This Graduate Certificate in Industrial Automation and Machine Learning equips professionals with advanced skills in automation technologies and machine learning applications for career enhancement in engineering
This 6 month long Graduate Certificate in Industrial Automation and Machine Learning (GCML) is designed in consultation with industry experts and is designed to equip you with communication (oral and written) skills to investigate, analyse and present technical ideas, information and solutions on Industrial Automation and Machine Learning related problems and projects in a professional, independent and organised manner, individually and in teams, within the engineering domain.
Upon completion of this graduate certificate, graduates will be able to identify, critically analyse and creatively solve intellectually complex, specialised engineering problems in industrial process control systems, industrial automation and process control systems relevant to Industrial Automation, individually or in groups, underpinned by critical analysis, innovation, evaluation, synthesis, accountability, machine learning and sound engineering judgement of solutions relevant to the engineering domain. These programs are particularly beneficial for engineering practitioners who are looking to advance their careers by further validating their specialization within the field of industrial Automation Engineering and Machine Learning.
Course Benefits:
There is a global shortage of automation, instrumentation, Machine Learning and control engineers. Due to the rapid growth of new industries and technologies, industrial processes are becoming increasingly automated. Previously mechanized systems that required human intervention now use computerized control systems for higher accuracy, precision, and cost-effectiveness.
Industrial automation and Machine Learning are one of those expanding streams of engineering with an increasingly profound influence on most industries and enterprises. This graduate certificate will provide you with advanced skills in Industrial Automation and Machine Learning. Students with a background in electrical, mechanical, instrumentation and control, or industrial computer systems engineering can benefit from this program.
The content has been carefully designed to provide you with relevant concepts and the tools required in today’s fast-moving work environment. Our range of units cover in-depth knowledge of Automation fundamentals, networking, communication, Machine learning and program control strategies.
The program is composed of 4 units. These units cover a range of aspects to provide you with practical coverage in the field of Industrial Automation Engineering.
Please refer to the current teach-out program structure here.
Unit Number | Module/Unit Name (please ensure links are directing the correct unit outline) |
Duration (weeks) | Credit Points |
MIA500A | Industrial Automation Introduction | 12 | 3 |
MIA605A | Machine Learning for Industrial Automation | 12 | 3 |
MIA503A | Industrial Process Control Systems | 12 | 3 |
MIA510A | Industrial Data Communications | 12 | 3 |
(Deputy- Vishal Sharma)
Applicants are required to:
Applicants who hold a bachelor’s degree in a non-congruent engineering field are required to demonstrate their prior learning and experience is equivalent to the entry requirements (exact positions and roles that will be considered relevant are to be decided by each specialisation and will be considered on a case-by-case basis by the EIT Admissions Committee).
Applicants who do not hold a recognized bachelor’s degree are required to demonstrate their prior learning and experience is equivalent to this qualification. A minimum of an Australian Advanced Diploma (or equivalent) in Engineering and 5 years of technical work experience at a technologist level or above in a relevant engineering field is required for an application to be considered (exact positions and roles that will be considered relevant are to be decided by each specialization and will be considered on a case-by-case basis by the EIT Admissions Committee) **
Please note:
* Congruent field of practice means one of the following with adequate Industrial Automation Engineering content including programming, control and instrumentation (fields not listed below to be considered by the Dean and the Admissions Committee on a case-by-case basis):
** Applicants who enter and complete this qualification without holding a prior bachelor’s degree and go on to complete an EIT Master’s Degree may not be eligible for Engineers Australia recognition. However, students can lodge a personal application with Engineers Australia to be assessed on a case-by-case basis.
For full current fees in your country go to the drop down filter at the top of this page or visit the Fees page.
Payment Methods
Learn more about payment methods, including payment terms & conditions and additional non-tuition fees.
Like all Australian higher education providers and universities, EIT programs are accredited by the exacting standards of the Australian Government’s Tertiary Education Quality and Standards Agency (TEQSA).
This course is classified as Level 8 under the Australian Qualifications Framework (AQF).
Find out more about country-specific accreditation and professional recognition.
Potential job roles include engineering and management positions in the following areas of expertise:
Our Graduate Certificates takes 6 months to complete. The online graduate certificates are delivered on a part-time intensive basis over 2 terms, each of 12 weeks. Part-time students are expected to spend approximately 20 hours per week learning the program material, completing assessments and attending tutorials.After enrolment the maximum time allowed to complete all units is 3 years.
Any student has a right to appeal a decision of the Engineering Institute of Technology (EIT) or any member of the institute’s staff. EIT has a comprehensive Policy on Appeals and Grievances to assist students.
You must submit your application at least four weeks before the start date to be considered for your desired intake.