The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events SpecialistBridging Business and Digital Transformation with Machine Learning and Data Analytics to accelerate competitive advantage.
Download Brochure29 March 2024
8 Months, Online
6-8 hours per week, 1 Day Campus Immersion (Optional)
US$4,199 and get US$415 off with a referral
Participants report that enroling in a programme with colleagues fosters collaborative learning and amplifies their impact.
Please provide your details to get more information about the group-enrolment pricing.
The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events Specialist
This new year, invest in a learning journey to upskill and gain a competitive edge.
Emeritus is collaborating with NUS School of Computing to help you unlock transformative career growth. Enrol before 29 March, 2024 using this code APAC100ALL5924 and get USD 100 program fee benefit. Limited seats to success available. Claim yours now.
WhatsApp an Advisor on +65 8014 3066
Have questions? Our Advisor will assist you promptly.
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.
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.
This section teaches you how to collect, organise, and analyse data to
a. provide insights on how a business is functioning
b. predict trends
c. identify areas for improvement
Week 1: Introduction to Analytics
This section provides hands-on experience on the most popular programming language in the data science world, Python Programming, to apply Python functions, operators, files, and packages for:
a. data evaluation
b. data visualisation
c. application development
Week 8: Getting Started with Python
This final section on Machine Learning covers the theoretical learning while emphasising on practical know-how needed to apply the techniques to generate impactful results.
While focusing on Advance models and implementation challenges, the section stands on 3 building blocks of Machine Learning namely
1. supervised learning
2. reinforcement learning
3. unsupervised learning
Week 18: Introduction to Machine Learning and Learning
In this case study, the faculty demonstrates how to use data to provide insights on the potential customers of a sunglasses retailer.
In this demonstration, the faculty shows how to transform data on flight delays into a user-friendly interface.
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.
In this case study, the faculty demonstrates several operations on string data to organise and display audience feedback.
Through a lecture video, the faculty will show how to develop a system to cluster a dataset containing information on celebrities.
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.
In an increasingly data-driven world where humans are producing and consuming about 94 zettabytes of data by the end of 2022, data is becoming integral part of every organisational decision, interaction, and process. Machine Learning and Data Analytics are giving rise to innovative business models and products, and present immense potential to bring transformative changes across business sectors and industries.
Machine Learning and Data Analytics could accelerate businesses’ competitive edge by analysing and processing data to obtain insights to make more accurate predictions and deliver innovative and strong business values.
A key component needed to excel in Machine Learning and Data Analytics includes knowledge and applications of programming languages.
Python is ranked as one of the most demanded programming languages in the workplace used not only by software developers but also by professionals in major industries including finance, healthcare, consulting and academia.
The Machine Learning and Data Analytics using Python programme by National University of Singapore’s School of Computing is curated with a strong emphasis on real-world relevance to meet rapidly evolving industry needs and trends.
The Programme’s holistic and integrative design will provide you not only with strong conceptual knowledge and applications of Machine Learning and Data Analytics but also strong market-ready coding skills and practical applications of Python Programming to deploy solutions and streamline core business processes to increase returns, to meet the evolving needs of organisations.
The Machine Learning Market is expected to grow from $21.17 billion in 2022 to $209.91 billion by 2029, at a CAGR of 38.8% in forecast period.
The Data Analytics Market Worth USD 346.24 Billion at a CAGR of 30.7% by 2030.
Python is the world’s most popular programming language and has reached an all-time high of 15.42% market share.
*The schedule of live sessions and profile of Industry experts is subject to change and confirmation will be provided post programme start.
Note: Programme Faculty for the live sessions might change due to unavoidable circumstances, and revised details will be shared closer to the programme start date.
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
● Interview guidebooks
● 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
Upon successful completion of the programme, participants will be awarded a verified digital certificate by NUS School of Computing.
Download BrochureFlexible payment options available.