Machine Learning and Data Analytics using Python

Bridging Business and Digital Transformation with Machine Learning and Data Analytics to accelerate competitive advantage.

Country/Region
Work Experience

Please note that the programme duration includes a break week for Christmas from 24th Dec 2024 to 1st Jan 2025, and for Chinese New Year from 28th Jan 2025 to 3rd Feb 2025.

Future-Proof Your Career: Invest in Your Success

Emeritus and NUS School of Computing unite to offer an exclusive opportunity. Enrol before 18 October, 2024 using this code: APAC150ALL8316 and get USD 150 program fee benefit. Limited seats available. Reserve your spot today!

Upcoming Round Deadline: 18 October, 2024

What Will This Programme Do For You?

  • Explain the usage of data from insight generation and visualisation to fitting machine learning models using Python

  • Understand the data structures in Python

  • Extract data from database using SQL

  • Write custom functions and codes in Python, and use relevant libraries in Python such as pandas and Numpy to manipulate data

  • Perform ETL (Extract Transform Load) processing using data analysis expressions (DAX) to perform calculations

  • Align and apply the supervised and unsupervised learning models in Python

  • Develop dashboards using Power BI

  • Optimise neural networks by using normalisation to identify best parameters settings

  • Perform exploratory data analysis (EDA) and data wrangling on various data sources

  • Identify challenges and demonstrate best practices in implementing machine learning models

Note: The programme highlights mentioned above are subject to change based on faculty availability and the desired outcomes of the programme.

*This programme is primarily self-paced online with some live sessions conducted by programme faculty. The availability of post-session video recordings is at the discretion of the faculty members, and Emeritus or the institute cannot guarantee their availability. We have a curated panel of distinguished industry practitioners who will conduct weekly live doubt-clearing sessions.

**Assignments will be graded by industry practitioners who are available to support participants in their learning journey, and/or by the Emeritus grading team. The final number of quizzes, assignments, and discussions will be confirmed closer to the start of the programme.

***Participants are responsible for arranging their own travel and accommodation for the on-campus networking sessions.

Programme Highlights

No prior coding experience

No prior coding experience

Programme designed for professionals without prior coding experience

Premium school experience

Premium school experience

Certificate from Asia’s Leading University

Industry relevant curriculum

Industry relevant curriculum

In-depth and comprehensive understanding of Machine Learning, Case studies developed by NUS School of Computing faculty and Emeritus

Distinguished faculty

Distinguished faculty

Learn via video lectures from renowned faculty at NUS School of Computing

Flexible mode of delivery

Flexible mode of delivery

Pre-Recorded Video Lectures* from NUS faculty with for self-paced learning interspersed with live lectures from renowned NUS faculty and industry practitioners

Live and interactive sessions

Live and interactive sessions

4 live sessions with faculty and 2 with industry experts

Campus immersion

Campus immersion

Participants will be invited to attend a 1-day networking opportunity to meet with fellow global leaders and interact with programme faculty/director

Capstone project

Capstone project

Toward the end of the programme, you will demonstrate your newly gained analytics skills by applying what you learned to build a simulation of real-life projects

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Modules on Generative AI Including Applications

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Gen-AI Masterclass and Live Case Study Discussions

Tools

SQLite

Excel Power Pivot

Excel Tables and Charts

Power BI Desktop

Orange Data Mining

DAX

Python

Jupyter Notebook

Pandas

Numpy

Seaborn

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Matplotlib

Scikit Learn

Scikit Learn

Tensorflow

Note: All product and company names are trademarks or registered trademarks of their respective holders.

Use of them does not imply any affiliation with or endorsement by them.

Programme Modules

The curriculum is organised into a 30-week programme that will be taught via video lectures from NUS faculty experts with more than 20 years’ experience in the field.

Segmented into 3 integrative sections, the programme aims to systematically equip you with the knowledge and skills you need to implement Machine Learning and Data Analytics to solve real-life problems and meet evolving needs of organisations.

Integrated with Generative AI(Optional)

  • Module 1: Introduction to Generative AI

  • Module 2: Generative AI Models

  • Module 3: Working with Generative AI

  • Module 4: Coding

Masterclass to address cutting-edge tools and latest developments

Note: *This programme is primarily self-paced online with some live sessions conducted by programme faculty. The availability of post-session video recordings is at the discretion of the faculty members, and Emeritus or the institute cannot guarantee their availability. We have a curated panel of distinguished industry practitioners who will conduct weekly live doubt-clearing sessions.

**Assignments will be graded by industry practitioners who are available to support participants in their learning journey, and/or by the Emeritus grading team. The final number of quizzes, assignments, and discussions will be confirmed closer to the start of the programme.

The bonus content on Generative AI is optional and does not count towards your final evaluation.

Case Studies

Marketing Analysis for a Sunglasses Retailer

Marketing Analysis for a Sunglasses Retailer

In this case study, the faculty demonstrates how to use data to provide insights on the potential customers of a sunglasses retailer.

Airlines Delay Data Analyis

In this demonstration, the faculty shows how to transform data on flight delays into a user-friendly interface.

Performance Analysis of Top 10 Tennis Players

In this case study, the faculty demonstrates the application of logical flow in programming using various statements in Python to the study the performance of athletes.

Movie Reviews Analysis

In this case study, the faculty demonstrates several operations on string data to organise and display audience feedback.

Hierarchical Clustering for a Data Set on Celebrities

Hierarchical Clustering for a Data Set on Celebrities

Through a lecture video, the faculty will show how to develop a system to cluster a dataset containing information on celebrities.

Boston Housing Dataset Analysis

In this demonstration, the faculty demonstrates the application of neural network concepts to identify the median value of houses in Boston based on input features.

Programme Goals

  • Developing Machine Learning Champions in future-ready organisations.

  • Productive and efficient implementation of Machine Learning to solve real-life problems.

  • Enabling competency in Machine Learning, including knowledge of Data Analytics and Python programming language.

Programme Faculty

Faculty Member DANNY POO
DANNY POO

Associate Professor

Dr Danny Poo is a tenured Associate Professor at School of Computing (SOC), National University of Singapore (NUS).

Dr. Poo is a member of the School’s Curriculum Committee t...

AMIRHASSAN MONAJEMI

Senior Lecturer (Educator Track)

Dr Amirhassan Monajemi is a Senior Lecturer with the School of Computing, National University of Singapore (NUS).

Before joining the NUS, he was with the Faculty of Computer ...

AI XIN

Lecturer (Educator Track)

Dr. Ai Xin is currently a Lecturer with the School of Computing at the National University of Singapore (NUS).

She has many years of experience teaching Artificial Intelligen...

Who Is This Programme For?

The programme is designed for professionals without prior coding experience*, from both tech and non-tech domains, who want to:

  • Pivot into a Machine Learning career

  • Acquire Machine Learning concepts and techniques to transition into Machine Learning roles

  • Gain the expertise to lead and solve real-world business problems with data and modelling at the core

The programme is particularly applicable to major industries such as IT Product & Services, Banking and Financial Services, Consulting, Education, Healthcare, and Retail, across sectors and functions.

Note: *Although no prior coding experience is required, non-tech participants are encouraged to put additional effort and complete the set of pre-readings provided to prepare for the course.

Programme Faculty for the live sessions might change due to unavoidable circumstances, and revised details will be shared closer to the programme start date.

Past Participant Profiles

Work Experience

Industries

Emeritus Career Services

Stepping into a business leadership career requires a variety of job-ready skills. Below given services are provided by Emeritus, our learning collaborator for this program. The primary goal is to give you the skills needed to succeed in your career; however, job placement is not guaranteed.

Emeritus provides the following career preparation services:

  • Resume building videos

  • Interview preparation videos

  • Linkedln profile building videos

  • Glossary of resume templates

Please note:

NUS or Emeritus do not promise or guarantee a job or progression in your current job. Career Services is only offered as a service that empowers you to manage your career proactively. The Career Services mentioned here are offered by Emeritus. NUS is not involved in any way and makes no commitments regarding the Career Services mentioned here

Certificate

Certificate

Upon successful completion of the programme, participants will be awarded a verified digital certificate by NUS School of Computing.

The Learning Experience

What is it like to learn with the learning collaborator, Emeritus?

More than 300,000 professionals globally, across 200 countries, have chosen to advance their skills with Emeritus and its educational learning partners. In fact, 90 percent of the respondents of a recent survey across all our programs said that their learning outcomes were met or exceeded. All the contents of the course would be made available to students at the commencement of the course. However, to ensure the program delivers the desired learning outcomes, the students may appoint Emeritus to manage the delivery of the program in a cohort-based manner during the course period the cost of which is already included in the overall Course fee of the course.

A dedicated program support team is available 7 days a week to answer questions about the learning platform, technical issues, or anything else that may affect your learning experience.

Limited seats are available.

Early registrations are encouraged. Seats fill up quickly!

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