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Microsoft Azure Data Fundamentals

5 weeks
17th October 2022
100% online learning
Microsoft Azure Data Fundamentals Certificate

Course overview

Our Microsoft Azure Data Fundamentals course will set the foundation for you to master data in the cloud. In this 5-week boot camp, you will complete online modules at your own pace and have the opportunity to join live sessions with our Microsoft Certified Trainers (MCTs).

This course will prepare you for the Azure Data Fundamentals certification exam from Microsoft, giving you the foundation you need to build your technical skills to start working with data in the cloud.

The benefits of completing AIICT's Microsoft Azure Data Fundamentals Course

Our Microsoft Azure Data Fundamental 5-week course is ideal for beginners to the database and professionals who want to learn what exactly Data is and what kind of services Microsoft Azure offers.

In this course, you will gain foundational knowledge of core data concepts and related Microsoft Azure data services. You will learn about core data concepts such as relational, non-relational, big data, and analytics, and build your foundational knowledge of cloud data services within Microsoft Azure. Explore Azure storage for non-relational data and the fundamentals of Azure Cosmos DB. Students will learn about modern data warehousing, real-time analytics, and data visualization.

This flexible learning program is designed to provide you with the knowledge and skills to take the Microsoft Azure Data Fundamentals Certification (DP-900) exam with minimal disruption to your work and life. The benefits of completing the AIICT Microsoft Azure Data Fundamentals 5-week course:

Flexible Study

Start together, finish whenever: start your study at the same time, then move through the course at your own pace.

Mentorship with industry experts

Connect with our carefully selected group of experts in the field, whose role is to mentor you through your course.

Multi-platform learning environments

Access a variety of tailored learning experiences, such as video content, quizzes, eBooks, practical activities, expert-led webinars, podcasts, Live Chat, networking, and research.



Industry Partner Program

On course completion, we’ll connect you with potential employers via our Industry Partner Program.

Course Structure

Microsoft Azure Data Fundamentals
5 weeks
100% online learning
Microsoft Azure Data Fundamentals Certificate

This course is aligned to the DP-900 Microsoft Azure Data Fundamentals certification exam. You will learn the fundamentals of database concepts in a cloud environment, get basic skilling in cloud data services, and build your foundational knowledge of cloud data services within Microsoft Azure.

After completing this course, students will be able to:

  • Describe core data concepts

  • Identify considerations for relational data on Azure

  • Describe considerations for working with non-relational data on Azure

  • Describe an analytics workload on Azure

  • Introduction to data concepts

  • Weekly live sessions with our Microsoft Certified Trainers

  • Practice Exam and Exam voucher

  • Discussion Forum and Trainer support

You will get tips and tricks, testing strategies, useful resources, and information on how to sign up for the DP-900 proctored exam. By the end of this course, you will be ready to sign-up for and take the DP-900 exam.​

This course is the first step to your Database journey and a precursor to the following exams:

  • Microsoft Azure Database Engineer

  • Microsoft Azure Data Analyst

  • Microsoft Azure Data Scientist

You might want to consider our Certified Data Science Professional course as the next step of your learning journey.

Enrolment information

The course requires no prerequisites; even if you are brand new to IT, with the right attitude and appetite to learn, you will be able to join the course.

Successful Azure Data Fundamentals students start with some basic awareness of computing and Internet concepts, and an interest in extracting insights from data. It is an advantage to have experience using a web browser, familiarity with basic data-related concepts, such as working with tables of data in a spreadsheet, and visualizing data using charts.

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.

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

Exams

The course includes one exam 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. AIICT provides you with exam vouchers to register for this exam.

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 which includes a Pre-Enrolment Profile

Once your enrolment process has been submitted, your course advisor will contact you

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

Payment information

Upfront Payment

Pay a once-off $850 incl. GST

If you have any questions about how payment plans work, simply reach out to our customer service team on 1800 515 110 or email us at [email protected].

FAQs

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.

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.

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. Artificial intelligence is the development of “smart” machines that, through the use of data, are able to mimic human-like tasks and behaviour. 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 development of AI technologies, while AI technologies 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 our simple payment plans, you only pay for what you study, making it simple and affordable to study ICT.

Support every step of the way

Our team will make sure you finish what you start, with support from ICT instructors and staff at every step.