EVERYDAY TERMS

The course breaks down complex data processes and machine learning techniques / models through the visual power of animation, motion graphics, and storytelling. ​


EXPLAINED AND PRESENTED BY EXPERTS

The course is presented and explained by experienced data scientists. They will share the concepts used when designing machine learning models for real-world problems. ​


SCENARIO-DRIVEN ASSESSMENT

Participants will complete scenario-based assessments to ensure that they understand and can apply the techniques taught in the modules. ​



Who should take
this course?

The programme is designed for professionals who are keen to understand how Machine Learning is changing and disrupting businesses. 

This online course will be of interest for professionals who deal with data on a day-to-day basis and wish to understand how data can be leveraged for smarter business decisions.



Trainer Profiles


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​JANET UY
Asean Lead Data Scientist,
Oracle Singapore
RITCHIE NG
Chief AI Officer,
Ensemble Capital
​ELAINE LIEW
Data Scientist,
Govtech Singapore

KENNETH SOO
Co-Author
"Numsense! Data Science for the​ Layman"

Partner



Curriculum

This online course comprises 8 chapters with 20 modules, covering topics like how to conduct a machine learning project from start to finish to basic machine learning techniques. The concept within each module is delivered through an engaging visual presentation using animation and motion graphics, delivered by experienced data scientists. 

By the end of this course, participants will be able to: 

  • Grasp the complexities of big data generated by people and systems
  • Learn the data requirements of a problem space
  • Discover the steps to conduct a machine learning project from start to finish
  • Recognise 10 basic machine learning techniques
  • Apply appropriate machine learning techniques for different types of business problems
  • Understand how to work effectively with a data expert to implement a machine learning solution
  • Comprehend the ethical considerations when implementing a machine learning solution
​​CHAPTER 1 - The Rise of a Data-Driven World

Learn about the history of data and how machine learning will revolutionise the way decisions are made on an organisational and global level. 
​CHAPTER 2 - Conduct a Machine Learning Project - [Part 1]

Discover the fundamental steps data scientists take to frame a problem statement, collect and prepare data and select or engineer features for a machine learning implementation.
​CHAPTER 3 - Conduct a Machine Learning Project - [Part 2]

Understand how data scientists select, train and evaluate appropriate machine learning models, to achieve business objectives. 
CHAPTER 4 - How Machines Predict Values

Follow the science behind linear regression to predict the future.
​CHAPTER 5 - How Machines Predict Categories

Identify how machine learning is able to categorise data accurately, enabling companies to effectively profile a large customer database and provide the most relevant products and services.
CHAPTER 6 - How Machines Predict Relationships

Develop an understanding of data clusters and association rules and discover how machine learning creates differentials and associations with data
CHAPTER 7 - Advanced Modelling Techniques

Grasp concepts such as artificial neural networks and reinforcement learning and see how they have already begun to propel machines into the new age of artificial intelligence. 
CHAPTER 8 - Key Considerations when Machines Learn

Define and navigate the moral and ethical grey areas when dealing with machine learning


Course Informat​ion

​Application Period
25 Sep - 30 Oct
Course Date​
​23 Nov 2020​​
Assessment/ Award
This course provides a broad overview of the knowledge, skills and mental models that data scientists use to frame problem statements, select machine learning model​s and evaluate those models. 

The course is estimated to take 20-30 hours to complete on average. Upon the successful completion of the course, participants will be awarded a certificate of completion from Ngee Ann Polytechnic.
Course Fees
Full course fee: $695.50

Singaporeans and Permanent Residents: $208.65
Singaporeans qualified for SkillsFuture Mid-Career Enhanced Subsidy: $78.65
Singaporeans and Permanent Residents qualified for Enhanced Training Support for SMEs*: $78.65

*Enter SME in the promo code during course application.

Course fee is payable upon acceptance. It is inclusive of 7% GST and subject to review.

For more information on other subsidies, please click here.


Ngee Ann Polytechnic reserves the right to reschedule / cancel any programme, modify the fees and amend information without prior notice.​

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