Data Science Course Questions

Data Science powered by Metis

Data science is the study of data. It draws from multiple disciplines, including mathematics, statistics, computer science, human-computer interactions and the visualisation of information. Data science extracts value from data to generate insights, analyse and solve problems, develop knowledge, and make informed decisions. Data science is now a critical component of businesses operations for many organisations, helping to drive strategy and gain an analytical advantage over their competitors in the market.

Data science is a broad field with a range of career opportunities and job roles across a multitude of industries. When starting a career in data science, it’s ideal to understand which area you want to pursue, so you can attain the essential skills and education requirements. It’s recommended you complete a course or qualification to develop skills and enhance your knowledge. Non-accredited data science courses and programs are available if you’re looking to start your data science career or upskill if you’re already working in the industry. Other qualifications range from bachelors degrees through to masters and doctorate degrees.


Kaplan Professional powered by Metis accelerates data science learning for individuals, companies and institutions through corporate training and online short courses. If you’re interested in data science and are considering upskilling or reskilling, the Beginner Python and Math for Data Science program is for beginners looking for an introduction to basic Python programming skills and mathematics. There are no prerequisites for this program, so you don’t need to have a high level of knowledge to enrol.

Demand for data science expertise is booming due to new technological capabilities that have enabled quantitative data to be transformed into practical business insights. Many organisations across a range of industries now see the integration of data and analytics as vital to their business operations. Data volume is also continuing to grow, with ninety percent of the world’s data created in the past two years.


This has meant data science has become a desired and attractive skill set, with statistical analysis and data mining ranking as some of the most in-demand skills requested by employers in posted job advertisements.


Importantly, data science isn’t just limited to the technology sector – there are opportunities in areas such as agriculture, cybersecurity, defence, health, finance, medicine, science and many more.

Metis is a leading data science educator, providing full-time immersive bootcamps, evening professional development courses, online training and corporate programs to accelerate the careers of data scientists.

Metis has over five years’ experience delivering data science courses in the United States, as well as more recent expansion of program delivery into Europe and the Middle East.

With over 1,600 graduates and counting, Metis was the first provider to receive accreditation from the Accrediting Council for Continuing Education & Training (ACCET) for their full-time, immersive Data Science Bootcamp.

Metis’ expert data science practitioners have advanced degrees from some of the world’s most distinguished educational institutions, coupled with practical experience gained from senior positions at powerhouse global firms.

There’s variation in the adoption of data science terms across businesses and industries. The below definitions can be used as a guide.

Data scientist

The term data scientist is used the most broadly. A job posting for a data scientist might describe a role identical to others calling for ‘data analyst’, although there are usually more diverse coding skills needed for the role.

Data scientists are asked to participate in the entire cycle of problems and solutions. They help identify opportunities for companies to use data, while also finding, collecting and integrating relevant data sources; performing analyses of varying degrees of complexity; writing code and creating tools that teams and businesses can use over time; and visually presenting the data to tell a story to company stakeholders.

Data analyst

A data analyst creates and communicates insights from data to measure outcomes, makes predictions and guides business decisions. Often, there’s a lighter coding burden placed on a data analyst, although they may be expected to know certain languages or packages in R or Python.

Data engineer

A data engineer is a designer, builder and manager of the information or ‘big data’ infrastructure. They develop the architecture that helps analyse and process data in the way the organisation needs it – and they make sure those systems are performing smoothly.

Python is a widely used and rapidly growing open-source programming language, commonly used by data scientists, data analysts and software engineers. Unlike Excel, Python is scalable, and is better able to meet business needs by readily handling massive data sets and accommodating the demands of real-time analysis and collaboration. In addition to being immensely popular, Python is a straightforward and user-friendly programming language, making it very easy to learn.

R is a highly popular programming language commonly used by data scientists, data analysts and statisticians. R is an important tool for data science and provides an environment that allows users to analyse, process, transform and visualise information to gain insights from data. It’s a popular statistical modelling language used for solving complex problems.

Research shows there’s growing demand for qualified individuals for positions in the data science field. This is largely driven by the exponential growth of available data and the narrow set of specific skills required to extract value from that data. Recent estimates suggest 2.5 quintillion bytes of data are created each year, with 90% of all data in existence being created in just the last two years1.  As a result, the number of data-related job postings has surged and median salaries have risen, leading to ‘data scientist’ becoming the best job in a 2016 Glassdoor survey based on the number of job openings, salary and job satisfaction1.

External data continues to validate the demand for the types of programs Metis offers. For example:

  • According to a recent global survey, 76% of businesses plan on increasing investment in analytics capabilities over the next two years1.
  • The most common salary for data scientists in Australia is between $120,000- $140,0002.
  • The projected job growth for data scientists in Australia between 2019 and 2024 is 12.9%2.


1 Deloitte Access Economics, 2018, The future of work: Occupational and education trends in data science in Australia.
Seek, 2020, How to become a Data Scientist- Salary, Qualifications & Reviews.

Kaplan Professional is joining forces with Metis to bring their highly successful data science courses to Australia with a local perspective.

The combination of Kaplan Professional’s trusted local presence and the global capability of Metis results in the delivery of world-class, live online data science courses that lead to learning, not just a transfer of information.

The live online courses are delivered by Metis’ renowned team of expert instructors who bring their deep industry experience directly into the classroom. With advanced degrees from institutions like MIT, Columbia, UC Berkeley and Northwestern, Metis instructors are also seasoned practitioners who’ve worked at leading global organisations in financial services, consulting, tech and more.

Unlike other online options, where sessions may be pre-recorded, the Metis live online format allows for direct interaction with the instructor, teaching assistant and other participants.

Our data science courses are 100% online and completely live, so it’s just like you’re sitting in the classroom. This means you’ll be able to interact directly with instructors and classmates in real-time, ask questions and participate in discussions. You’ll also have 24/7 access to the online class recordings if you miss a class or need to refer back.

Our instructors are world-class data science practitioners who bring their deep industry experience and will be available to support you throughout your learning process. You’ll also have access to Kaplan Professional’s knowledgeable Student Advice team, who are on hand to provide guidance and support throughout your study. To get in touch, simply send an email to or call 1300 368 372.

Beginner Python and Math for Data Science is designed for absolute beginners who have little to no prior data science experience and are considering a new career in the field. It provides an introduction to the basic Python programming and mathematical concepts essential to developing data science skills. This course is also ideal for those who need a refresher with fundamental Python programming and/or mathematic concepts to develop their data science skills or succeed at the next level.

Introduction to Data Science is designed for those who have a basic understanding of data analysis techniques. It provides a well-rounded introduction to the core concepts of basic machine learning and hands-on coding experience to help you take one step closer to becoming a data scientist.

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