We live in a world that is data-driven, and data science is a growing and highly sought-after field that delivers numerous benefits for businesses. Naturally, this has led to a huge demand for graduates in data science across the globe. Here are 4 exciting careers for students in data science courses in Singapore to consider upon graduation.
1. Data Scientist
Data scientists are involved in designing modelling processes to create algorithms, predictive models, and performing custom analysis. They are continually on the lookout for new ways to make sense of data, with help from tools, automation systems, and data frameworks. Through processing and refining their data, data scientists provide invaluable insights on business in various ways, such as creating personalised customer experiences, helping companies make informed strategic decisions, as well as identifying areas to streamline operational costs.
Amity Global Institute features a Master of Science in Data Science programme for students in Singapore, designed to equip you with the specialist skills and knowledge across various environments that require data science. Students will learn topics such as Big Data and Business Intelligence, Machine Learning, as well as Data and Interactive Visualisation, amongst other topics.
2. Data Analyst
The rise of big data has resulted in vast data sets that require proper processing to be able to impact business decisions. Data analysts focus on sorting out these huge data sets, using a variety of tools to identify, collect, clean, analyse, and interpret data for practical insights. They are required to be familiar with database tools, various programming languages, data visualisation, as well as statistics and maths; and are employed in numerous industries such as business, healthcare, and government.
Amity Global Institute’s Master of Science Artificial Intelligence with Data Analytics programme is designed for graduates in Singapore to hone their specific expertise in both AI and data analytics, two highly in demand fields in data science. Some of the topics covered include Artificial Intelligence Ethics and Applications, Intelligence Decision Support Systems, as well as statistical and research methods to hone practical skills required in the industry.
3. Machine Learning Engineer
Machine learning (ML) refers to an application of artificial intelligence, focusing on the usage of data and algorithms to allow programs to imitate the way humans learn and grow over time. Machine learning engineers design and develop algorithms to facilitate the learning and operation of various programs, ranging from chatbots to virtual assistants and driverless cars. They also handle the training and retraining of predictive ML systems, improving operational efficiency and refining learning objectives for useful predictions.
Machine learning engineers play a key role in helping businesses to predict consumer purchasing habits and market trends, assists in accurate sales forecasting, as well as improve predictive maintenance in manufacturing. Generally, becoming a machine learning engineer requires years of experience, usually requiring a master’s degree. Data science courses in Singapore provide a strong foundation for students to understand key principles and skills to pursue this engaging and lucrative career path.
4. Data Engineer
Data engineers are involved in building data pipelines, which transform raw and unstructured data into an accessible format that data scientists and other specialists can conveniently use. They organise the collection, processing, and storing of data across different sources, create and maintain analytics infrastructure, and assist businesses by facilitating scalable analytics with increased data, along with data security and management.
Data engineers require a highly technical skillset, such as an in-depth knowledge of database systems such as SQL, various programming languages like Python and Java, as well as familiarity with ETL (extract, transform, and load) systems. Data science courses in Singapore provide the foundations for the technical skills needed to embark on a data engineer career, along with other careers in data science.
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