Certified Data Science Specialist
As Singapore moves toward a Smart Nation dream and having our lives flooded by large amount of information, but not all of them being useful data. Therefore, it is essential for us to learn how to applying data science to every aspect of our daily life from personal finances, reading, lifestyle to making business decisions. Leveraging on this data to make our life easier, or unlock new economic value for a business.
This course is a hands-on guided course for you to learn the concepts, tools, and techniques that you need to begin learning data science and managing big data. We will cover the key topics from data science to big data, and the processes of gathering, cleaning and handling data. This course is well balanced between theory and practical, and key concepts are taught using case studies references. Upon completion, participants will be able to perform the basic data handling tasks, collect and analyze data, and present them using industry standard tools.
Upon completion of this course, you will be able to:
- Identify appropriate model for different data types.
- Create your own data process and analysis workflow.
- Define and explain the key concepts and models relevant to data science.
- Differentiate key data ETL process, from cleaning, processing to visualization.
- Implement algorithms to extract information from dataset.
- Apply best practices in data science, and familiar with standard tools.
|Day 1 Introduction to Data Science
Life of a data scientist
Day 2 Beginning Databases
Structured Query Language (SQL)
Introduction to Python
Lab: Exploring data using Python
Day 3 Data Gathering
Instructor-led case study Exploratory Data Analysis
Introduction to R
Lab: Exploring data using R
|Day 4 Introduction Text Mining
Day 5 Presenting Data
Data Analysis Presentation
Lab: Mini Project Big Data Landscape
Big data Tools and Applications
This workshop is intended for individuals who are interested in learning data science, or who want to begin their career as a data scientist.
All participants should have basic understanding of data, relations, and basic knowledge of mathematics.