In this data analytics course by WILEY, you will learn how to handle and derive actionable insights from data.
Classes focus on practical applications of data analytics so you start gaining experience in applying data analytics to real life situations even before getting certified.
At the end of the course, graduates will be certified as a professional data analyst with an industry-recognised certificate from WILEY.
Wiley Certified Data Analyst TSC Proficiency Level:
Analytics and Computational Modelling - Level 3
Data Engineering - Level 4
Data Visualisation - Level 3
Wiley Certified Data Analyst (CITREP+/FY21/CE/202105/006798)
Administered by the Infocomm Media Development Authority (IMDA), the CITREP+ funding support is eligible for Singapore Citizens and Permanent Residents. Valid for courses and examinations commencing from 1 April 2021.
Terms and conditions apply. Please visit go.gov.sg/tesacitrep for full details.
According to an Accenture study, 79% of enterprise executives agree that companies need to embrace Big Data to be sustainable in the long run.
A further 83% have pursued Big Data projects to seize a competitive edge.
The Wiley Certified Data Analyst course will be a mixture of e-learning content and in-person training by our WILEY Certified Instructors.
You will also work with enterprise-level projects to give you a deeper understanding of the topics.
At the end of the course, there will be an exam/assessment.
Upon passing, you will successfully earn an industry-recognised data analyst certification and the title of WILEY Certified Data Analyst.
(Includes one-time examination fee and non-subsidised GST)
All students who fail the certification examination must submit a non-subsidised retake fee of $214 before retaking the examination.
The Wiley Certified Data Analyst course includes a mixture of e-learning content and in-person training by our WILEY Certified Instructors.
In total, there will be eleven classes of 3 hours each and a 90 minute certification examination.
Module 1: Introduction to Big Data
Session 1: Introduction to Big Data
Session 2: Business application of Big Data
Session 3: Technologies for handling Big Data
Session 4: Understanding the Hadoop 2 Ecosystem
Session 5: Frameworks for Processing on Hadoop – MapReduce and YARN
Module 2: Understanding Analytics
Session 1: Understanding Analytics
Session 2: Analytical tools
Session 3: Exploring R
Session 4: Reading datasets into R, Exporting data from R
Session 5: Manipulating and Processing Data in R
Module 3: Data Analysis using R
Session 1: Using functions and packages in R
Session 2: Descriptive statistics in R
Session 3: Analysing data using functions, loops, and data frames, introducing Rhadoop
Session 4: Graphical analysis in R
Session 5: Hypothesis testing in R
Session 6: Statistical analysis on massive scale – Rhadoop and Mahout
Module 4: Big Data Analytics Methods
Session 1: Implementing a Big Data Solution
Session 2: Data Cleaning and Pre-processing
Session 3: Social Media Analytics and Text Mining
Session 4: Mobile Analytics
Session 5: Big Data Visualizations
Module 5: Machine Learning Foundations
Session 1: Introduction to Machine Learning
Session 2: Linear Regression
Session 3: Non-linear Regression
Session 4: Graphical Models and Bayesian Network
Session 5: Decision Trees
Module 6: Advance Machine Learning
Session 1: Cluster Analysis
Session 2: Artificial Neural Networks
Session 3: Support Vector MachineSession 4: Time Series
Module 7: Big Data Analytics – Technologies and Tools
Session 1: Storing Data in Hadoop 2 HDFS
Session 2: Working with MapReduce on YARN
Session 3: Working with YARN
Session 4: Exploring Hive
Session 5: Advanced Querying with Hive
Session 6: Analysing Data with Pig
- Spark and Scala Fundamentals
- Typical Interview Questions
- Case Studies:
- Big Data Business Problems and Solutions – Telecom Industry
- Big Data Business Problems and Solutions – Insurance Fraud Analytics
- Big Data Business Problems and Solutions – Credit Risk
- Big Data Business Problems and Solutions – Online Customer Segmentation
- Big Data Business Problems and Solutions – Use of Visualization Tools in e-commerce
Note: The certification examinations are not included in the class schedules. Learners are required to book their examination slots separately.
CLASS 1: 13 Jul - 20 Aug
Tues & Friday, 7pm - 10pm
@ Online (Class Full)
CLASS 2: 25 Jul - 29 Aug
Suns, 10am - 5pm (29 Aug 10am - 1pm)
@ Online (Closed registration)
CLASS 3: 28 Jul - 6 Oct
Weds, 7pm - 10pm
@ Online (Last Few Seats)
CLASS 4: 31 Jul - 11 Sept
Sats, 10am - 5pm (11 Sept 10am - 1pm)
CLASS 1: 23 Aug - 27 Sept
Mon & Thur, 7pm - 10pm
CLASS 2: 28 Aug - 2 Oct
Sat, 10am - 5pm (2 Oct 10am - 1pm)
What Our Students Say
Frequently Asked Questions
What is Data Analytics?
How does the Wiley Certified Data Analyst course differ from those provided by other providers?
What happens if my preferred class is fully booked? How do I get notified of new class openings?
What specifications are required of my computer for the class? Can I use a Macbook or Windows computer?
Any laptop that can connect to the internet and has minimum 8GB RAM can be used for the course.
Do I need to install any software beforehand? Is the software free?
I have no prior experience. Will I be able to understand the content taught in the courses?
Yes, but if you are worried about this, we encourage you to read the materials on your Learning Management System before each class to ensure that you can follow along.
How much time do I have to spend to self-read or self-study materials outside the course?
As this is a blended learning course, you are strongly encouraged to spend about 1 to 2 hours a week on the pre-readings.
Is this course very coding intensive?
The course teaches analytical thinking and skills to be applied on data. This focuses heavily on using coding to efficiently and effectively analyse data.
Does the certification expire? Do I have to renew it?
How does the Wiley Certified Data Analyst certification boost my resume?
I want to pursue a career in data analytics but have no prior experience. Is the Wiley certification able to provide the knowledge and skills I need to join the industry?
I have experience in the data analytics field. How will the certification benefit me?
Which companies recognise the Wiley certification?
When is the certification examination held? Is it on the last class?
How long is the certification examination?
Exam takers will have 90 minutes to complete 45 MCQs.
How difficult is the certification examination?
What is the passing rate for the examination?
The passing rate usually fluctuates between 93 to 96%.
What is the passing score for the examination?
You must achieve a score of 50% to pass.