Certified Artificial Intelligence Professional

6 months
Start ASAP
100% online learning
AWS Certified Cloud Practitioner, AWS Certified Data Analytics, AWS Certified Machine Learning, TensorFlow Developer Certificate

Course overview

Lumify Learn has introduced the new Certified Artificial Intelligence Professional course to prepare students for high-paying and rewarding jobs in artificial intelligence (AI) that are increasingly in demand all over the world, across a variety of industries and job roles.

The course includes valued and widely-recognised certifications from industry leaders AWS and TensorFlow and offers students the opportunity to learn about the most exciting and dynamic field in technology right now, with a high demand for skilled professionals across many industries, particularly in AI applications.

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The benefits of completing Lumify Learn's Certified Artificial Intelligence Professional Course

Get the foundation you need for a career as an Artificial Intelligence Professional using a variety of popular tools and gain valuable soft skills to get you ready for a high-paying and rewarding job.

The benefits of completing the Certified Artificial Intelligence Professional course:

Lumify Edge

Bridging the gap between learning and earning, Lumify Edge supports our students in their transition from study to their next IT role. Enhance our students’ personal brand ready for job interviews, direct access to exclusive Lumify Group job portal and internship opportunities.

Job Ready Skills

Earn certifications in high demand in Australian and Internationally – Fast.  Gain the skills you need to jumpstart your career in IT with our Learn-Practice-Test-Repeat approach. Fast tracking our students to success.


Discover the power of quality mentors. Our Mentors are experienced industry professionals who will guide you in your studies and help you to leverage your skills in real work scenarios.

Flexible Study

Study on your own schedule. Manage your studies around work and family while still enjoying your life. You even have the option to fast-track and finish your studies ASAP.

Course Structure

Certified Artificial Intelligence Professional
6 months
100% online learning
AWS Certified Cloud Practitioner, AWS Certified Data Analytics, AWS Certified Machine Learning, TensorFlow Developer Certificate

This course includes the fundamentals of cloud computing, core AWS services and will provide an introduction to security and architecture on the platform to help you prepare for the certification.

With this online course, you will use AWS services to design, build, secure, and maintain analytics solutions that provide insight from data.

This course will provide foundational knowledge of integrating machine learning into tools and applications. You will be able to build TensorFlow models using Computer Vision, Convolutional Neural Networks, Natural Language Processing, and real-world image data and strategies.

With this course, you will learn how to design, implement, deploy, and maintain Machine Learning (ML) solutions for given business problems.

  • Access to content sourced directly from AWS in partnership with Lumify Learn

  • Take your career to the next level with skill assessments to skill up in the job you want

  • Job-ready personal development skills

  • Challenges with step-by-step instructions and access to pre-configured AWS environments

Lumify Edge

Lumify Edge is designed to provide you with the tools you need to launch a fulfilling and well-paid IT career.

By enrolling in the course, you will be eligible to take part in Lumify Edge where we connect you with those recruiting for positions in the market along with Internship opportunities.

Learn more

Enrolment information

Basic understanding of statistics and mathematics or relevant experience in the industry is required for this program. However, even if you are relatively new to IT, with the right attitude and appetite to learn, you will be able to join the course.

You will begin your study in a cohort with your fellow students – from there, you will have twelve months to complete the course, entirely at your own pace.

Tech Requirements

While there are no prerequisites for the course, you will need to have access to a laptop or desktop computer with a reliable internet connection.

Lumify Learn accepts no responsibility for personal electronic devices that are utilised for the course and undertakes no responsibility to investigate their damage.


The course includes four exams across four certifications that need to be undertaken in-person at a testing centre near you, or in an online proctored environment. Exam fees are included in the cost of the course.

Lumify Learn provides you with exam vouchers in order to register for these exams.

What happens next?

A course advisor will call to chat about your course and set up a time for you to get started

You will then be invited to complete the Student Enrolment process to secure your spot in the course

Once your enrolment has been submitted, our Student Support Team will contact you to confirm your enrolment

If all your documentation is in order, you will then be invited to attend an online orientation

Payment information

Upfront Payment

RRP: $5,680

1. Pay upfront $4,544 fee.
20% discount - a saving of $1,136.

2. Talk to a Course Advisor to learn more about our 8-24 month payment plans.

ZipMoney: Study now, Pay later

Pay 18 or 24 monthly payments
Course total $5,680 + ZipMoney fees
For more information about ZipMoney CLICK HERE

The types of AI depend on functionalities and capabilities:


  • Narrow AI: Narrow AI, also known as weak AI, is a type of AI wherein learning algorithms only perform a single task. Any knowledge gained from completing that task will not be automatically applied to others. Examples of narrow AI include speech recognition, face detection, and chess playing.

  • General AI: Also known as artificial general intelligence (AGI) or strong AI, General AI is a type of AI that allows machines to learn, comprehend, and perform tasks humans. General AI mimics the human brain to solve complex problems.

  • Super AI: This a hypothetical type of AI that can surpass human intelligence and ability in every aspect. In theory, super AI would be able to create, understand, and learn things that humans cannot.


  • Theory of mind: In AI, theory of mind is the capability to attribute to others mental states like desires, intentions, and beliefs. Often using neural networks, theory of mind enables AI to predict and understand human behavior depending on inferred mental states, which is a critical aspect for interactions between humans and AI, and social understanding.

  • Self-awareness: In AI, self-awareness is a theoretical term that involves systems that possess a level of consciousness or self-recognition. This allows the systems to perceive and understand their own existence and possibly adapt their behavior depending on their self-assessment.

  • Reactive machines: These refer to AI systems that operate based on pre-defined rules and responses. These systems don't have the ability to learn from past experiences, and their actions are only determined by specific, programmed conditions.

  • Limited theory: Limited theory involves understanding a specific problem or domain area within the broader AI field. It involves developing theories and models designed to address particular issues without going for a comprehensive understanding of all AI aspects.

Data and AI professionals require high levels of both technical and non-technical skills.

Those in either field need a strong grasp of various programming languages, including (but not limited to) Python, SQL, Java, R, and C++. A strong knowledge of analytical tools is also necessary for data scientists, these including software such as SAS, Hadoop, Pig, Hive, and Spark. Artificial intelligence experts are expected to have an advanced knowledge of machine learning and deep learning, along with a close familiarity of programming frameworks such as TensorFlow, NumPy, and SciPy. Plenty of these technical skills may overlap between fields, helping you flexibly find work within either sector – though having experience in both areas can help bolster your opportunities on the job market.

Both professions require expertise in mathematics (i.e. algebra, statistics, probability), and excellent skills in communication, business planning, analytical thinking.

Being highly technical, complex tech fields, those looking to enter the data and AI industry are recommended to pursue formal training in either area. You’re more likely to gain employer attention with recognised certifications under your belt, along with a strong portfolio of your previous experience.

Those in data science are often encouraged to specialise. Though your skills are applicable to any field, employers will typically seek out industry-specific experience, making it critical to hone your skills in your preferred sector. As mentioned, having at least a basic concept of machine learning and AI can help boost your employment value in the field.

Those in AI are required to build their knowledge on computer science, deep learning, neural networks, and machine learning to start exploring entry-level opportunities in the job or internship market. Of course, a fundamental understanding of big data and data analytics can help broaden your horizons.

On top of formal education, aspiring data and AI experts are also encouraged to expand their skills through personal practice. Plenty of online communities exist to help you learn from and collaborate with other like-minded professionals, these including Stack Overflow, Kaggle, and Dataquest for those in data science; and GitHub, Global AI Community, and r/machine learning (Reddit) for those into AI.

Data refers to the information we produce through computer systems; from text, multimedia, and programs we create, to our communications and transactions via social media and online services. The term artificial intelligence refers to the development of 'smart' machines that, through the use of data, are able to simulate human-like tasks and behaviour, essentially achieving a simulation of human intelligence. Such technology is gaining widespread use in the impending age of automation, where AI systems are increasingly adopted to handle menial, repetitive business processes.

The two hold a symbiotic relationship, in which data science tactics are used to bolster the development of AI technologies. AI technologies, including natural language processing (NLP), are used to improve the processes of data science and analysis. Those working in the latter field are typically termed as 'data scientists,' who spend much of their time cleaning and extracting valuable insights from both structured and unstructured datasets. Those working in the former field are generally considered 'AI specialists' or AI developers, focused on the programming and science behind crafting 'intelligent' code or machinery.

Talk to an advisor

Request a callback from one of our advisors to ask questions or discuss about your study options.

100% online learning

Our industry-leading ICT courses and web-based learning environment are available to you 24/7.

Payment plans available

With a variety of payment plan options, you'll be able to find a plan that fits your budget.

Support every step of the way

Our team will make sure you finish what you start. Our Trainers, Mentors and Student Support Team will be there for you at every step.