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Certified Data Analyst
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Wiley Certified Data Analyst
2021 Intake
Open For Registration
Analytics
Track
Review
Course Descriptions
Learn data analytics skills from a curriculum curated from thorough market research and consultations with top companies around the world. Our expert trainers will provide quality instruction and insights from their decades of industry experience.
The Wiley Certified Data Analyst program will make you thoroughly conversant with basic and advanced analytic techniques for mining, manipulating, and analyzing Data, familiarize you with key Data platforms, and provide foundations to business and industry requirements to be able to participate productively in Data analytics projects.
By equipping yourself with the internationally recognized Wiley Certified Data Analyst certification, you gain a valuable key that opens the doors to exciting opportunities and the ability to flourish at work regardless of your industry.
Instructor
Andy was earlier a Senior Assistant Director at MCI formulating and reviewing manpower policies in the infocomm and media sectors.
Prior to that, he was working at NUS Entrepreneurship Centre grooming start-ups and helping aspiring entrepreneurs to fulfil their aspirations.
Andy have also spent a number of years in the Infocomm Development Authority (IDA) facilitating Tech SMEs to develop innovative products that could help them scale and grow beyond the local shores.
Andy Tai
Course Page
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Certification
The certificate is internationally recognised by most, if not all companies.
In their 200 years of publishing and research, Wiley has established themselves as a provider of high quality content that benefits academia, businesses and governments worldwide.
In the Asia-Pacific region alone, Wiley is the co-chair of the Project DARE (Data Analytics Raising Employment) Advisory Group, and thus has a close working relationship with academics, businesses and governments of 14 APEC member economies.
For more information about Project DARE, please refer to https://www.apec.org/Press/Features/2017/0620_DSA.
REAL-WORLD APPLICATION
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.
COURSE STRUCTURE
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.
CERTIFICATION
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.
Curriculum
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.
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INTRODUCTIONIntroduction What is AI good for?
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GRAPH-SEARCH ALGORITHMSBreadth-first search introduction Breadt-first search implementation Depth-first search introduction Depth-first search implementation I - with stack Depth-first search implementation II - with recursion Enhanced search algorithms introduction Iterative deepening depth-first search (IDDFS) A* search introduction
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BASIC SEARCH & OPTIMIZATION ALGORITHMSBrute-force search introduction Brute-force search example Stochastic search introduction Stochastic search example Hill climbing introduction Hill climbing example
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META-HEURISTIC OPTIMIZATION METHODSHeuristics VS meta-heuristics Tabu search introduction Simulated annealing introduction Simulated annealing - function extremum I Simulated annealing - function extremum II Simulated annealing - function extremum III Travelling salesman problem I - city Travelling salesman problem II - tour Travelling salesman problem III - annealing algorithm Travelling salesman problem IV - testing Genetic algorithms introduction - basics Genetic algorithms introduction - chromosomes Genetic algorithms introduction - crossover Genetic algorithms introduction - mutation Genetic algorithms introduction - the algorithm Genetic algorithm implementation I - individual Genetic algorithm implementation II - population Genetic algorithm implementation III - the algorithm Genetic algorithm implementation IV - testing Genetic algorithm implementation V - function optimum Swarm intelligence intoduction Partical swarm optimization introduction I - basics Partical swarm optimization introduction II - the algorithm Particle swarm optimization implementation I - particle Particle swarm optimization implementation II - initialize Particle swarm optimization implementation III - the algorithm Particle swarm optimization implementation IV - testing
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MINIMAX ALGORITHM - GAME ENGINESGame trees introduction Minimax algorithm introduction - basics Minimax algorithm introduction - the algorithm Minimax algorithm introduction - relation with tic-tac-toe Alpha-beta pruning introduction Alpha-beta pruning example Chess problem
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BUILDING TIC-TAC-TOEAbout the game Cell Constants and Player Game implementation I Game implementation II Board implementation I Board implementationj II - isWinning() Board implementation III Minimax algorithm Running tic-tac-toe
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INTERVIEW: SINGAPOREAN EXPERTBackground of Expert Information and Communication Technology in Singapore
Comprehensive Resources
Study Materials
Provided as printed resources STUDY MATERIAL or PDFs, these consist of the entire learning material covered in the curriculum.
Videos
These help you understand the core essential concepts in a media‐rich format.
Online Lab
Your course resource includes the Virtual Lab Environment, which ensures you have the required tools and datasets for labs available at your fingertips.
Project Work
To enable you to work on sample enterprise-level project.
Assessments
Various kinds of assessments to evaluate your learning through the course.
Live Classes
There will be instructor led training to optimize learning. (Face to Face)
Learning Outcomes
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Gain complete technical know-how of basic and advanced data analytics and visualization techniques to analyze data, create statistical models, and provide business insights.
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Experience working with Hadoop and its component tools, as well as with basics in Spark – a cutting edge Big Data Analytics platform.
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Build strong foundation in managing and processing huge datasets with tools such as Hadoop 2 framework, MapReduce and YARN, Hive, Pig, RHadoop, Mahout.
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Undergo hands-on experience of working with Data analytics tools on real data-sets, including R, in form of extensive lab-work and projects through a controlled lab environment.
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Work on an integrated live project in the end to solve multiple Data analytics problem.
Class Schedules
Note: The certification examinations are not included in the class schedules. Learners are required to book their examination slots separately.
February 2022
Class 01
Class Duration
19 February 2022 - 26 March 2022
Saturdays
10am - 5pm (1pm Lunch break)
Live Lectures
19, 26 February 2022
5, 12, 19, 26 March 2022
26 March 2022 (10am - 1pm)
Lecture Format
Online Interactive Zoom Classes
February 2022
Class 02
Class Duration
17 February 2022 - 24 March 2022
Mondays & Thursdays
7pm - 10pm
Live Lectures
17, 21, 24, 28 February 2022
3, 7, 10, 14, 17, 21, 24 March 2022
Lecture Format
Online Interactive Zoom Classes
March 2022
Class 01
Class Duration
26 March 2022 - 30 April 2022
Saturdays
10am - 5pm
Live Lectures
26 March 2022
2, 9, 16, 23, 30 April 2022
Lecture Format
Online Interactive Zoom Classes
March 2022
Class 02
Class Duration
29 March 2022 - 10 May 2022
Tuesdays & Fridays
7pm - 10pm
Live Lectures
29 March 2022
1, 5, 8, 12, 19, 22, 26, 29 April 2022
6, 10 May 2022
Lecture Format
Online Interactive Zoom Classes
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