(SCTP) Advanced Professional Certificate in Data Science and AI (Classroom, Synchronous and Asynchronous e-learning) (Full-Time) (TA-eligible)
About This Course
According to a 2024 Forbes study on AI trends, the global AI market was valued at $136.55 billion in 2022, expected to grow at a compound annual growth rate of 37.3% from 2023 to 2030, reaching $1,811.8 billion by 2030. Singapore is one of the fastest-growing markets for AI talent in Asia-Pacific, with AI talent hiring rising 14% faster than overall hiring in 2022 (EDB, 2023).
This Advanced Professional Certificate prepares learners for careers in Data Science, Data Engineering, Machine Learning, and AI. Emphasising practical applications and hands-on experience, the programme equips learners to excel as data specialists in these rapidly evolving sectors.
The hybrid learning approach combines online and in-person classes with project-based learning, providing flexibility for career switchers in today’s fast-paced digital economy. Delivered by expert instructors and NTU faculty, the curriculum covers databases, Python programming, big data engineering, data analytics, and machine learning algorithms to meet the needs of Singapore's employers.
Graduates will gain the expertise and skills necessary for data analyst, data engineer, and data science roles. They will understand fundamental concepts in machine learning, AI, and data science, and be able to implement these principles practically. A portfolio of real-world projects will demonstrate their problem-solving abilities using advanced technologies.
Learners will engage in real-world case studies and capstone projects, addressing actual industry challenges. They will also have access to resources such as discussion groups, and mentorship from seasoned professionals.
In summary, this programme offers an exceptional learning opportunity for those seeking a career in AI and data science, equipping learners with the knowledge and skills to thrive in these dynamic industries.
What You'll Learn
At the end of the course, learners will be able to:
● Analyze and manipulate data effectively using Python and SQL.
● Create and manage databases for data storage and retrieval.
● Conduct exploratory data analysis to extract meaningful insights.
● Visualize data to communicate findings and trends.
● Apply data science techniques to solve practical problems.
● Deploy an ML model version via API or web app for inference or serving.
Entry Requirements
Familiarity with Python programming language, at a basic to intermediate level. At least an understanding of and ability to code the following concepts: variables, data types, operators, control structures, loops, built-in methods and functions, classes, and objects.