A brief overview of the Professional Certificate in Data Science Course at MAGES Institute, a 6mth program design for non-ICT personnel for a career-transition into ICT Sector.

1. Data Science
Course
THE FUTURE STARTS HERE
Rethinking business,
technology and data.
Supported by

2. CONFIDEN
TIAL
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Applied data science
with Machine Learning
NEED FOR
DATA SCIENCE
USE CASE OF
DATA SCIENCE
DATA
SCIENTISTS IN
DEMAND
04.
WHAT IS DATA
SCIENCE
APPLIED
DATA SCIENCE
PROGRAM
05.
FEES/GRANTS/
APPLICATION
PROCESS
06.
01.
03.
02.

3. 3
DATA

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What is data?
4
CONFIDENTI
AL
IMAGES TEXT
NUMBERS BITS
Data is a collection of facts, such as numbers, words,
measurements, observations or just descriptions of things

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Types of data
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TRADITIONAL
DATA
Structured and in
table format (Excel,
Spreadsheet etc.)
Can be managed
from a single
computer
BIG DATA
Numbers, text,
images, audio,
mobile data…
Retrieved and
computed in real
time
Distributed across a
network of
computers

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Where does data
come from?
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Where does data come from? (1/3)
Evolution of
technologies
Social media Other factors
PHONE
DESKTOP
TELEPHONE
CLOUD
SMART CAR

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Where does data come from? (2/3)
Evolution of
technologies
Social media Other factors
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TWITTER
INSTAGRAM
E-MAILS
FACEBOOK
YOUTUBE

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Where does data come from? (3/3)
Evolution of
technologies
Social media Other factors
TRANSPORTAT
ION
HEALTHCARE
BANKING AND
FINANCE
MEDIA AND
ENTERTAINME
NT
EDUCATION
RETAIL
INSURANCE
GOVERNMENT
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10. 10
Need for Data
Science
So Data Science is Mainly Needed For
Better Decision Making
01.
Predictive Analysis
What Happens Next?
02.
Pattern Discovery?
Is there any hidden
Information in the Data?
03.

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05.
08.
Benefits of data science
REDUCE
MAINTENANCE
COST
OFFER
ENTERPRISE-WIDE
INSIGHT
REDEVELOP YOUR
PRODUCTS
KEEP YOUR DATA
SAFE
CREATE NEW
REVENUE
STREAMS
TARGET BETTER
WITH CUSTOMER
PREFERENCE
TAKE SMARTER
DECISIONS
OFFER TAILORED
HEALTHCARE
PERFORM BETTER
RISK ANALYSIS
CUSTOMISE YOUR
WEBSITE IN REAL
TIME
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01.
04.
07.
03.
09.
10.
06.
02.

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Case studies
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Today
Reactive Health
Tomorrow
Proactive Health
• Seek health services when feeling ill
• Consumer sorts through different care
options
• Data is then captured to confirm diagnosis
• Care option reaches out if there is an
anomaly and triage via tests/consultation to
confirm whether a hospital visit is needed
• Provider already has historical data-set of
relevant bio-markers and genetic
predisposition
MEDICAL
GRADE
WEARABLES
Predictive diagnostic
to
Proactive diagnostic

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Data science in various industries
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ENTERPRISE
Capturing data
volume, variety and
value
MACHINE
LEARNING
Data science is
leveraged to disrupt
ML based application
RETAIL
DIGITAL
MARKETING
Analyze consumer
behavior
Predict product pricing
INSURANCE
Fraud & Risk detection
Insurance claim
prediction
Detect targeted
audience
Demographic behavior
analysis
HEALTHCARE
FUNDING
Detect causes of
disease
Risk prediction
MEDICAL
Disease prediction
Analyze patient’s
recovery growth
Detect possible
fundraisers

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The Process
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COLLECT RAW DATA
FRAME THE PROBLEM PROCESS THE DATA PERFORM IN-DEPTH ANALYSIS
Identify available datasets
Extract data into usable format
COMMUNICATE RESULTS
Identify Business insights
Visualize your findings
Tell a clear & actionable story
Ask a lot of questions
Identify business priorities
Examine Data at a high level
Clean the data
Create a predictive model
Evaluate & Refine model
EXPLORE THE DATA
Split, Segment & Plot the data
Identify Patterns & extract features
01.
02.
03.
04.
05.
06.

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Applied Data
science with
Machine
learning
Who are Data Scientists
01.
Why industries need Data
Scientists
02.
Data Scientists
Demand, Salary, Career
path
03.

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DATA SCIENTIST?
Data Scientist is capable
of extracting and
interpreting data, which
requires hands-on
machine learning, skill
with advanced
programming and
statistical expertise
Who are Data Scientists
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WHAT MAKES A
DATA SCIENTIST?

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Rapid market growth is evident, and
Organizations indicate they are
increasingly spending on AI
technologies and getting positive
returns
This will lead to higher demand for
Data Scientist across the Industries
Investment in
current fiscal year
Investment change
in next fiscal year
Return from AI
investment to date
$5M+
$500K - $5M
< $500K
More than 20 %
+10 % to +20 %
+1 % to +9 %
Stay the same
40 % +
+30 %
+20 %
+10 %
Notes: Percentages may not total 100 percent due to not including all answer choices
from
all questions; all monetary amounts are given in US dollars
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SOURCE: Deloitte
Organization are spending on
AI technologies and seeing a
return
on their investment
Why industries need
Data Scientist

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TIAL
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CONFIDEN
TIAL
02.
ARTIFICIAL
INTELLIGENCE
Besides the rise of data
online, the demand for data
scientists is also linked to
new technologies, including
Artificial Intelligence.
01.
BIG DATA
Ever since the internet has
taken the spotlight, data
has become key for
companies across
industries. Every action that
a user takes online can now
be tracked, leading to huge
amounts of data..
Why the demand for Data Scientists is high?
Big data and AI are the major factors in the growing demand for data
scientists, but other related tech trends are also driving the need.
For example, the internet of things and deep learning are just two trends
that are very realistic for 2020.

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2,7 Million
Career opportunities
Estimated for Data
Science and analytical
roles in 2020
28%
Annual Growth
In job opportunities for
data scientist, data
developers and data
engineers across the
globe
SALARY TREND
Jobs requiring Data
Science skills are paying an
average of $114,000.
Advertised data scientist
and data engineering jobs
pay an average of $105,000
and $117,000 respectively
TOP INDUSTRIES
Prominent economic
sectors where data
analytics is marking its
presence include
• Energy
• Insurance
• Healthcare
• Retail Banking
JOB TITLES INCLUDE
• Data Scientist
• Data & Analytics Manager
• Data Architect
• Principal Scientist
• Data Engineer
Data Scientists
Demand, Salary,
Career path
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Data Science
Career Path
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21. 21
Applied Data
science with
Machine
learning
About the data science
program
01.
Core topics covered in the
program
02.
Weekly breakdown for the
program
03.

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CONFIDEN
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02.
DURATION
Full Time – 14 weeks
Part Time – 24 weeks
01.
PROGRAM
OVERVIEW
Data science immersive
course offers students the
opportunity to advance their
careers and gain skills for
the new digital economy.
Students will learn how to
use the right software and
techniques to read visual
and statistical data and
present it in a way that
solves real world problems..
Program overview
SUPPORTED BY

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IMMERSIVE program features
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CONFIDEN
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Syllabus is living and
evolving.
We constantly improve on it
based on the ever-changing
needs of the gaming industry
and feedback from our students
and alumni. You will develop a
range of portfolio pieces under
constructive peer review.
SERIOUS
COMMITMENT
01.
MENTOR
MEETINGS
03.
STRUCTURED
CURRICULUM
02.
CAREER
SUPPORT
04.
You bring the desire. We
will bring the right support
and resources to help you
thrive. Recommended
commitment is 12 hours a
week outside of class time
for Part Time and for Full
Time.
Once the Immersive
Program begins, you’ll meet
with your Mentor during the
project with reviews to keep
you making progress.
We focus on the right skills
in the right order. Our
curriculum designed very
carefully to meet the
demand of the industry.
Please Refer to week by
week breakdown.
We provide each of our
graduates with access to
job readiness training, an
alumni network,
connections to employers
and opportunities to hone
new skills in AR/VR.

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ARE YOU READY for
MAGES DATA SCIENCE COURSE?
Growing the data science ecosystem
MAGES Institute of Excellence Pte. Ltd.
2 Orchard Link, SCAPE #05-08,
Singapore 237978
(Near Somerset MRT)
Reg No: 200912099N
Reg from: 21st Aug. 2016 to 20th Aug. 2020
Reach us at enquiry@mages.edu.sg
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