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  • Applied Data Science for Innovation
MICROCREDENTIAL

Applied Data Science for Innovation

Enrol now

Learn how to solve challenging business problems and drive innovation by mastering the essentials of machine learning with one of the industry’s leading data science experts.

About this microcredential

This interactive course will teach you how to design and implement innovative machine learning solutions to solve complex real-world problems. With the advent of a new digital era, businesses are facing increasingly challenging and complex problems. Smart organisations that can successfully leverage value from their data gain unparalleled competitive advantages – with machine learning widely used across many industries, such as financial services, healthcare and telecommunications.

You will learn essential machine learning techniques in depth, such as regression, classification, and clustering. Featuring a uniquely transdisciplinary approach to learning, this microcredential will also introduce you to agile project management, entrepreneurship and data citizenship that will prepare you to tackle complex problems in the future, providing transferrable skills across a broad range of industries, sectors and organisations.

This dynamic, innovative approach, combined with hands-on learning and practice will help you to become well versed in implementing, optimising and maintaining machine learning solutions that can disrupt industries and change people’s lives for the better.

Whether you’re keen to unlock new career opportunities or help your organisation develop more strategic, innovative initiatives, this microcredential will help you master the latest thinking and best industry practices in data science and become an invaluable contributor in whatever field you work in.

This course has been co-designed by renowned academics and industry partners from the UTS Master of Data Science and Innovation program. 

Key benefits of this microcredential

This microcredential aligns with the 4 credit point subject, Applied Data Science for Innovation (36113) in the Master of Data Science and Innovation. This microcredential may qualify for recognition of prior learning at this and other institutions.

Who should do this microcredential?

This microcredential is suitable for anyone interested in learning more about machine learning, such as:

  • Business analysts
  • Data analysts
  • Developers
  • Entrepreneurs
  • Project managers
  • Product owners.

 

The concepts and intuition behind all algorithms were explained very clearly. The weekly assignments are well paced, and gradually lead me to more and more advanced areas. The detailed and constructive feedback is tailored to me and my progress, which is something that other online classes I’ve done could not provide. I highly recommend this course to people who would like to get into ML field with none or little prior knowledge.

Kai-Ping Wang, Senior Software Engineer at Sandstone Technology

Price

Full price: $3,142 (GST free)*

*Price subject to change. Please check price at time of purchase. 

Discounts are available for this course. For further details and to verify if you qualify, please check the Discounts section under Additional course information. 

Enrolment conditions

  • Course purchase is subject to UTS Open Terms and Conditions. 

COVID-19 response 

  • UTS complies with latest Government health advice. Delivery of all courses complies with the UTS response to COVID-19.

Additional course information

Course outline

This course consists of weekly 3-hour evening classes (Wednesdays, 5.30pm-8.30pm) over six weeks, with participants also needing to undertake approx. 2-3 hours weekly self-directed online learning activities.

The following content will be covered during the microcredential:

Introduction to Python programming

  • Installation and setup
  • Data structures
  • Conditions and loops.

Running machine learning projects

  • Different types of learning
  • Machine learning approaches for tackling business problems
  • Machine learning and Agile methodology.

Exploring data

  • Descriptive statistics
  • Visualising data
  • Identifying and fixing issues
  • Feature engineering.

Machine learning algorithms

  • Univariate and multivariate linear regression
  • Logistics regression
  • K-Nearest Neighbors
  • Decision tree
  • Random forest
  • K-means.

Optimising machine learning

  • Model evaluation
  • Assessing underfitting and overfitting
  • Hyperparameter tuning
  • Model interpretation.

Deploying machine learning solutions

  • Lifecycle of machine learning models
  • Machine learning pipelines and artefacts
  • Machine learning as a service.

Course delivery

This course offers in a series of weekly, interactive online sessions facilitated by a leading industry expert. Each session consists of a mix of subject presentations and hands-on experience. Participants will be able to learn the theory behind machine learning algorithms and data mining techniques followed by practical workshops, where they will apply what they've learnt to real-world business use cases.

In between sessions, participants will be required to engage in individual and collaborative online activities designed to support the understanding of the machine learning algorithms and their application.

Course learning objectives

By the end of the microcredential you will be able to:

  • Understand the different elements of machine learning
  • Manage a machine learning project end-to-end
  • Analyse datasets and propose relevant approaches
  • Assess model performance and make recommendations
  • Train machine learning models
  • Communicate and present results.

Assessment

Assessment task one - Machine learning project

  • Type - project
  • Group work - individual
  • Weight - 60%.

Assessment task two - Hackathon

  • Type - report
  • Group work - group and individually assessed
  • Weight - 40%.

Requirements

Mandatory

  • To complete this online course, you will need a personal computer with adequate internet access and sufficient software and bandwidth to support web conferencing. You will also require an operating system with a web browser compatible with Canvas.

Desired

  • Exposure to programming, data analysis or statistics.

Discounts

Discounts are available for this course as follows: 

  • UTS alumni/students 10% discount with voucher code: TDIalumni 
  • UTS staff 10% discount 

Discounts cannot be combined and only one discount can be applied per person per course session. Discounts can only be applied to the full price. Discounts cannot be applied to any offered special price. 

How to enrol and obtain your UTS staff discount (UTS staff)

  • Please contact the team at support@open.uts.edu.au in order to secure your enrolment and 10% staff discount.

How to apply your discount voucher 

  • If you are eligible for a UTS alumni or student discount, please ensure you have provided your UTS student number in your UTS Open Profile (under “A bit about you”). If you are an alumni and have forgotten your UTS student number, email support@utsopen.uts.edu.au with your full name, UTS degree and year of commencement.  
  • Add this course to your cart 
  • Click on "View Cart" (blue shopping trolley at top right of screen). You will need to sign in or sign up to UTS Open 
  • Enter your eligible code beneath the “Have a code?” prompt and click on the blue "Apply" button 
  • Verify your voucher code has been successfully applied before clicking on the blue "Checkout" button. 
$2,869.00

START DATE

08 June

MODE

Online

DURATION

6 wks

COMMITMENT

Avg 14 hrs/wk
Enrol now

Make an enquiry

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Meet the expert

Aneesh Chivukula

Aneesh Chivukula

Aneesh holds a PhD in data analytics and machine learning from the University of Technology Sydney, Australia. He holds a Master Of Science by Research in computer science and artificial intelligence from the International Institute of Information Technology Hyderabad, India. His research interests are in computational algorithms, machine learning, data mining and data analytics. Aneesh has industry experience in research engineering and product development of machine learning algorithmics. As an analytics executive, he has developed enterprise solutions with artificial intelligence in the open source, Cloud, Big Data & DaaS marketspaces. He has worked in application domains such as e-Governance, internet of things, capital markets, corporate finance, personalized marketing, news media, Ecommerce and CPG.

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Book a session

Thu 08 Jun 2023 -
Thu 13 Jul 2023
Expert: Aneesh Chivukula
  • This course runs on Thursday evenings at 5.30-8.30pm, and will be facilitated online via Zoom video sessions. Learners will also need to undertake approximately 2-3 hours of self-directed online learning activities during the week. Assessments may be due throughout the final week of the course. Click on ‘Sessions’ information below to see the live Zoom session dates.
  • Online
  • 6 sessions, 18 hours total
    Date
    Time
    Location
    Notes
    Thu 08 June 2023
    5.30pm-8.30pm
    Online via Zoom
    Thu 15 June 2023
    5.30pm-8.30pm
    Online via Zoom
    Thu 22 June 2023
    5.30pm-8.30pm
    Online via Zoom
    Thu 29 June 2023
    5.30pm-8.30pm
    Online via Zoom
    Thu 06 July 2023
    5.30pm-8.30pm
    Online via Zoom
    Thu 13 July 2023
    5.30pm-8.30pm
    Online via Zoom
$2,869.00
Error occurred while adding to cart

To complete this online course you will need a personal computer or device with a reliable internet access and an operating system with a web browser compatible with Canvas and Zoom.

Enrolments are scheduled to close Thursday, 1 June 2023, 11.59pm (AEST).

Wed 08 Nov 2023 -
Thu 14 Dec 2023
Expert: Aneesh Chivukula
  • This course runs on Wednesday evenings at 5.30-8.30pm, and will be facilitated online via Zoom video sessions. Learners will also need to undertake approximately 2-3 hours of self-directed online learning activities during the week. Assessments may be due throughout the final week of the course. Click on ‘Sessions’ information below to see the live Zoom session dates.
  • Online
  • 6 sessions, 18 hours total
    Date
    Time
    Location
    Notes
    Wed 08 November 2023
    5.30pm-8.30pm
    Online via Zoom
    Wed 15 November 2023
    5.30pm-8.30pm
    Online via Zoom
    Wed 22 November 2023
    5.30pm-8.30pm
    Online via Zoom
    Thu 30 November 2023
    5.30pm-8.30pm
    Online via Zoom
    Thu 07 December 2023
    5.30pm-8.30pm
    Online via Zoom
    Thu 14 December 2023
    5.30pm-8.30pm
    Online via Zoom
$2,869.00
Error occurred while adding to cart

To complete this online course you will need a personal computer or device with a reliable internet access and an operating system with a web browser compatible with Canvas and Zoom.

Enrolments are scheduled to close Wednesday, 1 November 2023, 11.59pm (AEST).

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Applied Data Science for Innovation Applied Data Science for Innovation
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