Overview

Summer School in Data Science & Analytics for Food Security (51 Hrs)

THREE WEEKS COURSE

August 2024
ICESCO HQ and AOAD Digital Knowledge Hub, Rabat - Morocco

Part One (Pre-course online) 7 Days (21 Hours)
Part Two (Face-to-face training) 5 Days (25 Hours)
Part Three (Post-course online) 5 Days (15 Hours)

The workshop will be facilitated two of the world-renowned experts in Digital Transformation, Dr Rawad Hammad and Professor Allam Ahmed winners of Emerald Literati Award for Outstanding Paper 2021 on learning theories and models underpinning technology-enhanced learning artefacts.

Food Security is gaining an enormous interest since COVID Pandemic and Ukraine-Russa conflict. Supporting planning and decision making for food security is now on the top agenda of states and international organizations. This workshop has been designed to introduce a variety of fundamental perspectives on Digital Transformation (DT), Artificial Intelligence (AI), Data Science (DS) and Knowledge Management (KM) to support a more intelligent and comprehensive planning and decision support in many aspects.

The aim of this course is to develop an upgraded critical mass of experts and policy makers cross the Arab world that can use these smart tools applied to food security planning and decision support. This introductory course aims at providing students with insights on how data-related methods are used to tackle and monitor food security. It gives an overview of a data science based approach.

The program uses a blended approach of teaching, where digital and physical presence were used. A pre workshop one-week online module prepares the audience with fundamentals followed by an intensive face to face one week workshop where core learning activities will be conducted through instructor’s lectures and invited seminars by experts. A practical module accompanying the theoretical component with hands-on sessions with Python notebooks will also be planned. The Python module will give students the opportunity to put into practice the methods introduced during the course through the exploration of AOAD open datasets and research question (e.g., estimating Food Deficits from Agricultural data).

The course objective is to upgrade a critical mass of Arab Policy Makers and Experts in modern smart approaches in food security modelling.

Related Sustainable Development Goals

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Location

Rabat, Rabat-Salé-Kénitra, Morocco

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Dr. Rawad Hammad
Rawad is a computer scientist with 20 years of experience in academic research, teaching, industry and leadership. He is a Senior Lecturer in Computer Science and Digital Technologies and the leader of two MSc Programmes and a Technology-Enhanced Learning Research Group at the University of East London. He is also co-director and co-founder of a newly established Smart Health Centre at UEL. He is an executive committee member of the international society of Artificial Intelligence in Education, and a panel member of different research journal/conference communities such as EC-TEL, IARIA, WASD.

Professor Allam Ahmed
Professor of Knowledge Management and Sustainable Development; Co-Founder of SMART KM MODEL: An Integrated Knowledge Management Framework for Organizational Excellence and led the implementation of the first of its kind in the Middle East and North Africa (MENA) Knowledge Management Framework (KMF) Musharaka. Founding President of World Association for Sustainable Development (WASD); Founding Director of SDGs Universities International Initiative (SDGsUNI); Founding Director of Middle Eastern Knowledge Economy Institute (MEKEI); Founder, in collaboration with the UNESCO Chair on Transfer of Technology (UNESCOTT), the International Diaspora Initiative/Sudan Knowledge (SK). Fellow Faculty of Public Health (FPH), UK; Fellow Chartered Institute of Marketing (CIM), UK; and Fellow (FAWB) Academy of World Business, Marketing and Management Development (AWBMMD) Australia. Professor Ahmed spent 15 years (2004-2019) at the University of Sussex Science Policy Research Unit (SPRU) (1st science and policy think tank in the UK) where he established and led Sussex’s most successful postgraduate programme MSc International Management.

Contact Us

To register/enquire about this course and all our various comprehensive list of courses and workshops, please contact us (admin@wasd.org.uk) and if you have any question and/or if you would like to request a training workshop/program not listed in our portfolio please contact our training coordinator Janet Snow at: janet.snow@wasd.org.uk.

Registration and Fees

Included in the course fee, the following learning materials will be provided:

Admission to all sessions including all coffee/tea breaks and lunches.
All overhead slides.
Case studies (print and video).
Certificate of competition from Queen Mary University of London and WASD.

What will you learn

Developing familiarity with Food Security models and its related data science applications.
Gaining an in-depth knowledge and applied data science skills about food security planning and decision support.
Understanding the potential of AI, KM and data science on your organisation/career in terms of productivity.
Understand the difference between AI, machine learning and deep learning.
It is a great opportunity for participants to gain good knowledge on AI and data science and gain background information on problem solving using AI. Moreover, you will also learn about problem description, representation and solving using AI and/or data science.

Program Structure

For each session there is an activity or set of activities. These are designed to help you engage with the introduction to the theories explored within the course.
Your tutor will be on hand to guide you through the course and will expect you to bring to bear personal experience and reflection on the topics covered.
Group work will be required for participants to engage in the workshop. Such activity allows participants to embed the new.
knowledge within their experience through active discussion and challenge.

COURSE CONTENTS:

Agricultural Statistics Fundamentals (Descriptive Statistics, Sampling, Hypothesis Testing, Errors and Estimation, Qualified Assessment)
Python for Data Science
Agricultural and Food Security Data Repositories
From Data Banks to Data Spaces
Big Data in Agriculture and Food Trade
Spatial Data and GIS concepts
Food Security Models and Indicators
Forecasting, Data Mining, and Intelligence
Artificial intelligence & Machine Learning
High Performance Computing
Visualization and Presentation

Programme Day One

Monday
08:45 - 09:00
Arrival refreshment and networking

09:00 - 10:30
Session (1) Introduction

Introduction to the course and the organisation.
Challenges facing leaders in the post Covid-19 era.
Organisation transformation in the 21st Century.

10:30 - 11:00 Tea/Coffee Break and Networking

11:00 - 12:30
Session (2) Effective Change Management and Strategic Alignment

Change Management.
Strategic Leadership.
Impact Analysis.

12:30 - 13:30 Lunch Break and Networking

13:30 - 15:00

Session (3) KM and Leadership Group Exercise (3 - 5 trainees in each group)

What is leadership?
KM spotlighting best documents.
KM pre-proposal organisation assessment.
Conclusion, presentation and discussion.

END OF DAY ONE

Programme Day Two

Tuesday
08:45 - 09:00
Arrival refreshment, reflection on Day 1 and networking

09:00 - 10:30

Session (4) Understanding Digital Transformation

DT foundations and pillars.
DT frameworks.
Innovation and business models in the context of DT.

10:30 - 11:00 Tea/Coffee Break and Networking

11:00 - 12:30

Session (5) Digital Transformation Analysis

DT readiness assessment for your organisation.
DT strategies, technologies and processes.
Research Hubs for DT, AI and organisational excellence.

12:30 - 13:30 Lunch Break and Networking

13:30 - 15:00
Session (6) Digital Transformation Brainstorming Group Exercise (3 - 5 trainees in each group)

Pick up a strategy/plan for any of your organisations.
Analyse the progress in the plan.
Identify the pain points according to your knowledge.
Suggest how Digital Transformation can be used to resolve the early-identified pain points.
Conclusion, presentation and discussion.

END OF DAY TWO

Programme Day Three

Wednesday
08:45 - 09:00
Arrival refreshment, reflection on Day 2 and networking

09:00 - 10:30

Session (7) Knowledge Management

What is KM?
Understanding KM within organisations.
KM case studies.

10:30 - 11:00 Tea/Coffee Break and Networking

11:00 - 12:30

Session (8) KM Framework

KM readiness assessment for your organization.
SMART KM Model.
Establishment of KM Community of Practice (CoP) in your organization.

12:30 - 13:30 Lunch Break and Networking

13:30 - 17:00
Session (9) Study Visit (more details to follow)

END OF DAY THREE

Programme Day Four

Thursday
08:45 - 09:00
Arrival refreshment, reflection on Day 3 and networking

09:00 - 10:30

Session (10) Artificial Intelligence for Business Excellence

Understanding AI.
Implementation of AI in business context.
Data science for managers and leaders.

10:30 - 11:00 Tea/Coffee Break and Networking

11:00 - 12:30

Session (11) Learning Strategies

Data analytics and decision support system.
Deep learning.
Machine learning.

12:30 - 13:30 Lunch Break and Networking

13:30 - 15:00
Session (12) Digital Transformation Risk Management Group Exercise (3 - 5 trainees in each group)

Select one of the early-developed Digital Transformation strategies/plans.
Align it with one of your organisational strategy.
Analyse the risk associated with applying the proposed DT plan.
Propose few risk mitigation strategies.
Conclusion, presentation and discussion.

END OF DAY FOUR

Programme Day Five

Friday
08:45 - 09:00
Arrival refreshment, reflection on Day 4 and networking

09:00 - 10:30

Session (13) Digital Transformation Strategy

DT strategy formation and performance management.
Develop a data strategy.
Future perspectives for DT.

10:30 - 11:00 Tea/Coffee Break and Networking

11:00 - 12:30

Session (14) Knowledge Management Strategy

KM and strategic management and alignment.
Evaluate the benefits of carefully thought through KM strategies.
Transformative leadership.

12:30 - 13:30 Lunch Break and Networking

13:30 - 14:30
Session (15) Conclusion and Graduation

Concluding remarks and next steps.
Presentation of Certificates.

END OF PROGRAMME

Target Participants

The course covers materials for all levels from supervisory through to senior level from the Arab States institutes working in Food Security. Participants will be assessed on three elements:

Individual participation in class (20%)
A Review report and presentation about one of the covered topics (20%)
Online test (20%)
Final project 40%)

Benefits for Employers

Meeting with other participants and enhance relationship with different organizations.
The opportunity for employers to showcase their role in different field.
At the end of the course attendees should be able to acquire a comprehensive knowledge and practical experience about AI n alignment with the local needs and capabilities.
This course will also complement the different management skills already developed through earlier courses.
Addresses the practical challenges that managers face as they seek to build, upgrade and exploit knowledge assets within their organizations
Debate the importance and value of managing knowledge within your organization
Using participants’ own organizations as cases, participants will explore how and when they can establish AI initiatives in their organizations and who will be involved?
Moreover, after competition of the course, participants to write a report, supported by the tutor, of what they have learnt and what is particularly relevant to their employers. A focus to be one aspect of the workshop which has implications for the way they will improve their professional practice when they return to their employers. This will help reassure the employers of the benefits of the programme and help consolidate the understanding of the manager.

Data Science and Analytics for Food Security

Overview

Related Sustainable Development Goals

Related Courses

Location

Country/Regions

Social Networks

Contact Us

Registration and Fees

What will you learn

Program Structure

Programme Day One

Programme Day Two

Programme Day Three

Programme Day Four

Programme Day Five

Target Participants

Benefits for Employers

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