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Introduction to Deep Learning (IDL)

 

Overview

Duration 5 days
Enquiry Please contact Ms. Jenny YIP
Tel: 66013592 or
Email matykk@nus.edu.sg

 

Requirement and expectation on this course

Participants need to equip knowledge of calculus and linear algebra at entry university level.

Over a period of 5 days, there will be 16 hours of lectures and 4 hours of practical session in computer lab.

 

Upcoming Class

Lecture 18 - 21 Nov 2019

9am - 11am

2pm - 4pm

Practical Session 22 Nov 2019

9am - 11am

2pm - 4pm

 

Objective

"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."

 

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

 

Fees & Funding

 

International Participants

Singapore Citizens

Singapore PRs

Enhanced Training Support for SMEs

39 years old or younger

40 years old or older

Eligible for WTS

Full Programme Fee

$2,400.00

$2,400.00

$2,400.00

$2,400.00

$2,400.00

$2,400.00

Less: SSG Grant Amount

$0.00

$1,680.00

$1,680.00

$1,680.00

$1,680.00

$1,680.00

Nett Programme Fee

$2,400.00

$720.00

$720.00

$720.00

$720.00

$720.00

7% GST on Nett Programme Fee

$168.00

$50.40

$50.40

$50.40

$50.40

$50.40

Total Nett Programme Fee Payable, Including GST

$2,568.00

$770.40

$770.40

$770.40

$770.40

$770.40

Less Additional Funding if Eligible Under Various Schemes

$0.00

$0.00

$480.00

$600.00

$0.00

$480.00

Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes

$2,568.00

$770.40

$290.40

$170.40

$770.40

$290.40

 

Various Funding Schemes

1) SkillsFuture Mid-Career Enhanced Subsidy (MCES)
  Singaporeans aged 40 and above may enjoy subsidies up to 90% of the course fees.
 
2) Workfare Training Support (WTS)
  Singaporeans aged 35 and above (13 years and above for Persons With Disabilities) and earn not more than $2,000 per month, may enjoy subsidies up to 95% of the course fees.
 
3) Enhanced Training Support for SMEs (ETSS)
  SME-sponsored employees (Singaporean Citizens and PRs) may enjoy subsidies up to 90% of the course fees. For more details, click on Enhanced Training Support for SMEs.

Course participant is eligible for only one funding scheme.

Lecturers

REN Weiqing

Professor

National University of Singapore

 

JI Hui

Associate Professor

National University of Singapore

 

http://tiny.cc/FoS_IDL

 

Publicity Poster

 

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