Time Series Analysis, Forecasting and Data Visualization

Course Objective

 At the end of this course, participants will be able to:

  1. Describe the various ways of presenting data involving multiple dimensions
  2. Describe and be able to augment the various concepts of moving averages, smoothing, residuals and autocorrelations into time series models
  3. Evaluate and assess the differences of various time series and forecasting modelling techniques
  4. Design and propose the use of relevant analytical models and statistical solutions in addressing research problems
  5. Describe ethical considerations of data visualization, and analytical pitfalls to avoid

 

Course Outline 


1. Introduction to Data Visualization
2. Data Visualization Techniques
3. Forecasting and Time Series Analysis
4. Elements of Time Series Analysis and Forecasting
5. How to handle Seasonality and Cycles in Forecasting
6. Case Studies and Applications

 


 

Suitable for


Specially designed for data visualizers, data analysts, time series researchers and executives performing trend analysis and forecasting, this course not only equips participants with the necessary elements and understanding of various time series models, but also cover aspects of data visualization in terms of presenting and communicating the insights from the otherwise mono-dimensional data in an intuitive and engaging manner.


Participants who may not have the relevant training will find this course useful and enriching, while those who may have some training or working experience in this area will find this course offering fresh insights into the area of data visualization, time series analysis and forecasting.


Participants should ideally possess a tertiary qualification and be generally comfortable with quantitative discussions, applications and working with models.
 


 

Assumed Skills and Knowledge / Minimum Entry Requirements


Participants should ideally possess a tertiary qualification and be generally comfortable with quantitative discussions, applications and working with models, testing of assumptions.

 


  
Award / Certification / Accreditation:

Certificate of Performance will be awarded to participants who pass the required assessment.


 

Mode of Assessment


Participants are required to sit for an open-book quiz where participants will be graded in accordance to the course objectives to ensure they are met in a practical way.
 


 

Profile of Trainer


Mr. Ng Jinsheng joined IBM SPSS in 2008 as an Executive in Training and Consulting after his graduation from the National University of Singapore (NUS) with a Degree in Statistics and Applied Probability. During his stay in IBM SPSS, he has trained hundreds of participants from the public service and private sector in statistical and data mining concepts, tools and applications in solving business problems. He has also led consulting projects and worked with C-level executives in addressing pressing business issues during which he received numerous praises and testimonies. During his working with IBM SPSS, Mr. Ng Jinsheng also completed his Masters of Science in Knowledge Management [M.Sc(KM)] from the Nanyang Technological University (NTU) and graduated one of the top in his cohort with a Dean’s List award in academic excellence. He later joined SAS Institute as an Education Specialist in the Training department, and thereafter as a Senior Associate in professional Consulting services.


An academic paper he has co-authored was nominated for the Best Paper Award in the 20th International Conference on Computers in Education (2012). He is currently a founding member of AnaVantage Management Consultancy LLP, and lectures and trains at Tertiary Institutions in Singapore in the area of business statistics, data mining and analytics, and develops analytics courses for undergraduate programmes in Singapore. Professionally recognized by the Project Management Institute (PMI) as a Certified Associate in Project Management (CAPM), he is also an IBM Business Analytics Certified Specialist in IBM SPSS Modeler (Professional) and IBM SPSS Statistics, as well as SAS Certified Predictive Modeler using SAS Enterprise Miner and SAS Certified Business Analyst using SAS 9: Regression and Modeling.


Professionally as a Trainer, Jinsheng possessed an Advanced Certificate in Training and Assessment (ACTA) conferred by the Workforce Development Agency of Singapore (WDA) and a proud recipient of the prestigious “Excellence in Teaching” Award (EIT) conferred by the Singapore Polytechnic (SP) during the Annual Excellence in Teaching and Training Convention 2015.  He is also conferred the title of an Associate Adult Educator by the Institute of Adult Learning (IAL) in 2016, an Adult Educators’ Professionalisation recognition which awards pedagogical and professional excellence.

 


 

Funding Incentives

 

1. 10% Discount for SP Alumni
To enjoy this discount you must be a Diploma Graduate from Singapore Polytechnic.
Applicants who make a false declaration to enjoy the discount will be subjected to paying up to the full course fee and/or be legally persecuted.
 


1. All applications must be made via Online Registration at www.pace.sp.edu.sg

Course fees can be paid by the following payment modes:

Credit Cards, Internet Banking, NETS (Not Applicable for company sponsored)
a) For e-payment using Visa/Master cards and Internet Banking, please click on the ‘Make e-Payment’ button on the acknowledgement page to proceed.

b) For NETS payment, you can pay at:
Singapore Polytechnic
PACE Academy
Blk T1A, Level 1
Mon-Fri: 8:30am to 7:30pm

Cheques
c) Please make cheques payable to “Singapore Polytechnic”. Please cross the cheque and write the Registration Reference ID, Applicant Name and NRIC/FIN number on the back of the cheque. Mail the cheque to:

Singapore Polytechnic
PACE Academy
500 Dover Road
Blk T1A, Level 1
Singapore 139651

Please note that an administrative charge of $15 will be imposed for any returned cheques from the bank or financial institution.

2. All successful applicants will be notified with a letter of confirmation via email.

3. Withdrawal and Deferment

Withdrawal and deferment notice must be made in writing to the Professional & Adult Continuing Education (PACE) Academy, Singapore Polytechnic via email accordingly:

Online Courses - [email protected]
All other Courses[email protected]

For withdrawal cases, the portion of course fee to be refunded is based on the date of notice as follows:

Classroom

  • 2 weeks before the commencement of the course - Full refund
  • Less than 2 weeks before commencement of the course - 70% refund
  • On or after date of commencement - No refund

E-Learning

  • There will be no refund or transfer of course once the account has been created.

The Singapore Polytechnic reserves the right to cancel or postpone any of the courses. Applicants will be duly notified and where applicable, the full fees will be refunded.

The Singapore Polytechnic also reserves the right to amend the fees charged or the period and duration of the courses.

The data provided to Singapore Polytechnic will be kept strictly confidential and will be used for the purpose of course administration. The data may be passed on to the relevant organisations that require the information related to the course.

 

 

 

IMPORTANT DATES

 

There is no schedule for the course you selected.


Please register your interest.

 

 

COURSE DETAILS

Duration: 2 days

Time: 9am to 5pm

Venue: Singapore Polytechnic

 

COURSE FEE

 

S$890.00 (before GST)

S$952.30 (after GST)

 

Please refer to Funding Incentives for more information.

 

 

HOW TO APPLY

 

 

Terms and Conditions