1-Day Introduction to Data Science

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains.

Data science combines statistics, scientific methods, AI, and data analysis to extract value from data. It enables data-driven decisions, improved performance, and better customer engagement for companies. Statistics is crucial for advanced machine learning algorithms, translating data patterns into actionable insights for smarter decision-making and increased profitability.

This 1-day Introduction to Data Science course will equip you with foundational Data Science skills and prepare you for more advanced Data Science topics in future. Topics covered will include an introduction to data science, data science in an organization, tools and skills for data scientists, sources of data and types of data science work, data storytelling and presentation, Learners can expect to learn basic knowledge of data science and how it can be applied to the real-life!

Upon completion of the course, learners would be able to understand:

• The value of data – Data science ensures that you use pattern recognition in your data via algorithms to make predictions on that data (regression, classification, clustering). The 4 levels of data analytics are discussed including differences ad value to organizations. Data has a certain value and you need to understand what this is in order to make appropriate decisions
• Data science in action – Understand direct and indirect methods using data science models in the industry. Case studies and examples are used to show successful use cases of data science models to reduce costs, increase sales, better customer feedback and so on.
• Getting started – The opportunities for data science are out there – learn how to get started with popular programs and easy-to-use methods. Learn how to use data and optimize the patterns in the data to make predictions.

• A high-level overview of the above-mentioned topics with no technical details or jargon. Businessmen, marketers or investors who seek to understand how data can be used to generate money and/or business value are welcome.
• For beginners, no coding/programming or computer science background is required and those without any knowledge of data are also welcome.

"Very knowledgeable of the topics presented today. Delivered in an understandable manner. Shares his knowledge openly during the training." - Nurazlina

"Engaging speaker that is knowledgable, friendly and approachable." - Mohamed

Dwight graduated with a degree in Biotechnology (from NUS in 2001), Advanced diploma in Pharmaceutical management (from MDIS in 2007) and Masters in Education (from NTU in 2013). In 2014, Dwight ventured into Data Analytics and Database Management and picked up Statistics/Machine Learning, Big Data analytics, text mining & social media analytics and web applications. His other expertise includes data science programming languages such as R and Python. He is also deeply passionate in deep learning using sequential models and sequence to sequence models using Keras and h2oAI machine & deep learning platforms and libraries. He is also a Senior Data Analyst, where he performs data analytics and create predictive models using healthcare data.