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Data and Artificial Intelligence

“Big data” refers to datasets in large volumes, collected and analysed by organisations to reveal any critical trends, patterns, or associations. Such information is then typically used to extract meaningful consumer or market insights, helping companies make key business decisions.

Artificial Intelligence, or “AI”, is the capacity for machines to be able to perform work that typically require human thought – ranging from routine activities such as text editing, product packaging, and menial house cleaning to more complex tasks such as artwork creation or socialisation.

AIICT currently offers a variety of online courses in data science and AI, helping arm you with the core concepts, tools, and fundamental skills to navigate either sector. Explore basic areas of machine learning, data analytics, and cloud computing through our Certified Artificial Intelligence Professional course; data services and AI solutions through our Certified Data Science Professional course; and the skills to navigate Microsoft Azure’s databases through our Certified Data Analytics Professional course.


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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 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.

AIICT’s data and AI courses will explore all areas key to each field, with many in the specific context of Microsoft Azure and AWS’ cloud environments. Students will explore topics such as:

  • Core data concepts

  • Database concepts in the cloud

  • Cloud data services

  • Data analytics

  • Cloud computing fundamentals

  • Basic AI development

  • Natural Language Processing

  • Neural networks

  • Machine learning solutions

  • Navigating open-source software (i.e. R, Python, SQL)

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.

Though AIICT cannot guarantee any job outcomes, our data and AI courses offer a helpful starting point for those looking to enter the field.

Potential career paths include:

Data science. Professionals focused on developing the right tools and processes to mine, manage, and analyse “big data” are typically known as data scientists. Our courses in Microsoft Azure Data Fundamentals and general Data Science can help equip you with basic skills in navigating and managing databases; along with leveraging cloud services and AI solutions in data analytics.

AI development. If you’re more interested in improving the processes of data analytics (or general automation), then our AI certification can equip you with the fundamentals of machine learning and neural networks. AI developers are responsible for coding, testing, and deploying AI-based software used in data science or general business operations.

Database administration. With much of our programs focused on key data concepts; general data management and analysis; and navigating data services on the cloud – you’ll also build the fundamental skills required to pursue job opportunities as a database administrator. These professionals are responsible for ensuring efficient performance of an organisation’s databases; helping store, manage, configure, and secure such information.

Data and AI Courses in TechTalk

Why Study Data and AI?

As we venture into an increasingly digital era, the world of big data is only set to grow. Researchers estimate that we produce at least 2.5 quintillion bytes of data each day, and with our current pace of technological development – this number is bound to see exponential growth in no time.

Big data and AI work to bolster the other, with big data used to improve AI mechanics, and AI used to automate the routine tasks of data analysis. As our reliance on online platforms and information continue to grow, so will our production of digital data, boding high demand for data professionals in the years to come. Similarly, with automation not only necessary for big data, but for plenty other industries looking to innovate, AI professionals are bound to see in an increasing general need for their skills.

As such, big data professionals (also known as “data scientists”) are seeing great demand for their skills as organisations scramble to capitalise on our growing online information. The ability to collect, manage, and analyse large datasets has formed a core part of many business operations in order to improve productivity and profits – these including companies in Australia’s technology, finance, agriculture, and retail sectors. There’s never been a better time to explore the world of data analytics, and the area not only offers plenty of training options but provides great flexibility (industry-wise) in where you choose to take your career.

Deloitte statistics currently predict a 2.4% growth in employment between 2021-2022, with qualified professionals expected to earn an average of $130,176 AUD per year.

However, data science ventures have been made all the more possible through the use and development of artificial intelligence – another field bound to see rapid growth in the years to come. As mentioned, data and AI are mutually dependent sectors; as demand for one increases, so will demand in the other.

Australia currently faces a growing shortage in AI-related talent, creating plenty of high-paying job opportunities for those with a greater interest in the processes behind data science. CSIRO estimates the need for an additional 161,000 new AI specialists by 2030, funding programs that help tech graduates develop the job-ready skills they need to start in the field. Those entering the industry will thus find plenty of training opportunity as well as vacant roles – and with the limited talent pool, generous salary packages that currently sit at an average of $110,000 AUD per year.

However, the field of AI isn’t just limited to data science; the sector also offers the opportunity of working in various industries currently seeking innovative, automated technologies. This include sectors of healthcare, community services (i.e. aged care), and infrastructure. With 44% of Australian jobs expected to face automation in the coming decades, individuals are increasingly encouraged to code – or be coded.

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