Introduction to deep learning



Overview

School FACULTY OF SCIENCE
Department MATHEMATICS
Code FOS-IDL
Funding Type SSG Funded
Stackable To An Academic Qualification? Not applicable
Name of Full Academic Qualification Not applicable
Category Science
Course Type SHORT COURSE
Can be done on AUDIT basis? No



Objectives

Deep learning is a powerful machine learning tool for artifical intelligence and data sciences, with a wide range of real-world applications . This course aims at introducing basic concepts, numerical algorithms, and computing frameworks in deep learning. The emphasis is on the numerical algorithms, implementation in industrial computing framework, and examination on real data-intensive problems drawn from practical applications. At the end of this course, students will acquire the basic understanding on the fundamentation of deep learning, master the most often used computational tools, and be able to use them to solve practical problems. Major topics include: Basics on learning theory, clustering, supervised learning, deep neural network, programming in python, tensor flow Deep learning is an emerging field under data analytics. Deep learning can be applied to many different industries such as healthcare, finance and engineering. Therefore, it is a very useful and practical skill for executives, managers, professionals, researchers, etc. Learners can utilise the knowledge picked up from this course to come up with better solutions to solve real-world problems that might be related to business decisions, mathematical or scientific research, topics related to social sciences, etc.




Outline

Not available




Who Should Attend

• Data Analysts; • Big Data Consultants; • Advertising Analysts; • Customer Insights Analysts; • Data engineers; • Data managers; • Marketing analysts; • Product managers; • Chief Technology Officer; • Chief Information Officer; • Chief Digital Officer.




Entry Requirements

Knowledge of calculus and linear algebra at entry university level




Class Schedule

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Lecture Sessions

AM, PM




Lesson Delivery

a) Facilitated Learning - 20 hours; b) Project - 20 hours.




Calendar

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Full Fees (before GST)

S$2400.00




Fees and Fundings

International Participant Singapore Citizen 39 years old or younger Singapore Citizen 40 years or older eligible for MCES Singapore Citizen eligible for WTS Singaporean PRs Enhanced Training Support for SMEs
Full Programme Fee S$2400.00 S$2400.00 S$2400.00 S$2400.00 S$2400.00 S$2400.00
SkillsFuture Funding Eligible for Claim Period (19 Oct 2017 to 30 Sep 2020) - (S$1680.00) (S$1680.00) (S$1680.00) (S$1680.00) (S$1680.00)
Nett Programme Fee S$2400.00 S$720.00 S$720.00 S$720.00 S$720.00 S$720.00
7% GST on Nett Programme Fee S$168.00 S$50.40 S$50.40 S$50.40 S$50.40 S$50.40
Total Nett Programme Fee Payable, Incl. GST S$2568.00 S$770.40 S$770.40 S$770.40 S$770.40 S$770.40
Less Additional Funding if Eligible Under Various Scheme - - (S$480.00) (S$600.00) - (S$480.00)
Total Nett Programme Fee, Incl. GST, after additional funding from the various funding schemes S$2568.00 S$770.40 S$290.40 S$170.40 S$770.40 S$290.40



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