Professional Certificate in Machine Learning (Python) – Introduction to Python Programming

Overview

Python is one of the leading open-source programming languages in the field of data science. It is a language that can be applied throughout the data pipeline, which includes data management, wrangling, modelling and visualisation. Learn how to solve real world problems by applying statistical techniques and machine learning models using Python.

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Run 1: 22, 26, 27 April 2019 [FULLY SUBSCRIBED - 30 PAX, REGISTRATION CLOSED!]

Run 2: 6, 10, 11 May 2019 [NOW OPEN FOR REGISTRATION!]

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Python is a general-purpose, versatile, powerful and popular programming language. It's great as a first language because it is concise and easy to read.  This course serves as an introduction to both fundamental programming concepts and the Python programming language.

Next Course Starts On06 May 2019 (Mon) See Full Schedule
Fee SGD1712.00* (as low as SGD113.60* after maximum funding) Learn more
Duration

2 weekday evenings and a full Saturday (15 hours)

Level
Basic
Learning Objectives

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

•    Get introduced to pseudo-coding and the world of python programming.
•    Explore concepts of numerical and string variables.
•    Learn to write control flow statements and make logical comparisons.
•    Learn to implement for and while loops as well as functions.

Work towards a bigger goal

This module is part of:

Professional Certificate in Machine Learning (Python)

Learn more

Who Should Attend

•    Aspiring data science professionals seeking to apply Python to real world data problems e.g. business intelligence analysts, data engineers
•    Anyone with an interest in learning about the fundamentals of data science programming!
•   Anyone whose work interfaces with data analysis who wants to learn key concepts, formulations, algorithms, and practical examples of what is possible in machine learning and artificial intelligence
•   Managers who need the vision and understanding of the many opportunities, costs, and likely performance hurdles in predictive modeling, especially as they pertain to large amounts of textual (or similar) data
•   Professionals looking for a deeper understanding and hands-on experience with SMU School of Information System's adjunct faculty and industry expert
•   No prior experience or background required in the field

Assessment

Assessment

    •In-class group work

    •Individual assessment

Learning Activities

Instructional Methods and Learning Activities

Lectures, Discussions, Case Studies

Fees and Funding

SkillsFuture Singapore (SSG) Funding:

A) Self-Sponsored Individual/Non-SME Company Sponsored Individual
•    S$193.60 (Singapore Citizens above 40 years old) after SSG (Mid Career Enhanced Subsidy) MCES Funding (Up to 90% course fee subsidy);
•    S$513.60 (Singapore Citizen/PR below 40 years old) after SSG Funding (Up to 70% course fee subsidy);
•    S$113.60 (Singaporeans on Workfare Training Support Scheme) after SSG (Workfare Training Support Scheme) WTS Funding (Up to 95% course fee subsidy).

A.1 SkillsFuture Credit

Self sponsored Singapore Citizens aged 25 and above may use their SkillsFuture Credit (up to S$500) to further defray part of the subsidised course fee. Please click User Guide in the Skillsfuture Credit website to find out how to submit your claim. 

SkillsFuture Credit claims may be submitted by logging in via 
MySkillsFuture.sg.
SkillsFuture Course Code*: CRS-N-0048190
SkillsFuture Course Name*: Professional Certificate in Machine Learning (Python): Module 1 - Introduction to Python Programming
* Important Note: Participants claiming SkillsFuture credits should locate the course in Training Exchange using the Course Code/Name


B) SME Company Sponsored Individual (Enhanced Training Support for SMEs - "ETSS"):
•    S$193.60 (Singapore Citizen/PR) (Up to 90% course fee subsidy)

Note: Companies which meet all of the following criteria can qualify for the Enhanced Training Support under the SME scheme:
           i. Company must be registered or incorporated in Singapore;
           ii. Employment size (at group level) of not more than 200; OR Annual sales turnover (at group level) of not more than S$100 million; and
           iii. At least 30% local shareholding being held by Singapore Citizens or Singapore Permanent Residents.

B.1 Absentee Payroll
Companies who sponsor their employees for the course may apply for Absentee Payroll via the SkillsConnect system. For more information, please visit SkillsConnect.

C) Full Fees (Foreigners. i.e. non-Singaporean Citizens and non-Permanent Residents)
S$1,712 (after GST) for non-Singapore Citizens and non-Permanent Residents.

Schedule

Start Date(s)
Intake Information

Course dates:

Run 1 : [FULLY SUBSCRIBED - 30 PAX] [REGISTRATION CLOSED!]

22 Apr 2019, 

26 Apr 2019,

27 Apr 2019

Run 2 : [NOW OPEN FOR REGISTRATION!]

6 May 2019, 

10 May 2019,

11 May 2019

Speaker/Trainer Bio

Mr. Johnson Poh

Adjunct Faculty, Big Data and Analytics, SMU

Johnson is currently Adjunct Faculty at Singapore Management University's School of Information Systems and his focus areas include applied statistical computing, machine learning as well as big data tools and techniques. His industry experience spans across finance, consulting and government sectors, serving as Head of Data Science and Principal Data Scientist in DBS, Booz Allen Hamilton and Ministry of Defence respectively. An avid programmer and data enthusiast, Johnson enjoys developing apps and data products. Most recently, he was awarded first prize in Singapore’s largest coding competition, Hackathon@SG 2015 as well as the CapitaLand Data Challenge 2016. Johnson completed his bachelor’s degree at University of California, Berkeley, majoring in the subjects of Pure Mathematics, Statistics and Economics. He received his postgraduate degree in Statistics at Yale University.

Additional Details

• Good Bachelor's Degree
• Diploma Holders with at least 3 years of working experience

Policies

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