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AI Career Pathway

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AI Career Pathway

AI Career Programmes

Target Audience: Career changers with no tech background

Duration: 104 Hours of structured, instructor-led learning (13 -15 weeks)

Outcome: Earn 6 industry-recognised certifications and gain the foundational skills needed to confidently begin a career in artificial intelligence.

From Concept to Capability
This pathway is crafted to guide learners with no prior experience, starting from understanding AI at a high level, then building essential data knowledge, advancing into real AI technologies, and finishing with modern cloud deployment.

Potential Job Outcomes : 
● Data Analyst
● Junior Machine Learning Engineer
● Junior AI Software Developer
● Junior AI Engineer
● AI Research Assistant

If you would like to learn more, please complete the form below and we’ll get in touch.

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1. Data Analyst

Work Content: Data Analysts are responsible for collecting, processing, and interpreting data to help organizations make informed decisions. Their tasks often include creating data visualizations, generating reports, and analyzing trends to provide actionable insights.

Skills Required: Proficiency in SQL for database querying, expertise in Microsoft Excel for data manipulation, and experience with data visualization tools such as Power BI and Tableau are commonly sought after. A strong understanding of statistical analysis and data modelling is also beneficial.

Entry-Level Salary Expectation: Entry-level Data Analysts in Australia can expect to earn between AUD $80,000 and $90,000 annually, depending on factors such as location, industry, and the individual’s skill set.

2. Junior Machine Learning Engineer

Work Content: Junior Machine Learning Engineers assist in developing and deploying machine learning models. They work on data pre-processing, model training, and evaluation under the guidance of senior engineers.

● Skills Required: Proficiency in Python, understanding of machine learning algorithms, experience with libraries like TensorFlow or PyTorch, and familiarity with data handling and pre-processing techniques.

Entry-Level Salary Expectation: Entry-level Machine Learning Engineers in Australia can expect to earn between AUD $114,000 and $136,250 annually.

3. Junior AI Software Developer

Work Content: Develop and maintain software applications that incorporate AI
functionalities, collaborate with cross-functional teams, and ensure software quality.

Skills Required: Proficiency in programming languages such as Python, understanding of software development principles, and familiarity with AI concepts.

Entry-Level Salary Expectation: Salaries typically range from AUD $65,000 to $80,000 annually.

4. Junior AI Engineer

Work Content: Assist in designing and implementing AI models, collaborating with senior engineers on various projects.

Skills Required: Proficiency in programming languages such as Python, familiarity with AI frameworks, and problem-solving abilities.

Entry-Level Salary Expectation: Approximately AUD $75,000 to $85,000 annually.

5. AI Research Assistant

Work Content: Support research projects by collecting data, conducting experiments, and analyzing results related to AI studies.

Skills Required: Strong analytical skills, experience with data analysis tools, and a basic understanding of AI methodologies.

Entry-Level Salary Expectation: Approximately AUD $60,000 to $70,000 annually.

What’s Included in Your AI Journey:
1. CompTIA AI Essentials
2. CompTIA Data+
3. PECB: Artificial Intelligence Professional
4. Microsoft Azure Fundamentals (AZ-900)
5. Microsoft Azure AI Fundamentals (AI-900)

The Certification Pathway:

1. CompTIA AI Essentials
Duration: 1 day
Content: Understand what AI is and why it matters
Explore real-world use cases and ethical considerations
Perfect for absolute beginners

2. CompTIA Data+
Duration: 5 days
Content: Learn data concepts, analytics, governance, and visualization
Essential data literacy for working with AI and ML models
Builds a strong foundation for AI logic

3. PECB: Artificial Intelligence Professional
Duration: 5 days
Content: Hands-on training in machine learning, NLP, AI ethics
Understand AI lifecycles and implementation strategies
Core AI technical and practical knowledge

4. Microsoft Azure Fundamentals (AZ-900)
Duration: 1 day
Content: Learn basic cloud concepts and Azure services
Understand computing, networking, storage, and security in the cloud
Enables cloud-based AI understanding

5. Microsoft Azure AI Fundamentals (AI-900)
Duration: 1 day
Content: Dive into AI-specific services in Azure
Includes machine learning, computer vision, NLP, and decision-making AI
Connects AI concepts with real-world cloud implementation