Welcome to the 2019 bootcamp. This year, we will run in multiple streaming sessions, culminating in the Finals of the InterCampus Machine Learning competition and the intermediate stream on Deep Learning concepts.
It is a six-day residential, all-expenses-paid Artificial Intelligence Bootcamp and Hackathon on emerging trends in machine learning and deep learning and will run between 19 and 23 November 2019. The intent of the bootcamp and hackathon is to build world-class capacity in advanced data analytics, upskill financial inclusion data analysts and researchers in emerging best practices, and to support the development of contextually relevant algorithm and tech innovation.
The bootcamp will include face-to-face teaching, virtual online classes, and a hands-on hackathon using the Zindi.com platform. Distinguished data scientists from leading institutions including the Google AI Lab, Stanford AI Research, GitHub and Bankable Frontiers Associates will facilitate the sessions. An ongoing pan-Nigeria selection competition will select the 150 best-performing students/researchers/practitioners that will be accepted into this free bootcamp. The bootcamp will also serve as the final test of the Inter-Campus Machine Learning Competition, sponsored by BlueChip Technologies. Over 10,000 students from 90 universities and polytechnics participated in the preliminary phase. The bootcamp will also include a very competitive hackathon using Nigeria-centric data to explore, extrapolate and explain emerging possibilities in algorithms.
The bootcamp is driven by a broader strategic intent to accelerate Nigeria’s development through a solution-oriented application of machine learning in solving social/business problems and to galvanize data science knowledge revolution for employability, technology innovation and sustainable socio-economic development.
The bootcamp learning sessions will be enriched by leading experts from different parts of the world, including Dr. Dumebi Okwechime, Chief Decision Scientist, RenMoney; Kris Sankaran, PhD, MILA Canada; Prof. Thomas G. Dietterich,Emeritus Professor of Computer Science, USA; Prof Anima Anandkumar, Professor of Computing, CalTech; Ike Okonkwo, Data Scientist Zynga Games, California; Kathleen Siminyu, Head of Data Science, Africa’s Talking; Dr. Stephen G. Odaibo, CEO, RetinaAI, USA; Samuel Edet, Joint PhD, Student IMT, Italy and Ku Leuven, Belgium; Wale Akinfaderin, PhD, Senior Data Scientist, Duke Energy; Emmanuel Doro, PhD, Principal Data Scientist, Jet.com, USA; Uzo Mkparu, Group Head, CRM, Customer Analytics & Insights FCMB; Pascal Bernard, Head of Data Science, OneFi; Elaine Nsoesie, PhD, Assistant Professor, Botson University; Prof. Kunle Oluktun, Professor of EE and CS at Stanford University; Dr. Nnana Orieke, Cloud Solution Architect, Data and AI, Microsoft; Nicholas Litombe, PhD, Data Scientist, Physicist; Robert John, Data Science Officer, EnterFive; Dr. Sakinat Folorunsho, Lecturer, Computer Science, OOU; Olubayo Adekanmi, Convener, Data Science Nigeria, Chief Transformation Officer, MTN Nigeria.
Microsoft, BlueChip Technologies, Terragon Group, AXA Mansard, FCMB, InstaDeep AI, ProShare Nigeria, The Guardian, Guardian TV, OneFi, KPMG and Zindi South Africa are the sponsors and partners of the bootcamp and summit.
Participation in the 6 days Artificial Intelligence Bootcamp is based on a pre-qualification competition on “Staff Promotion Algorithm” on Kaggle, the global Machine Learning competition platform. click here.
Schedule
Tuesday 19 November 2019: Welcome Session
TIME
FOCUS/SPEAKERS
TOPICS
3:00 – 4:00
Welcome Refreshment, Registration
4:00 – 5:30
Welcome session, Camp Rules and Welcome Prof Thomas Dietterich,Masterclass by BigML’s
Chief Scientist & Emeritus Professor of Computer
Science at Oregon State University.
Robust Artificial Intelligence and
Trustworthy Machine Learning
5:30 – 6:00
Welcome Quiz and wins
6:00 – 7:00
Terragon Group Masterclass on AI emerging trends
Babatunde Adeniran & Esemeje Omole
Data Scientists, Terragon Group, Nigeria
Masterclass on Emerging Trends in Machine Learning/Artificial Intelligence in the business space
7:00 – 8:00
Dinner and check-in into rooms
Wednesday 20 November 2019: Tools, Concepts and Frameworks
TIME
FOCUS/SPEAKERS
TOPIC
8:00 – 8:30
Breakfast
8:30 – 10:00
Alina Game, GRID3 Nigeria Data Analyst
Edith Darin, GRID3 Nigeria Researcher
Michael Harper, GRID3 Nigeria Data Analyst
Wole Ademola Adewole, GRID3 Nigeria GIS consultant
Sophie Delaporte, GRID3 Nigeria Communications Manager
Introduction to Geospatial Data Analytics with GRID3
10:00 – 11:30
PARALLEL SESSION – different topics in different classes based on participants’ level and interest
Basic Tool Mastery: Quick run through, short cuts and fast-track expert knowledge
Wuraola Oyewusi, Research Lead, Data Science Jupyter/Python
Nigeria
Jupyter/Python
11:30 – 1:30
PARALLEL SESSION – different topics in different classes based on participants’ level and interest
Conceptual Exploration of Maths for Machine and Deep Learning
Maths and Concepts in Machine Learning: Samuel Edet, Doctoral Researcher , Economics,
Networks and Business Analytics at IMT School
for Advanced Studies, Italy
ML – Defining a Model Cost /
Loss / Error Function,
Mathematical Optimization,
Gradient Descent, Stochastic
Gradient Descent etc.
Maths and Concepts in Deep Learning: Dr Stephen Odaibo, CEO/Founder Retina-AI,
Houston, USA
DL: Introduction to Deep
Learning, Core Maths concepts,
Common Activation Functions ,
Deep Neural Network, Forward
and Back-Propagation etc.
2:00 – 5:00
PARALLEL SESSION – different topics in different classes based on participants’ level and interest
Hands-on Machine Learning and Deep Learning via mini-projects
Samuel Edet, Doctoral Researcher , Economics,
Networks and Business Analytics at IMT School
for Advanced Studies, Italy & band Ku Leuven,
Belgium
Women in AI Session Dr Sakinat Folorunso, Computer Science Lecturer/Researcher, OOU & Lead for WIDS
6:00 – 7:00
Daily Book Prize wins
Industry Engagement Session Uzo Mkparu HCIB, Assistant Vice President/Group Head, CRM, Customer Analytics & Insights, First City Monument Bank Limited
What industries are looking for in a Data Scientist
7:00 – 8:00
Dinner
8:00 – 9:00
Masterclass on Artificial Intelligence Engineering Prof Kunle Olukotun,Professor of Electrical
Engineering and Computer Science at Stanford
University and Director of the Pervasive
Parallelism Laboratory, USA. Founder of
Mines.io
Future Computer Systems for
Software 2.0
Thursday 21 November 2019 : Theoretical Depth and Exploration
TIME
FOCUS/SPEAKERS
TOPIC
8:00 – 8:30
Breakfast
8:30 – 9:30
Sabrina Smai,
Software Engineer – Microsoft, Canada
Problem-solving and Solution Approach in Artificial Intelligence
9:30 – 11:00
PARALLEL SESSION – different topics in different classes based on participants’ level and interest
Practical AI in use
Elaine Nsoesie PhD, Assistant Professor at
Boston University School of Public Health/
Institute for Health metrics and Evaluation,
Boston, USA
Artificial Intelligence for Health –
use for non-traditional data for
health risk prediction
Pascal G. Bernard, Head of Data Science, CARBON/ One Finance & Investment Ltd., London
Jacobo Varela, Data Scientist, CARBON/ One Finance & Investment Ltd., London
Artificial Intelligence for Financial Inclusion
9:00-10:00 Alternative Data and Risk Prediction
10:00-11:00 Graph Databases: A key to addressing Financial Services challenges.
Margaryta Ostapchuk,Technical Evangelist, Commercial Software Engineering team, Microsoft Canada
Cognitive Solutions Development in Microsoft Azure
11:00 – 4:00
PARALLEL SESSION – different topics in different classes based on participants’ level and interest
PARALLEL SESSIONS ON AI THEORIES IN PRACTICE
(2) Computer Vision CNN: Convolutional Neural
Networks Dr Emmanuel Doro, Director, Data Science at
Walmart, USA
(3)Natural Language Processing: Kathleen Siminyu, AI for Development Network,
Kenya & Ayodele Olabiyi, Product Researcher
and NLP Project Lead, Data Science Nigeria & Wuraola Oyewusi, Research/Innovation Lead, Data Science Nigeria
4:00 – 5:30
PARALLEL SESSION – different topics in different classes based on participants’ level and interest
AI PhD Research or Running an AI-first start-up
Kris Sankaran ,PhD, postdoc at MILA, Montreal, Canada
& Elaine Nsoesie PhD, Assistant Professor at Boston University School of Public Health/ Institute for Health metrics and Evaluation
Writing scientific Research paper and PhD readiness
Masterclass on Artificial Intelligence At Scale Anima Anandkumar, Professor of Computing at
California Institute of Technology & Director of
Machine Learning research at NVIDIA
Trinity of AI (Data, Cloud,
Algorithm) – imperatives of AI at
scale
Friday 22 November 2019 : Real-world Application Enablers and Use cases
TIME
FOCUS/SPEAKERS
TOPIC
7:30 – 8:00
Breakfast
8:00 – 9:00
Microsoft Azure DevOps Best practice: Dara Oladapo, Customer Success Manager, Microsoft4Afrika
Machine Learning best practices for Digital Media and Programmatic Advertising Analytics Mohit Rawan Terragon Dial-in session
Project-based immersion into Machine Learning best practices for Digital Media and Programmatic Advertising Analytics
4:00 – 5:30
Open House: Building a world-class
career in AI& Data Science Dumebi Okwechime PhD, Chief
Decision Scientist – Renmoney, Lagos Nicholas Litombe PhD, Senior Data
Scientist at Unacast, USA Margaryta Ostapchuk, Technical Evangelist, Commercial Software Engineering team, Microsoft Canada Sabrina Smai, Software Engineer – Microsoft, Canada
5:30 – 7:00
Introducing Malaria competition and dataset (24 hour Hackathon)
Prof Delmiro Fernandez-Reyes
Reader in Digital Health, University College London Hackathon break and work
Introduction to the Insurance Dataset for recruitment by Axa Mansard
Introduction to the Max.ng Challenge
7:00 – 8:00
Dinner
8:00 – 12:00
Hackathon Individual work session
Saturday 23 November 2019: Real-world Application Enablers and Use cases
TIME
FOCUS/SPEAKERS
TOPIC
8:00 – 8:30
Breakfast
8:30 – 9:30
Artificial Intelligence for Good AI Poster session
9:30 – 11:00
Statistical Best Practice Masterclass Kris Sankaran PhD, postdoc at MILA,
Montreal, Canada
