Data Science Academy

Center for Learning & DevelopmentAmerican University of Science & TechnologyBeirut – Ashrafieh – Alfred Naccache Avenue

Phone: 961 1 218716/7 Ext. 618schahensarian@aust.edu.lb

Website: www.aust.edu.lb

Data Science Academy

In partnership with

Data Science and Big Data

2017 Post Graduate Diploma

Joint Certificate Program

Data Science Academy

Matrix TRC Data Science Academy, offers full flexible courses, as well as a complete 11

month diploma (316h) that encompasses exhaustive Data Science and Big Data topics, that:

Covers most needed expertise in the emerging strategic numerical economy

Puts all Machine Learning algorithms into practical applications

Helps companies implement a vital internal Data Center for scientific information

Brings a synergy between the main information system stakeholders

Joins a group of local and international experts in each field

Supports participants with latest analytical and complete IT technologies

Tackles comprehensively the whole IoT and Big Data components

Brings highest ROI with participants applying 4 projects from within their businesses.

The Program

Data Science Academy

Research Methodologies

M1

From Business to Statistics

M2

Profiling Techniques 1

(Basic)

M3

Profiling Techniques 2

(Intermediate)

M4

Data Management

M5

Profiling Techniques 3

(Advanced)

M6

Forecasting Models from A to Z

M7

Social Media Analytics

M8

Machine Learning 1

(Supervised)

M9

Data Warehousing & Operations

M10

Machine Learning 2

(Unsupervised)

M11

Programming with R and Python

M12

Project Management Pillars

M13

SAS Data Technologies

M14

The Modules

15: Cloud and IOT (16h)

• Virtualization and Containerization• Communication protocols• IoT Architecture and IaaS

BIG DATA

16: Big Data Technologies (16h)

• Real Time Streaming Analysis• Hadoop / MapReduce

• Spark

Extra Guest Speakers (24h)

3. People-Meter

4. Project Management

1. Questionnaire Design

2. Relational Tables

5. World Bank Econometrics

6. Industrial Quality Measurements

Joint Certificate

Program

7. Data Security

Data Science Academy

The ModulesA state of the art 3,500 colored PowerPoint slides with more than 120 examples and real case studies.

All courses certified by

Data Science Academy

M1. Research Methodologies

M6. Profiling Techniques (Advanced)

M2. From Business to Statistics

M3. Profiling Techniques (Basic)

M7. Forecasting from A to Z

M5. Data Management

M9. Machine Learning 1 (Supervised)

M8. Social Media Analytics

M11. Machine Learning 2 (Unsupervised)

M13. Project Management Pillars

M10. Data Warehousing

M15. Cloud and IoT

M16. B.D Technologies

NSJMM A J A O D J

Schedule

M15.

BIG DATA

M14. SAS Data Technologies

M12. Programming with R and Python

Project 1

Project 2

Project 3

F M

M4. Profiling Techniques (Intermediate)

2017 2018

Data Science Academy

Who Should Attend?

This program is primarily aimed to serious people who aspire to learn state-of-the art Data Science techniques, and how it can be

applied to solve data and business issues. It specifically suites practitioners involved mainly, but not exclusively, to the below fields.

It is also addressed to anyone who wants to “get connected” with latest data management and analytical solutions, how different

tools can be used, and what factors should be considered when planning for any “Big Data” project.

Prerequisites

Previous knowledge or experience in statistics, data mining, or artificial intelligence algorithms is not required at all. However, a serious interest and

continuous active participation is a must for a successful completion of the diploma.

Data Science Academy

Clients and Participants

Data Science Academy

Some Testimonials

Abed Al Rahman Itani (Azadea)

IT Business Solution Specialist

The diploma was very inspirational, energizing, bringing lots of

ideas. I learnt a lot. I am inspired to rethink the way I plan and

present my work. A very high pedagogical standard. Well done!

Ali Younes (DG Jones and Partners)

Quantity Surveyor / Estimator

This program takes the broad and expanding domain of data science and introduces it with an intricately linked set of subjects, instruments and methodologies,

and goes on into the expansion on each sub-domain in such a way that respects and accounts for the development of each module alone and the whole of the

course in parallel throughout. Presented in a way that puts it into orchestral tune and shows the making and tuning of each of its instruments while

handcrafting each instrument and hearing the music of the orchestra simultaneously.

Ghassan Zein (Ideatolife)

Senior System Admin.

The Data Science program

provided me with the complete

needed knowledge to develop

a product for Data Analysis

and Predictions to help our

customers taking the right

decision at the right time.

Kris Khairallah (BOB)

IT Developer - Data architecture & BI

The course exceeded my expectations in

many regards, especially in the depth of

information supplied and the access to the instructor for

feedback on work in progress. In a very non-threatening

environment, I learned key principles of design that I can

implement immediately. A diploma I highly recommend!

Radwan M. Hadwan (Bank Audi SAL)

Systems, Policies and Regulatory

Body Relations Unit

Matrix TRC Data Science program opens

new scopes for participants to new job

opportunities, widens the critical thinking,

and enhances the analytical skills of those

who are mostly implicated in data.

Sabine Oussi (Sabis)

Data Analyst – IT

Attending Data Science

& Big Data post-graduate

diploma has made me

discover data from a

different perspective. It is not only about

what the business intelligence tools can do

nowadays but mainly about the real analysis

that lies behind their logic. DS & BD is a full

program from basic to Big Data analytics

going through all the methodologies and

applications needed as well as other

contemporary topics.

Data Science Academy

Some Testimonials

Marc Lati (Ethos Interactive)

Co-founder

I joined the Data Science program, unsure of the benefit I might gain. But results

exceeded my expectations by far, with rarely encountered experts as competent and

enthusiastic about their courses. Some of them master their knowledge, reaching

professional skills that made complex information look so easy to understand and

put into practice. Though it is given for the first time in the Middle East, the

diploma reveals great professionalism that brought me efficient added value. I

would advice it to any person who wishes to grasp a solid understanding of Data

Science and specifically Big Data analytics.

Mario Gergi Sarkis (Bank Audi S.A.L.)

Business intelligence officer

Data Science is a trend that has become a crucial element for every major Enterprise.

Learning data analysis smartly based on correct gathered information, affected dramatically

my business development skills in various aspects. Furthermore, predictive and classification

modules has helped me, as a professional daily data modeler, to reach better insight for all

key elements affecting clients, communication, business management and product assessment.

Jean Abi Saab (A.U.B)

Senior Research Analyst

The Data Science program has given me the right exposure not only to a broad

range of data models but also to various statistical tools that helped me in my

research projects. After the training, I was directly able to analyze data

using statistical methods and new approaches without becoming a slave of data.

The rich curriculum in data analysis and data mining allowed me to think

beyond needed reports to develop new insights and find hidden patterns.

Pierre Nehman (B.O.B)Senior HRIS & Payroll Officer

The program joins both levels for experienced professionals as well as

for beginners. The complete diploma enhanced my skills on how to deal

even with complex data through machine learning algorithms and

predictive analytics that were all supported with cutting edge

technologies. I would highly advise anyone to be part of it!

Madonna Beyrouthy (Sabis)Associate ManagerBook Orders

A very interesting, useful, and rich

diploma program! I am certain that it

will be of a benefit to both myself and my

team, especially when it comes down to

the different approaches in reading and

analyzing data. The material and topics

covered are very well presented and the

instructors are very professional. I

believe that this new topic will be an

important one during the coming years,

and I highly recommend everyone that

deals with data to enroll in it.

Data Science AcademyM1. Research Methodologies

Design of Research

Qualitative Research

Quantitative Research

Ethics and Reliability of Research

Validity of Research

Sampling

Data Science AcademyM2. From Business to Statistics

135…

TV Time

Count 850

Mean 548.79

Variance 9,944.17

Standard deviation 99.72

Coefficient of variation 0.18

Standard Error 3.42

Confidence Interval 95% [542.07 - 555.5]

Shapiro Normality test 91.8%

Minimum 220

First quartile 483.75

Median 547

Third quartile 613.25

Maximum 882

Range 662

Skewness 0.03

Kurtosis 0.00

Sum 466,468

Types of Variables

Simple and combined charts

Complete Descriptive Statistics

N.O.IGender / Invoice (Sum)

Male Female Total

1 $2,827 $3,056 $5,883

2 $20,366 $28,597 $48,963

3 $23,304 $56,730 $80,034

4 $8,276 $20,283 $28,559

5 $2,139 $8,691 $10,830

TOT. $56,912 $117,357 $174,269

One and Multilevel Tables

4334

19

35 31

4746

28

36 38

25

14

11

169

0

30

60

90

120

150

Capital North South East West

Software applications

n

x

X

n

i

i 1

Data Science Academy

z

-1.96 = - 𝑧0.025 𝑧0.025 = 1.96

|

-4

|

-3

|

-2

|

-1

|

2

|

3

|

4

|

5

|

0

H1 H1H0

M3. Profiling Techniques (Basic)

Hypothesis Tests

Benchmarking Variables

Statistical Tables

Software applications

cm0 5 10 15 20 3025

kg40 50 60 70 80 10090

$

1,5001,750

2,0002,250

2,500 3,0002,750

One-Means’ Deviation Sorting table

X: Heart beat / Y: Type of illness

Average R.V Raw deviation Std. Dev. Std. Error Stat d.f H0 limits P-Value Test Name

Pulse 83.34 84 -0.66 17.7 0.694 -0.95 646

[-1.96; 1.96]

0.343

t-student

Upper Tension 12.80 13.5 -0.70 2.4 0.095 -7.38 646 4.8x10-13

Lower Tension 7.29 7.5 -0.21 1.5 0.058 -3.67 646 2.6x10-4

Temp 37.23 37 0.23 0.8 0.032 7.03 646 5.2x10-12

Resp. Frequency 19.99 19.0 0.99 3.3 0.131 7.61 646 9.7x10-14

R.F (1x10-13)

Upper T. (5x10-13)

Temperature (5x10-12)

Lower Tension (0.00026)

Pulse (0.343)

5%

Calculate Explore

EvaluateDecide

Chance Analysis

Data Science Academy

cm0 5 10 15 20 3025

kg40 50 60 70 80 10090

$

1,5001,750

2,0002,250

2,500 3,0002,750

Comparison of means between two independent groups

X: Treatment (two modalities)

Y: LDL cholesterol level (continuous)

𝐴 𝐵 Total Diff. Std. Error Stat. d.f H0 limits P-Value Test Name

Mean 139 136 137.8 -3 2.1 -1.43 23 [-2.07; 2.07] 0.167 t-student

Variance 31.3 19.1 --- --- --- 1.637 (14; 9) 3.03 0.231 F-variances

Count 15 10 25

GPA (0.004)

IQ (0.007)

EQ (0.008)

Satisfaction (0.253)

Gender (0.423)

Baccalaureate type (0.558)

5%

M4. Profiling Techniques (Intermediate)

Profiling Variables

Statistical Tables

1.02

0.80

0.11

0.08

-0.80

-1.30

-1.14

-2.67

-2.71

-3.61

-5 -4 -3 -2 -1 0 1 2 3 4 5

B.T (G.S)

Gender (Female)

B.T (L.S)

B.T (S.E)

Gender (Male)

B.T (L.H)

Satisfaction

EQ

IQ

GPA

Public Private

Profiling Solutions

Software applications

Chance Analysis

Data Science Academy

POS

ERP

Legacy

Misc. OLTP

External Web Docs

Data Mart

(Marketing)

Data Mart

(Mgt.)

Data Mart

(Finance)

M

I

D

W

A

R

E

Web browserCustom-Built Applications

(4GL tools)

EIS, Reporting

Relational Query Tools

Data Mining

OLAP/ROLAP

Supply Chain Data

DataAccess

O.S/Data

Marketing

DataWarehouse

Finance

Meta Data Repository

Federated Data

Warehouse

INTRANET

External EDI

DSS

E

T

L

M5. Data Management

Data Science Academy

𝑗=1

𝑘

𝑖=1

𝑛𝑗

(𝑥𝑖𝑗 − ത𝑋)2

Groups Count Sum Average Variance

South 6 3,625 604.17 37,104

North 8 6,300 787.50 44,642

Beirut 7 7,250 1,035.71 20,595

Mount Lebanon 8 7,925 990.63 29,453

ANOVA

Source of Variation SS df MS F P-value F crit

Between Groups 786,503.1 3 262,167.7 7.92 0.0007 2.99

Within Groups 827,764.1 25 33,110.57

Total 1.614.267.2 28

0

100

200

300

400

500

S - N S - B S - M.L N - B N - M.L B - M.L

Tukey Kramer comparison

30

50

70

90

110

140 160 180 200

Explained VariationsTotal Variations Residual Variations

30

50

70

90

110

140 160 180 200

30

50

70

90

110

140 160 180 200

0%

20%

40%

60%

80%

100%

0

50

100

150

200

250

D-C M-S M-C D-B …

Pareto’s association

M6. Profiling Techniques (Advanced)

Complete Statistical Tests … and more!

Built-in Analytical Tables

Regression Solutions

Software applications

Data Science Academy

Y = 98.5 – 6.68t + 1.31t2

60

80

100

120

140

160

180

1 2 3 4 5 6 7 8 9 10

1

2

Tt = 3

t

1

Ct = 1.5

t

1 t

It = 0.97

2.62

t1

St = 0.6

tW SS F W SS F W SS F W SS F W SS F

TREND

SEASONS

CYCLES

IRREG.

Yt

1.0 -

0.6 -

0.2 -

-0.2 -

-0. 6 -

-1.0 -

Lag

A.C.F

1 5 10 15 20 25 30 35 40

20,000

35,000

50,000

65,000

1 5 9 13 17 21 25 29 32

M7. Forecasting Models From A to Z

Exponential Smoothing

Trends

Time Series

ARIMA – Box Jenkins

Software applications

Data Science AcademyM8. Social Media Analytics

Listening & Monitoring

Audience Analysis

Analytical Tools

Data Analytics

Data Science Academy

C.G

Y = 0 + 1X1 + 2X2Y

X1

X2

Y X2

X3

X1

Y X2

X3

X1

X3

X1

Y X2

X3

X1

X3

X1 X1

Y X2

X3

X1

X3

X1 X1

0.0

0.5

1.0

-15 -10 -5 0 5 10 15

𝑃(𝑍) = 1

1 + 𝑒−𝑧

S VE VI

S VE

VE VI

VI

0 g2

D.Sg1

D.S

Group 1 Group 2

M9. Machine Learning 1 (Supervised)

Gradient Descent Algorithms

Multiple

and

Stepwise

Regressions

Logistic Regressions

Discriminant Analysis

CART Trees

Software applications

Data Science AcademyM10. Data Warehousing & Operations

Data Base Environment

Data Storage Systems

ETL and DataData Base Technologies

Data Science Academy

QU

ALITY

PR

IC

E

SPORTINESS

LUXURY

Cluster … 1 2 3

M11. Machine Learning 2

(Unsupervised)

Principal Component Analysis and …

… Clustering

Simple & Multiple

Correspondence Analysis

Multi Dimensional Scaling

Quadrant Analysis

C4

C6

C3 C2

C7

C5

C8

C1

Importance

Im

pact 1

3 4

2

Software applications

Data Science AcademyM12. Programming with R and Python

2 million users worldwide

40% yearly increase of users

Leading programming language in data analyticsand data science.

Worldwide use of Python to come up with insights from

data and gain competitive edge.

Module oriented for data scientists to start and

develop their proper analysis.

Most powerful tool to store and manipulate data.

Data Science Academy

1. Integration

2. Scope

3. Time

4. Cost

6. Human Resources

7. Communication

8. Risk

9. Procurement

5. Quality

10. Stakeholders

Cu

mu

lati

ve v

alu

es

Funding requirements

Expenditures

Completion

date

Cost Baseline

Problem

People

Leader Manager

M13. Project Management Pillars

Data Science AcademyM14. SAS Data Technologies

ARCHITECTRE FLEXIBILITY: SMP - MPP - HADOOP - GRID - ESP

DEPLOYMENT FLEXIBILITY: DESKTOP - SERVER - IN-DATABASE - IN-MEMORY - Cloud

Information

Management

Data Mining /

Anomaly

Detection

Text Analytics Predictive

Analytics

High

Performance

Analytics

Fraud and

Risk

Detection

Reporting

and

Visualization

Integrated End to End Foundation

Data Science AcademyM15: Cloud and IoT

IaaS: reducing operational and infrastructure costs

Virtualization and Containerization

Connecting Everything to the Internet

IoT Communication Protocols IoT Architecture IoT market segmentsand value

16%

16%

12%11%

8%

8%

29%

IoT Value Add by 2020 - $1.9 Trillion

Manufacturing

Healthcare

Insurance

Banking & Sec.

Retail & Wh.

Comp. Services

Others

App

Bins/Libs

Guest OS

MySQL

Bins/Libs

Guest OS

MySQL

Bins/Libs

Guest OS

Hypervisor

Host OS

Server

APP

Bins/Libs

MySQL

Bins/Libs

Container Engine

Host OS

Server

APP

MySQL

APP

MySQL

Virtual Machines Containers

Data Science AcademyM16. Big Data Technologies

Big Data Universe

B.D Three Pillars

B.D Technologies

Machine Intelligence

Data Science Academy

- T2 -

Forecasting and

Social Media

(36 hours) - $950

- T1 -

Research and

Profiling Techniques

(88 hours) - $2,500

- T3 -

Machine Learning

(72 hours) - $1,900

- T4 -

Data Management &

Storage

(60 hours) - $1,750

- Understand data structure- Quantify and illustrate

information- Sort out characteristics of

different groups in seconds!

- Evaluate decisions error level- Optimize models to predict

behaviors- Project complex data sets

into maps

- Retrieve data from different sources

- Normalize data for SQL exploration

- Comprehend ETL – OLAP and Data Warehouse designs

BIG DATA

(56 hours)

$1,700

- Analyze unstructured data- Real-time streaming analysis- Manage Cloud Data Platforms- Hadoop – MapReduce- Spark

The Professional Certificates

- Learn forecasting techniques- Understand social media

channels- Analyze social media overall

data

M13

Project Management Pillars

Acq

uir

ed

Co

mp

ete

nci

es

Guest Speakers 1 - 3: 8h G.S 4: 4h G.S 2 - 5: 12hG.S 6: 8h G.S 7: 8h

M9 - 11

Machine Learning 1 and 2

M5

Data Management

M10

Data Warehousing

M15

Cloud and IoT

M16Big Data Analytics

M14

SAS Data Technologies

M2

Turning Businesses into Stat.

M3 - 4 – 6

Profiling Techniques

M7

Forecasting Models

M1

Research Methodologies

M8

Social Media AnalyticsM12

Programming with R & Python

Data Science Academy

The Specialties and DS Diploma

Data Science312 hours

Data Mining252 hours

Data Analysis124 hours

T1 (M1-M2-M3-M4-M6)

Research and Profiling Techniques

T2 (M7 – M8)

Forecasting & Social Media Analytics

T4 (M5 – M10 – M13)

Data and Project Management

T3 (M9 – M11 – M12)

Machine Learning

Acquired Competencies- Highlight Data Patterns - Sort Out Groups Characteristics- Evaluate Predictive Models- Control Processes Statistically

Acquired Competencies- Master Machine Learning Algorithms- Innovate New Analytical Products- Manage Data Warehouse Designs- Learn Project Management Tasks

Acquired Competencies- Manage IoT data - Understand Cloud Data Platforms- Implement Hadoop Framework

(MapReduce, Spark, etc.)

M15

• IoT / Real-time streaming analysis• Cloud data solutions

M16

• Hadoop framework• MapReduce• Spark / Apache

BIG

DATA

M14SAS Data Solutions

($3,500)

($6,500)

($7,900)

Benefit from the most flexible repayment plan. Settle part of your tuition fees gradually at

0% interest, and the remaining amount over 1 year after a grace period of 6 months.U LOAN

Data Science Academy

Walid Semaan(Advisory Board)

He is the founder and president of Matrix Training Research & Consulting, a company specialized in

statistical training and research. He graduated in Engineering from Ecole Supérieure d’Ingénieurs à

Beyrouth. He holds a degree in finance and marketing from the Ecole Supérieure de Commerce de

Paris (ESCP) and an MBA from the University Paris-Dauphine-Sorbonne in Paris. He is the creator and

architect of the automated artificial intelligence behind “Triple One Analytics”, winner of the Best

Innovative ICT Project at the Arab Golden Chip Award 2011.

The Experts

Data Science Academy

Anthony Franklin is an expert statistician with experience in many software languages

including open source technologies. Anthony conducted his doctoral studies at North

Carolina State University and completed his graduate assistantship with the NCSU Institute

of Advanced Analytics. Anthony resides in North Carolina and currently is a Sr. Analytics

Architect at SAS Institute with experience in risk management, hospitality and sports

analytics.

The Experts

Anthony Franklin(Advisory Board)

Data Science Academy

Pierre EL HADDAD is currently a Hubert H. Humphrey Fellow at The Maxwell School for Citizenship and Public

Policy, Syracuse University, New York, US. He is also a consultant, university teacher in management at

University of Balamand-Lebanon, and has twenty years of experience in private business management. His

present concerns relate to the participatory and collaborative institutional development towards sustainable

organizations and communities. In parallel, he is developing a CSR decision-making model, and studying the

role of the private sector in public administration reform.

Pierre has a master in civil engineering from Saint-Joseph University, an MBA in economics and finance from

Notre-Dame University in Lebanon, and he is finalizing his doctoral dissertation in business administration from

Jean Moulin University-Lyon III.

The Experts

Pierre EL HADDAD

Data Science Academy

Grace Madi is the head of the Project Management Office at Bank Audi. She established this office in

2010 to address the need for integrated, structured, and standardized approaches to managing the

large business and technology. The PMO oversees activities in the areas of PPM methodologies and

standards, project resourcing and consulting, risk analysis and mitigating, PPM system implementation

and support services, analysis and reporting. Grace has a diverse educational background with

Bachelors Degrees in Computer Science, she is a certified Project Management Professional (PMP), has

attended various course and certification in Risk Management, Cost estimation. She provides lectures

at various universities and seminars.

The Experts

Grace Mady

Data Science Academy

Karim earned a PhD degree in Software Engineering and is passionate about Service Oriented

Architecture, Cloud Computing & Software methodology. He has a broad experience working with

leading multi-national companies in Europe. Karim has also a sound academic experience and is

currently assistant professor and coordinator of the business computing degree at St. Joseph

University. He is actual a leading consultant at Element^n, expert in cloud development solutions.

The Experts

Karim Saikali

Data Science Academy

Mr. Taleb Kabbara a social media Consultant and Trainer with 10 years of experience in teaching,

training, consulting, and social media. He has worked with Leo Burnett Dubai for 4 years,

handling top global and regional accounts, to name few: McDonald’s Arabia’s Social Media,

Morgan International, Abu Dhabi Ministry of Foreign Affairs, Dubai Ministry of Education. He has

been in Lebanon for the past couple of years doing consulting and training workshops for working

professionals, agencies, brands, and celebrities.

Taleb Kabbara

The Experts

Data Science Academy

Rabih is the founder and CEO of Scriptr, an enterprise cloud

platform that enables Internet of Things developers to bring

their products to market faster and more reliably. In 2006,

Rabih served as SVP of Engineering for Vidavee, a cloud B2B

video on-demand startup acquired by Vignette. In 2003 he

co-founded ElementN the holding group behind Apstrata &

Scriptr. In 2000 he co-founded Super11.net in Brasil, growing

in few months to one of the largest Latin American ISPs,

Application Service Providers and portals. Rabih earned a B.S.

in Telecommunications from the St. Joseph University and an

MBA from the École Supérieure des Affaires in Beirut.

RabihNassar

Guest Speakers

Elie Aouad

Elie Aouad began his professional life by creating

the cryptographic hardware layer used in payment

authorization centers. Since 1995 he is the CEO of

EASEIT, a company he founded in France and

through which he created multiple cryptography

and security products used in France and all over

the world. Actually he works on projects including

the Internet Of Things and on the security, data

modeling and statistics in the health field, as well

as gives lectures in cryptography and security in

multiple universities.

Data Science Academy

Imad Hajj Chahine

HalaZeineh

Imad hajj chahine graduated in Software Engineer from Ecole

Supérieure d’Ingénieurs à Beyrouth (ESIB), specialized in

custom data-centric application in different fields of application

(financial, accounting, insurance, and statistics). He co-

founded Evolve in 2005 a company specialized in tailor made

solution serving a range of local and international clients, and

he is the lead Software engineer for “Triple One Analytics”. His

expertise covers statistical data analysis, big data,

performance and data visualization/representation. He is an

expert in many proprietary and open-source RDMS, NoSQL

and software application framework.

Mrs. Hala Zeine is a statistician, researcher and trainer with 7

years of experience in teaching, consulting, research projects,

data analyst and statistics. She worked in Center of Statistics in

Lebanon in collaboration with ESCWA, Mada Association, Arope

Insurance, Beirut Municipality in collaboration with USAID,

Lebanese Ministry of Social Affairs in collaboration with World

Bank, as well as many other institutions.

Hala is expert in data processing and analysis. Her knowledge

expands strongly to sampling methodologies as well as

estimation techniques, time series, and report writing.

Guest Speakers

Data Science Academy

Christian Saab is Managing Director at AGB Stat Ipsos, where he

manages operations and client relations and oversees business

growth. With more than 23 years of experience in the TAM

business, Media Research and Information Technology, Christian

works alongside TV stations, the advertising agencies and

advertisers to make decisions on allocating resources and budgets

by providing insights about their target audiences. Christian is also

part of the Joint Industry Committee of Media Research in Lebanon

and a speaker on industry related topics at universities.

Guest Speakers

Christian Saab

Layal Mansour is an economist with experience

in econometrics. She is a PhD holder from

University Lyon 2-France. She did her doctoral

studies using forecasting and time series

analysis applied to Monetary and Financial

Economics. Layal Mansour's teaching experience

is diversified, in France and in Lebanon and in

several universities. In parallel, she works as

consultant for The World Bank and the ESCWA.

LayalMansour

Data Science Academy

Matrix TRCData Science AcademyMar Roukoz - Berytech Technological PoleWalid Semaan: 961 3 636 208Fax: 961 4 533 040Website: www.matrixtrc.com

Center for Learning & DevelopmentAmerican University of Science & TechnologyBeirut – Ashrafieh – Alfred Naccache AvenuePhone: 961 1 218716/7 Ext. 260Fax: 961 1 339302Website: www.aust.edu.lb