Professional Certificate in Machine Learning (Python)

Overview

With recent advances in deep learning technologies, Machine Learning and Artificial Intelligence is gathering momentum to be one of the key pillars of the next Industry Revolution. It is anticipated that the machine learning market will grow from $1.4 billion in 2017 to $8.8 billion by 2022 according to a research report by Research and Markets and an increasing number of organisations would be looking into acquiring machine learning talent to help them develop intelligent applications that harness the power of AI to help them gain a competitive edge.

Through this course, graduates will develop the relevant skillsets to build data-driven Machine Learning/AI applications and cognitive products using Python, which is becoming one of the world's most popular programming languages used by world class organisations across different industries such as Google, IBM, Facebook, Tesla, Fiat, Bank of America, J.P Morgan, amongst others.

Learn from SMU's world-class award-winning faculty and industry practitioners on how to build effective machine learning systems to solve real world problems by applying statistical techniques and machine learning models using Python and become one of the most sought after Data Science professionals in the industry today. 

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Run 1: 22 April 2019 -  28 September 2019 [FULLY SUBSCRIBED - 30 PAX, REGISTRATION CLOSED!]

Run 2: 6 May 2019 -  12 October 2019 [NOW OPEN FOR REGISTRATION!]

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By just putting in a few days a month for the next 6 months, this is what you’ll get:
1) New skills to enhance to your resume, such as regression, classification, clustering, sci-kit learn and SciPy 
2) A practical industry-relevant capstone project that you can add to your portfolio - Participants may choose from predicting property investment trends, predicting crowdfunding success and recommendation engines
3) A certificate in machine learning (Python) from SMU to validate your competency

Click below on the Whatsapp icon and find out more about the Professional Certificate in Machine Learning (Python) right now! Our operators are standing by.

Next Course Starts On06 May 2019 (Mon) See Full Schedule
Fee SGD10272.00* (as low as SGD1161.60* after maximum funding) Learn more
Duration

2 weekday evenings and a full Saturday (15 hours) per module

Level
Basic
Learning Objectives

The Professional Certificate Program in Machine Learning (Python) enables you to:
•    Build up hands-on proficiency in Python programming 
•    Learn to wrangle data with Python
•    Apply common statistical data analysis techniques and modelling using Python
•    Apply data visualisation techniques using Python
•    Develop machine learning models encompassing supervised and unsupervised learning using Python
•    Apply them to real world problems in a capstone project

Topics/Structure

Modules

•    Professional Certificate in Machine Learning (Python) – Introduction to Python Programming
•    Professional Certificate in Machine Learning (Python) – Statistical Thinking and Exploratory Analysis
•    Professional Certificate in Machine Learning (Python) – Basic Concepts of Data Modelling
•    Professional Certificate in Machine Learning (Python) – Advanced Concepts of Data Modelling
•    Professional Certificate in Machine Learning (Python) – Practical Concepts in Supervised Machine Learning
•    Professional Certificate in Machine Learning (Python) – Practical Concepts in Unsupervised Machine Learning

This is a sequential programme where modules necessarily have to be taken in the above specified order to ensure that the foundations for pre-requisite knowledge are satisfied before participants are introduced to more advanced concepts.

Module 1

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

Next course starts on: 06 May 2019 (Mon) (See complete schedule)

Overview

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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.

Module 2

Professional Certificate in Machine Learning (Python) – Statistical Thinking and Exploratory Analysis

Next course starts on: 27 May 2019 (Mon) (See complete schedule)

Overview

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Run 1: 27, 31 May & 1 June 2019 [FULLY SUBSCRIBED - 30 PAX, REGISTRATION CLOSED!]

Run 2: 3, 7, 8 June 2019 [NOW OPEN FOR REGISTRATION!]

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In this course, you will learn the foundations of probability and statistics. You will learn both the mathematical theory, and get a hands-on experience of applying this theory to actual data using Python.

Module 3

Professional Certificate in Machine Learning (Python) – Basic Concepts of Data Modelling

Next course starts on: 24 Jun 2019 (Mon) (See complete schedule)

Overview

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Run 1: 24, 28, 29 June 2019 [FULLY SUBSCRIBED - 30 PAX, REGISTRATION CLOSED!]

Run 2: 1, 5, 6 July 2019 [NOW OPEN FOR REGISTRATION!]

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Once you’ve identified a big data issue to analyse, how do you collect, store, organise and visualise your data using Python? In this course, you will experience various data genres and management tools appropriate for each in Python.

Learning how to leverage Python libraries to visualize data will also enable you to extract information, better understand the data, and make more effective decisions. This course teaches participants how to take data that at first glance has little meaning and present that data in a form that makes sense to people.

Module 4

Professional Certificate in Machine Learning (Python) – Advanced Concepts of Data Modelling

Next course starts on: 22 Jul 2019 (Mon) (See complete schedule)

Overview

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

Run 2: 5, 8, 10 August 2019 [NOW OPEN FOR REGISTRATION!]

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In this course, you will start building the foundation you need to think statistically, to speak the language of your data, to understand what they are telling you. The foundations of statistical thinking took decades upon decades to build, but they can be grasped much faster today with the help of computers. With the power of Python-based tools, you will rapidly get up to speed and begin thinking statistically by the end of this course.

The trainer walks participants through using Python to implement simple statistical experiments and shares examples using real-world data to answer the three fundamental questions of statistical inference: how to use data to estimate the size of whatever effect you observe, how to quantify the precision of that estimate, and how to decide whether the apparent effect might be due to chance.

Module 5

Professional Certificate in Machine Learning (Python) - Practical Concepts in Supervised Machine Learning

Next course starts on: 26 Aug 2019 (Mon) (See complete schedule)

Overview

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Run 1: 26, 30, 31 August 2019 [FULLY SUBSCRIBED - 30 PAX] [REGISTRATION CLOSED!]

Run 1: 2, 6, 7 September 2019 [NOW OPEN FOR REGISTRATION!]

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This course covers the 2 main types of supervised learning, namely: regression and classification. The classification models are mainly used in face recognition, spam identification, etc. Regression models are often used to make predictions about future values of a system with direct applications in finance, health etc.

Participants will also learn how to choose an appropriate model and about the general trade-off between model accuracy and interpretability.

Module 6

Professional Certificate in Machine Learning (Python)- Practical Concepts in Unsupervised Machine Learning

Next course starts on: 23 Sep 2019 (Mon) (See complete schedule)

Overview

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Run 1: 23, 27, 28 September 2019 [FULLY SUBSCRIBED - 30 PAX] [REGISTRATION CLOSED!]

Run 2: 7, 11, 12 October 2019 [NOW OPEN FOR REGISTRATION!]

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In this course, participants learn the fundamentals of unsupervised learning and implement the essential algorithms using scikit-learn and scipy. They will also learn how to cluster, transform, visualize, and extract insights from unlabelled datasets. Participants end the programme with a capstone project by building either:

1)    a recommendation system to recommend popular youtube videos / music artists, OR
2)    exploring key factors in predicting success in crowdfunding projects, OR
3)    data driven housing valuation and trend analysis

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

Fees and Funding

SkillsFuture Singapore (SSG) Funding:

A) Self-Sponsored Individual/Non-SME Company Sponsored Individual
•    S$1,161.60 (Singapore Citizens above 40 years old) after SSG (Mid Career Enhanced Subsidy) MCES Funding (Up to 90% course fee subsidy);
•    S$3,081.60 (Singapore Citizen/PR below 40 years old) after SSG Funding (Up to 70% course fee subsidy);
•    S$681.60 (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.  As courses in this professional certificate have been modularised, participants will need to identify which course to apply credits for.

SkillsFuture Credit claims may be submitted by logging in via MySkillsFuture.sg.
* 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$1,161.60 (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$10,272 (after GST) for non-Singapore Citizens and non-Permanent Residents.

Schedule

Start Date(s)
Intake Information

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

Course dates: 22, 26 and 27 April 2019

Professional Certificate in Machine Learning (Python) – Statistical Thinking and Exploratory Analysis

Course dates: 27, 31 May 2019 and 1 June 2019

Professional Certificate in Machine Learning (Python) – Basic Concepts of Data Modelling

Course dates: 24, 28 and 29 June 2019

Professional Certificate in Machine Learning (Python) – Advanced Concepts of Data Modelling

Course dates: 22, 26 and 27 July 2019

Professional Certificate in Machine Learning (Python) – Practical Concepts in Supervised Machine Learning

Course dates: 26, 30 and 31 August 2019

Professional Certificate in Machine Learning (Python) – Practical Concepts in Unsupervised Machine Learning

Course dates: 23, 27 and 28 September 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

Admission Requirements

A good Bachelor's degree (of any field) from a recognised University. Diploma holders from a recognised polytechnic with at least 3 years of relevant working experience and/or start-up experiences are welcome to apply. International students who hold a valid Employment Pass (EP) or Dependent Pass (DP).

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