Program Overview

Data science is an interdisciplinary subject that analyses massive volumes of data using algorithms, procedures, and processes to find hidden patterns, provide insights, and guide decision-making. Data scientists utilise sophisticated machine learning algorithms to filter through, organise, and learn from structured and unstructured data to construct prediction models. Data science in Malaysia, a rapidly expanding field with applications in many sectors, offers a range of work options, from computing to research.

Data science has wholly changed several areas in our world. John W. Tukey’s work in 1962, “The Future of Data Analysis” revealed groundbreaking work on data science, which gained him international acclaim. Although John Tukey has had a significant impact on statistics, the most well-known quote ascribed to him is in the field of computer science. He was the one to coin the term “bit” as a shortening of “binary digit.” Only lately has the phrase ‘Data Science’ mainly referred to a new profession that is anticipated to make sense of the enormous warehouses of big data.

Almost all sides of business operations and policy profit from data science. For instance, it gives businesses knowledge about their clients to develop more effective marketing strategies and focused advertising to boost product sales. It helps with money and risk management, fraud detection, and equipment breakdown avoidance in factories and other industrial settings.

By enrolling in a data science course, you may learn how to apply technology to actual data science issues and get a thorough grasp of cutting-edge technologies, statistical analysis, and computational approaches. Here are some of the essential modules you will be expected to complete:

• Data Science Fundamentals
• Programming for Data Science
• Machine and Deep Learning
• Advanced Specialisation
• Business Specialisation

Data scientists add value to businesses by helping with product management and making well-informed decisions. The function includes a variety of tasks, which change according to the company’s requirements, resources, and size. Due to the immense breadth and significant overlap across data science professions, there is already enough ambiguity regarding the duties and obligations. Therefore, searching for data science jobs yields a few results for jobs in machine learning, data engineering, data analysis, development, and other related fields.

A highly qualified group of IT and prominent data specialists are behind every new technological advancement. Therefore, people who develop such technologies will have the most in-demand occupations in the future. The success criteria may alter, but data scientists have a promising future. Let’s look further into the study of data science in Malaysia.

Why Study This Program

Impact on Business Operations

Your influence as a leader in the field, both within your organisation and the rest of the world, might be one of the most compelling (at least globally) reasons to pursue a career in data science. You can strive to automate laborious operations within your organisation, saving the business time and perhaps thousands of dollars which could otherwise be dedicated to other projects. We’ll go through how businesses in contemporary industries are well aware of the immense value that their data scientists offer and how heavily they rely on them.

Data scientists are, therefore, ideally positioned to serve as organisations’ go-to strategists, whether they work for a smaller start-up or global powerhouses like Amazon, Apple, or Uber, all of whom are always looking for qualified data scientists. Although many data scientists work in the financial sector or for large IT companies, there are many other industries where you may apply your expertise in data science. The discipline of understanding human nature is where data scientists spend most of their time, looking at what makes people tick and why they don’t.

Data Science Skills Are Crucial

In an academic career, data science has shown to be highly beneficial for analysing research data. People research as computational materials scientists, examining vast amounts of data generated by computer modelling tools. By analysing this data, they can discover meaningful insights like unusual material features that make it suited for various applications, including medication delivery and design, solar energy harvesting, high-speed electronics, and biosensing. 

They also employ machine learning technologies to identify outliers and establish connections between specific material attributes across massive datasets. They have also produced high-quality visualisations of research data using data visualisation techniques. Data science knowledge allows scientists to analyse the pupils’ test results more effectively. To anticipate housing prices using variables like the number of rooms, square footage, age of the property, zip code, etc., they utilise skills in data science to construct models for their use, such as a mortgage calculator.

Increasing Demand

For most of the past decade, data science has been continuously ranked as one of the most in-demand areas, and this trend shows no signs of slowing down. In fact, until 2031, the U.S. Bureau of Labour Statistics (BLS) forecasts a 36% increase in employment in data science. So what about data science makes it such a sought-after career? Consider the most powerful and influential businesses on the planet. You probably immediately thought of business giants like Amazon, Google, Apple, or Facebook, which depend heavily on making decisions based on data.

A firm cannot exist today without implementing and developing a data-driven strategy based on popular apps. The demand for data scientists is still outpacing the supply. Thus there is a need and tremendous potential in the sectors connected to data science. However, the supply of data scientists continues to be relatively low. It is still a rather new and developing field, even in 2023, with significant demand in the future. 

A Successful Career

A data scientist makes 163% more money than the average worker. Due to this, a job in data science may be pretty rewarding. It is primarily a result of a significant pay bubble that the lack of data scientists has created. The learning curve is rather steep since studying data science requires knowledge and proficiency in some fields, including statistics, mathematics, and computer science. A data scientist, therefore, has a very high market value.

A data scientist’s job also depends on the industry in which the employing organisation specialises. For instance, a commercial sector will need a data scientist to examine its sales. A healthcare organisation will need data scientists to assist in analysing genetic sequences. A data scientist’s pay is based on their position and work. It also depends on the business’s size, established by how much data it consumes. The compensation for data scientists is still significantly higher than in other IT and management fields. Data science requires much effort and meticulous execution of kills.

Data Science is the Future

The occupation of the future is data science. Data-driven businesses are emerging, and new ideas are being created daily. Technology is now an ever-evolving sector, and as more and more people participate online, more data is generated. Industries need data scientists to help them make better decisions and provide better outcomes. Modern devices and apps interpret data as their power.

Being data-literate is becoming essential in today’s society. We need to understand how raw data may be turned into valuable goods. To analyse the data and derive insights from it, we must master the methods and comprehend the needs. To create valuable goods, the latent potential of data must be realised. Machine learning technologies make it possible to predict and correctly categorise data. The future may be accessed through big data and data science.

Why Study In Malaysia

Flexibility

Digital data and human understanding are combined in data science, which offers a surprising degree of employment flexibility. The freedom of a data science degree is one of its advantages. Graduates have two options: they may utilise technology to build tiny, narrowly focused businesses, or they can choose to work for well-known global companies. 

Since so many people and organisations want insights from Big Data, data scientists can also select their clientele. They could collaborate with businesspeople, advocacy groups for social justice, or even politicians. Thus, picking a professional path in data science that aligns with one’s interests and principles is simple.

Influential Experts

By studying data science, you can collaborate closely on your research project with several regional companies from various industries, including the ONS Data Science Camps. 

This implies that you can start networking and building contacts before you graduate. With this assistance, your research will continue at the cutting edge of new technologies and methodologies.

Affordable Course Fees

The fee required to study data science in Malaysia is comparatively less than that required in many other countries, such as the USA, the UK, Australia, and Canada, to name just a few. With data science degree expenses shooting up worldwide, Malaysia comes across as a reliable option to receive a high-quality education at an affordable cost.

Globally Recognised Degrees

Data science degrees from Malaysian universities enjoy global recognition. Studying data science in Malaysia allows students to pursue the program in Malaysia and then move anywhere globally. Several students continue their master’s and specialisation in Malaysia or transfer to other countries to pursue different pathways.

International Education Standard

The standard of data science programs in Malaysia meets international standards. This ensures exceptional education for students who enrol in this course. The course curriculum is rigorously developed, keeping in line with international benchmarks to ensure students learn the latest developments in data science. 

Excellent Campus Facilities and Infrastructure 

Malaysia offers excellent campus facilities, modern infrastructure, and innovative teaching aids for studying data science in Malaysia. The schools in Malaysia offer a great learning atmosphere. Several leading universities have developed in-house labs and testing facilities dedicated to helping students learn with hands-on experience, operate with state-of-the-art machinery, and stay up to date with the latest innovations.

Career Prospect

An analytics expert, a “data scientist,” is responsible for gathering, analysing, and interpreting data to support organisational decision-making. A mathematician, physicist, statistician, or computer programmer are just a few of the traditional and technical vocations the data scientist draws from. It combines scientific ideas with sophisticated analytics methods like machine learning and predictive modelling. Maths or statistics expertise is necessary for data scientists. Along with creativity and critical thinking, it’s also crucial to have a natural curiosity. To fully utilise the data, you need to be able to make connections between disparate pieces of information and have the drive to look for unanswered issues.

The roles and duties of a data scientist include gathering data from various sources, using machine learning tools to organise the data, processing, cleaning, and validating the data, looking for information and patterns in the data, developing prediction systems, clearly presenting the data, and making recommendations for strategies and solutions.

Here are a few more roles and responsibilities of a data scientist:

• Data collection and source identification.
• Analyse enormous volumes of organised and unstructured data.
• Construct strategies and solutions for corporate issues.
• Developing a data strategy in collaboration with the team and the leaders.
• Combining several algorithms and modules can help you find trends and patterns.
• Present data using a variety of tools and data visualisation approaches.
• Look into other tools and technology for creating creative data strategies.

You must be able to collect data, analyse it, and then explain your results to become a data scientist. This covers hard skills like teamwork and public speaking and soft skills like programming, database manipulation, sophisticated mathematics, and data visualisation.

Listed below are some of the skills you must have to have a career as a data scientist:

• Principles of data science.
• Deep understanding of mathematical topics like probability and statistics.
• Programming language expertise.
• Knowledge of machine learning and experience with data extraction, transformation, and loading.
• Excellent problem-solving capabilities and a deep understanding of data structures and algorithms.

Data Analyst

A Data Analyst’s responsibility is to study data to regulate market drifts. They assist in painting a clear picture of the position of the business in the marketplace. When a corporation defines the intended goal, a data analyst offers datasets to accomplish the targeted goals.

Data Engineer

Data engineers and mathematicians can further examine trends and patterns for interpretation using systems that automatically gather, store, manage, and analyse large amounts of data. They make the material easier to understand so that it may be used to a client’s or company’s advantage.

Business Intelligence Analyst

Business intelligence analysts’ primary responsibility is to evaluate and explain historical data and patterns. Data scientists elaborate on such data to develop future predictions or hypotheses to help distinguish between the two.

Machine Learning Engineer

Engineers that specialise in machine learning produce software and build data pipelines. They often require a solid foundation in software engineering and programming and statistical expertise. They are tasked with creating machine learning systems and performing tests and experiments to evaluate the efficiency and effectiveness of such systems.

Data Architects

Data architects design data management and organisation solutions. For data scientists to work with the trends and patterns, an architect will consider a company’s strategy for resolving a specific issue and build a system that processes and presents information.

Data Administrator

The organisation’s database system is maintained and operated by a database administrator. They create backup and recovery plans and are in charge of managing and storing data safely and securely. Defined, they are in charge of managing and operating a company’s database system daily.

Applications Architect

Observe how business apps behave and engage with customers and other applications. Applications architects are primarily concerned with creating the architecture of applications, which includes developing infrastructure and UI elements.

Marketing Analyst

To evaluate the success of marketing efforts, adjust campaigns, and gather information for the next campaigns, marketing analysts look at sales and marketing data. Technology has revolutionised many industries, including marketing. It offers a wealth of specific insights marketers can utilise to optimise their efforts.

Data Mining Specialist

A data mining professional is responsible for spotting patterns and linkages to assist a business in forecasting future behaviours. A data mining expert may assist firms in making better informed, data-driven choices by converting data into insights. A data mining professional employs statistical tools to aid with research, data mining, and connection modelling to achieve this.

Cloud Infrastructure Architect

Ensure that all business systems operate as efficiently as possible and can accommodate the growth of new technologies and system needs. Cloud Infrastructure Architect manages a company’s cloud computing strategy and has a similar job title.

Program Duration

The duration to study data science in Malaysia is three years for the bachelor’s program. English is the medium of instruction followed in schools across all major international private universities. 

The first year will have a number of common subjects between different specialisations. As students progress to years two and three, their modules and subjects will become more specialised as per their field of choice. 

Students can sometimes switch from one specialisation to another, but it will require approval from the University faculty and the relevant authorities in Malaysia.

Students who want to opt for program transfers to another University will usually need to prepare the transfer paperwork and start processing from their second year onwards to ensure all the paperwork and approvals are in place so the program transfer can be done.

Entry Requirements

The Malaysian Qualifications Agency (MQA) sets the entry requirements and guidelines for university admissions in Malaysia, which all universities must adhere to. All prospective international students must meet the minimum entry requirements, as the Ministry of Higher Education (MOHE) takes these standards into account during the application acceptance and processing phases.

The admission requirements to study data science in Malaysia for international students may vary from one university to another. However, the basic entry requirements are the same for most universities. 

Usually, there are two pathways to entering a degree program in Malaysia:

• First, students can join a foundation program after completing their secondary schooling, O levels, or equivalent qualifications. After completing the foundation in the information technology/computing program, they can continue to the bachelor’s degree as per their choice.
  
• Second, students who have completed their higher secondary school or A levels or equivalent will be able to join the bachelor’s degree programme directly into year one. 

If a student fails to meet the entry requirements for a bachelor’s degree programme, the faculty may offer different pathways into the degree programme, for example, through a foundation or a diploma programme. 

Universities may raise the entry requirements to ensure incoming students are academically prepared for the rigours of their programmes. So, prospective international students should consult with an admission advisor to determine the precise entry criteria for their chosen programme and their preferred university.

General Entry Requirements For Bachelor’s Degree

A Levels or Equivalent:

• 2 Passes in A-Level in Science stream with a Pass in Mathematics and one Science or ICT subject. Or 
• 2 Passes in A-Level with a Credit in Additional Mathematics at IGCSE/O-Level or equivalent. Or 
• 2 Passes in A-Level with a Credit in Mathematics and Science or ICT subjects at O-Level/IGCSE or equivalent. Candidates need to do a Prerequisite module in Further Mathematics or equivalent in the first semester of the Degree Programme.

Foundation: 

• Passed the relevant Foundation programme (minimum CGPA of 2.0).

English Language

International students who wish to study data science in Malaysia will need to also provide proof of their English language proficiency with IELTS or TOEFL exams. Students who have studied the British or American curriculum are generally exempted from the English proficiency requirements since the medium of instruction for that curriculum is in English by default. 

Students who have studied other curriculums where the medium of instruction is also English will usually need to provide a supporting letter from the school stating that the instruction language for their schooling has been English. With that letter, English language requirements are proven to have been completed.

Fees & Cost

Students sometimes only look at the tuition fee during the comparison. However, depending on how forthright and clearly the fee guidelines from the university are, the extra fees can be a hefty amount that could be a surprise. So students are advised to correctly add all the fees and decide which university fits their budget requirements to study data science in Malaysia. 

Various factors will contribute to the overall cost structure, such as:

• Tuition fees
• Accommodation fees
• Admission fee
• Registration and Visa fees and
• Other one-time fees.

These fees vary from university to university and can depend on varying factors. The quality, infrastructure, facilities and teacher-to-student ratio will also determine how much a university charges.

You must find the right balance between quality and cost to get the best education possible. The average cost to study data science in Malaysia is between RM30,000 to RM40,000 per year, depending on the University.

For reference, that’s around USD $7,500 to $10,000 per year for a 3-year data science degree program at the current exchange rate.

Accommodation

Accommodation cost is going to be another recurring fee for international students. Generally, students have two options: they can either stay at the on-campus accommodation provided by the university or at private accommodation. The prices will differ according to which university and area you choose.

Generally, campus accommodations at major universities start at around US$150 per month and can go up to $400 per month. The pricing for on-campus accommodation is determined by the size of the room, whether a student will be sharing the room or will be staying alone, or if the student is taking a master room which generally comes with an attached bathroom or decides to stay at a sharing room with shared bathroom.

Some universities also offer cooking facilities and on-campus accommodation, which are shared facilities which will also be factored into the accommodation costs. Utility costs are generally an add-on fee.

While choosing the university, you can check with your admissions advisor on the options available for accommodation and how much they will cost so that you have an idea of how much of a monthly budget you will require as a student.

Admission Procedure

Researching, applying and managing overseas admissions is a tedious, time-consuming and often confusing process. Incorrect application submissions can lead to lengthy processing, delayed approvals, or rejections. You can visit education, exhibitions and fairs to collect information. However, that is not enough. You can only collect cursory information at these places. However, your admission processing will usually take much longer. During that time, you will need consistent and dedicated support to ensure your application is in the right experienced hands.

This is where we help.

Edmates helps international students from around the world with complete admissions processing. Our integrated one-stop centre helps international students with everything. We help you find future-driven programs that match your abilities and interests in leading universities.

We handle the entire process from the beginning until you have joined the university. Our international support system will manage everything for you, absolutely free.

Each student is assigned with a dedicated admission advisor who will manage the complete admission process and also guide the student throughout the admissions process. The advisor will also liaise with the university admissions department to ensure clear communications and faster processing.

You can speak with your assigned advisor anytime by booking a free call online through the website. You will also receive regular updates regarding your application via emails, SMS and WhatsApp.

To learn about each step of the admission process, you can read our complete guide to start applying for your higher education the right way.