Courses
Certified Data Science Specialist (CDSS)
Our lives are flooded by large amounts of information, but not all of them are useful data. Therefore it is essential for us to learn how to apply data science to every aspect of our daily life from personal finances, reading and lifestyle habits, to making informed business decisions. In this course you will learn how to leverage on data to ease life, 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. We will cover the key topics from data science to big data, and the processes of gathering, cleaning and handling data. This course has a good balance of theory and practical applications, and key concepts are taught using case study references.
Upcoming Training Dates
17 Feb - 21 March 2025
05 - 09 May 2025
18 - 22 August 2025
17 - 21 November 2025
* This training schedule is subject to change
Pass the 2-hour exam consisting of 50 Online Multiple Choice Questions with the score of 70% to earn this certification
One of the most industry validated digital skills certification in Asia. Course and exams is taken by the industries / academia / governments from 26 countries in Asia via 30+ Authorised Training Partners (ATP) and 50+ Authorised Academy Partners (AAP).
“Vendor-neutral” certifications refer to any certifications that are not directly associated with specific IT vendors. These certifications tend to develop a knowledge and skill base that is universally applicable and individual with skills that are more conceptual, setting you up to work with a greater range of products / tools.
Inquiry Form
Do you want to learn data science from industry experts? This certification course for data science offers just that! Data science is undoubtedly the gold mine of the present and future. It enables you to seek valuable information through data analysis and machine learning functions.
From deriving strategic business decisions, to unlocking new economic values for businesses, data science allows presentation of predictions derived from data evidence.
This Certified Data Science Specialist Certification (CDSS) combines a good balance of theoretical knowledge and practical application. Upon completion of this 5-day course, you will be capable of leveraging data and put yourself in the forefront of any business decisions.
- Knowledge on how to Identify the appropriate model for different data types
- Skills to create your own data process and analysis workflow
- Insights about key concepts and models relevant to data science
- Awareness of differentiating key data ETL process, from cleaning, processing to visualization
- Expertise in Implementing algorithms to extract information from dataset
- Best practices in data science, and become familiar with standard tools
- Identify the 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 algorithm to extract information from dataset
- Apply best practices in data science and become familiar with standard tools
Training Module
Introduction to Data Science (2 hrs)
• What is Data?
• Types of Data
• What is Data Science?
• Knowledge Check
• Lab Activity
Data Science Workflow (2 hrs)
• Data Gathering
• Data Preparation & Cleansing
• Data Analysis – Descriptive, Predictive, and Prescriptive
• Data Visualization and Model Deployment
• Knowledge Check
Life of a data scientist (2 hrs)
• What is a Data Scientist?
• Data Scientist Roles
• What does a Data Scientist Look Like?
• T-Shaped Skillset
• Data Scientist Roadmap
• Data Scientist Education Framework
• Thinking like a Data Scientist
• Knowns and Unknowns
• Demand and Opportunity
• Labor Market
• Applications of Data Science
• Data Science Principles
• Data-Driven Organization
• Developing Data Products
• Knowledge Check
Data Gathering (2 hrs)
• Obtain data from online repositories
• Import data from local file formats (json, xml)
• Import data using Web API
• Scrape website for data
• Knowledge check
Data Science Prerequisites (2 hrs)
• Probability and Statistics
• Linear Algebra
• Calculus
• Combinatorics
Beginning Databases (1.5 hrs)
• Types of Databases
• Relational Databases
• NoSQL
• Hybrid database
• Knowledge Check Lab activity
Structured Query Language (SQL) (2 hrs)
• Performing CRUD (Create, Retrieve,Update, Delete)
• Designing a Real world database
• Normalizing a table
• Knowledge Check Lab Activity
Introduction to Python (2 hrs)
• Basics of Python language
• Functions and packages
• Python lists
• Functional programming in Python
• Numpy and Scipy
• iPython
• Knowledge check
• Lab Activity
• Lab: Exploring data using Python
Data Preparation and Cleansing (2 hrs)
• Extract, Transform and Load (ETL)
•Pentaho, Talend, etc
• Data Cleansing with OpenRefine
• Aggregation, Filtering, Sorting, Joining
• Knowledge Check Lab Activity
Introduction to R (2 hrs)
• Packages for data import, wrangling, and visualization
• Conditionals and Control Flow
• Loops and Functions
• Knowledge check
• Lab activity
• Lab: Exploring data using R
Exploratory Data Analysis (Descriptive) (2 hrs)
• What is EDA?
• Goals of EDA
• The role of graphics
• Handling outliers
• Dimension reduction
Data Quality (2 hrs)
• Raw vs Tidy Data
• Key Features of Data Quality
• Maintenance of Data Quality
• Data Profiling
• Data Completeness and Consistency
Machine Learning (Predictive) (2 hrs)
• Bayes Theorem
• Information Theory
• NLP
• Statistical Algorithms
• Stochastic Algorithms
Introduction to Text Mining (3.5 hrs)
• What is Text Mining?
• Natural Language Processing
• Pre-processing text data
• Extracting features from documents
• Using BeautifulSoup
• Measuring document similarity
• Knowledge check Lab activity
Supervised, Unsupervised, and Semi-supervised Learning (2.5 hrs)
• What is prediction?
• Sampling, training set, testing set.
• Constructing a decision tree
• Knowledge check Lab Activity
Data Visualization (2 hrs)
• Choosing the right visualization
• Plotting data using Python libraries
• Plotting data using R
• Using Jupyter Notebook to validate scripts
• Knowledge check
• Lab Activity
Big Data Landscape (1.5 hrs)
• What is small data?
• What is big data?
• Big data analytics vs Data Science
• Key elements in Big Data (3Vs)
• Extracting values from big data
• Challenges in Big data
Data Analysis Presentation (2 hrs)
• Using Markdown language
• Convert your data into slides
• Data presentation techniques
• The pitfall of data analysis
• Knowledge check
• Lab Activity
• Group presentation Lab: Mini Project
Big data Tools and Applications (2 hrs)
• Introducing Hadoop Ecosystem
• Cloudera vs Hortonworks
• Real world big data applications
• Knowledge check
• Group discussion
What’s Next? (0.5 hrs)
• Preview of Data Science Specialist
• Showing advanced data analysis techniques
• Demo: Interactive visualizations
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