2021 Artificial Intelligence Bootcamp

6 Tracks | 40 Speakers | 400 Finalists

Overview

The Data Science Nigeria Artificial Intelligence (AI) bootcamp, an all-expenses-paid learning bootcamp that builds Africa’s capacity in the use of advanced machine learning and deep learning concepts and drives the application of AI for socio-economic development.  

The bootcamp is driven by a broader strategic intent to accelerate Africa’s development through the solution-oriented application of machine learning to solve social and business problems, and to galvanize a data science knowledge revolution improving employability, technological innovations and sustainable socio-economic development. This reinforces the DSN’s vision to train one million talents in the next ten years through world-class knowledge and best practices applications.

The 2021 AI Bootcamp

It is here again!

The Data Science Nigeria AI Bootcamp – a gathering of the best of the best, taught and mentored by world-class experts! You cannot afford to miss this immersion of world-class learning, best practice knowledge and cutting-edge mentoring.

The AI Bootcamp 2021 will hold VIRTUALLY between October 25 and November 2, 2021 and will accept Professional, Researchers and 400 best candidates after an intensive 50-day learning, Hackathon and a Validation/Assessment Quiz.

Timeline

The roadmap to the 2021 AI Bootcamp

50 Days Pre-Bootcamp Program

The Pre-Bootcamp Study Program is an intensive program geared towards preparing participants for the AI Bootcamp. 

Learning Contents are open-source expert contents hosted on YouTube.

Learning Assessments hosted on Google Classroom.

Learning Support & Collaboration coordinated on Slack.

Pre-Bootcamp Content Structure

Machine Learning Track

This stream covers topics and concepts in:

  • Python Programming for Machine Learning.
  • SciKit-Learn for Machine Learning
  • Machine Learning Theories and Applications

The following is an outline of the learning outcome for the machine learning track.

  1. Intuitive and basic math understanding of Machine Learning
  2. Understand and build simple linear regression algorithm from scratch
  3. Understand and build simple clustering algorithms from scratch (Kmeans and K Nearest Neighbors)
  4. Understand and build Support Vector Machine algorithm from scratch
  5. Build supervised and unsupervised Machine Learning Algorithms using standard libraries like Scikit Learn
  6. Apply Machine Learning to real world problems
  7. Intuitive and basic math understanding of Deep Neural Networks
  8. Build Deep Neural Networks for with TensorFlow
  9. Intuitively understand and build Natural Language Processing Models
  10. Understand, build and implement Convolutional and Recurrent Neural Networks

Deep Learning Track

This stream covers topics and concepts in:

  • Deep Learning Theories.
  • Computer Vision
  • Natural Language Processing
  • Reinforcement Learning

The following is an outline of the learning outcome for the deep learning track:

  1. Intuitively build a neural network.
  2. Overcome overfitting and underfitting in their network via the use of regularization techniques.
  3. Understand the importance of the data pipeline for both language modelling and computer vision.
  4. Understand the concept of the key, value and query in a transformer model.
  5. Understand the importance of embedding layers for sequence decoding and encoding.
  6. Understand the limitations of recurrent networks and how LSTM was used to solve some of its limitations.
  7. Fully optimize their model for optimal production.
  8. Enlightened on the importance of mathematical principle guiding all forms of neural networks.
  9. Intuitively determine the type of model that best solves a problem.
  10. Build a full data and model pipeline for any problem relating to vision and sequences.

Specialized Track

This stream covers topics and concepts in:

  • Data Visualization with PowerBi.
  • Data Visualization with Tableau.
  • SQL
  • R-Programming
  • Geospatial Analytics
  • Microsoft Excel
  • Mechanism Design

The following is an outline of the learning outcome for the Specialized track:

  1. Practical Understanding of Data Visualization with PowerBi
  2. Practical Understanding of Data Visualization with Tableau
  3. Practical Understanding of SQL
  4. Practical Understanding of R Programming
  5. Practical understanding of Geospatial Analytics
  6. Practical Understanding of Microsoft Excel
  7. Practical Understanding of Mechanism Design

Posters

1st Position

Drone Based Monitoring System
For
Large Scale Farming

PDF Poster: Here
Video Presentation: Here

Written by: Paul Okewunmi, Oluwadunsin Fajemila, Amazing-Grace Olutomilayo

2nd Position

Driving an Inclusive Society: Sign-to-Speech Modeling for Sign Language Understanding

PDF Poster: Here
Video Presentation: Here

Written by: Steven Kolawole, Opeyemi Osakuade, Babatunde Kazeem Olorisade

3rd Position

Chemotronix: IoT device enabled
with
AI for carbon reduction

PDF Poster: Here
Video Presentation: Here

Written by: Peace Bello, Victor Olufemi, Grace Omojola, Dayo Abiona, Oyinbayode Akinleye

Application of Machine Learning For Reservoir Facies Classification in Port Field, Offshore Niger Delta

PDF Poster: Here
Video Presentation: Here

Written by: Alexander Nwakanma, Jerome Asedegbega, Oladayo Ayinde

Reducing the Risk of Female Gender Based Violence using Interpretable Machine Learning (South As a Use Case)

PDF Poster: Here
Video Presentation: Here

Written by:
Raheem Nasirudeen Adeleye

Májẽkéyé-Bà: Pest Prevention Unmanned Aerial Vehicle

PDF Poster: Here
Video Presentation: Here

Written by: Segun Adebayo, Aworinde Halleluyah Oluwatobi, Akinwunmi Akinwale, Ayandiji Adebamiji

Smallholders’
Loan Accessibility Predictions using Machine Learning Methodologies

PDF Poster: Here
Video Presentation: Here

Written by: Oladimeji Samuel Sowole

Terminator: AI Pest Diagnostic Tool

PDF Poster: Here
Video Presentation: Here

Written by: Gbadamosi Oluwaseyi Emmanuel, Tejumola Adeseun Asanloko

OceanAI - Saving our Oceans with AI

PDF Poster: Here
Video Presentation: Here

Written by: Bunmi Akinremi, Adeyemi Ayomide

Machine Learning In Cyber Security

PDF Poster: Here
Video Presentation: Here

Written by:
Mustapha Muhammad Ibrahim

Tech in Health: Building a web-based medical service

PDF Poster: Here
Video Presentation: Here

Written by: Samuel Dayo Adesola

Efficient Data-Mining Algorithm For Predicting Heart Disease Based On Angiographic Test

PDF Poster: Here
Video Presentation: Here

Written by: Banjoko Alabi Waheed, Waheed B. Yahya, Mohammad K. Garba, Razaq B. Afolayan, Kawthar O. Abdulazeez

Gleason Score Prediction for The Severity of Prostate Metastasis Using Machine Learning

PDF Poster: Here
Video Presentation: Here

Written by: Opeyemi Bamigabade, Popoola O.P1, Abubakar-Sidiq H.L, Kehinde Tijani Habeeb, Oluyemi Akinloye

Learning Bandits’ Tactics Using Stackelberg Security Game Model and Machine Learning Approach

PDF Poster: Here
Video Presentation: Here

Written by: Halleluyah Oluwatobi Aworinde, Segun Adebayo, Akinwale Akinwunmi, Olalekan Awoniran, Yadirichi Nwandu

Artificial Intelligence for Efficient Road Safety in Nigeria

PDF Poster: Here
Video Presentation: Here

Written by:Ogunniran Oluwasijibomi, Oluwadamilola Deborah Salau, Taiwo Odetola, Faith Oluwole

The AI Bootcamp Schedule

The AI Bootcamp will have sessions for the following groups:

Professionals

Dedicated sessions for Industry Professionals. This will feature- Use Cases, Amazing Demos, learn a skill (Skills area relevant to the industry), Meet a Mentor and Networking. This session will be OPEN TO ALL.

Ladies in AI

Dedicated sessions for Ladies. This will feature- Ethics of AI, Women Issues, Algorithmic Bias and Networking. This session will be OPEN TO ALL.

Researchers

Dedicated sessions for Researchers. This will feature- Research Ethics, Tutorials on World class paper writing, Poster presentation, Paper reviews and Research Collaborations. This session will be OPEN TO ALL.

Bootcamp Finalists

The 400 Finalists will have series of intensive learning sessions. The plenary and break-out sessions of the 2021 AI Bootcamp will focus on Academic Researchers, Industry Professionals and Beginners-to-Intermediate students.

Monday 25th October 2021 – Professionals Stream

Swipe right to view full table

TimeSession 1Session 2
10:00 - 11:30am Opening Event
Welcome Address: Bayo Adekanmbi, Convener Data Science Nigeria
Welcome Keynote: Dr Uyi Stewart, Chairman, Data Science Nigeria
Opening Event
AI Bootcamp Onboarding: Data Science Nigeria
11:30 – 12:30pm Break
12:30 – 2:00pm Data Science for Human Resource/People Analytics
Dr Raphael Yemitan, PWC
2:00 – 2:30pm Break
2:30 - 4:00pm Data warehouse 101
Damilola Ojo,
Delta Partners, Dubai
Customer Lifecycle Management through Data Analytics
Anthony Obi, MTN Nigeria
4:00 – 4:30pm Break
4:30 - 6:00pm Big picture Session: Big Picture Session: AI for Social and Business Growth in Africa
Prof. Ndubuisi Ekekwe, Lead Faculty, Tekedia Institute

Tuesday 26th October – Ladies in AI Stream

Swipe right to view full table

TimeSession
10:00 am - 12:00 pm Breakfast Session
Building a Successful Career in Data Science & Artificial Intelligence

Panelists
Amulya Badlani
AI Dev Ecosystem | Emerging Areas Strategy at NVIDIA | Tech Mentor
Wafaa Mohammed
Master's Student in Machine Intelligence at African Institute for Mathematical Sciences
Dr. Sakinat Folorunsho
Department of Mathematical Sciences, Olabisi Onabanjo University
Dr Adeyinka Oresanya
Machine Learning Researcher, Data Storyteller Katalista Ventures
Moyosore Lawal
Solutions Architect at Syntelli Solutions Inc.
Ndane Ndazagha
Data Scientist | Data Analyst at Eden Life
12:00 – 12:30 pm Break
12:30 – 2:00 pm Breakfast Session
Replay
2:00 – 2:30 pm Break
2:30 – 4:00 pm Machine Learning with BigML
Prof. Thomas Dietterich,
Oregon State University
4:00 - 6:00pm Identifying and Maximizing Opportunities for Ladies in AI
Keynote: Dr Natalie R.,
Founder of Robots Can Think

Panelists
Diane Igoche,
Associate Professor of Data Analytics, Robert Morris University United States

Dr Natalie R,
Founder of Robots Can Think

Aishatu Gwadabe,
Peace Technologist

Afolabi Ibukun
Department of Computer & Information Sciences,
Covenant University

Wednesday 27th October – Researchers Stream

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TimeSession
10:00 am - 1:00 pm Poster Session
Top 15
1:00 – 1:30 pm Break
1:30 – 2:30 pm Breakout Session
Networking Session with Poster Presenters
&
Best Poster Voting
2:30 – 3:00 pm Break
3:00 - 5:00pm Panel Session
Best Practice in Research Writing

Panelists
Bonaventure Dossou,
AfricaNLP Researcher at Masakhane
Kobby Panford-Quainoo,
Tutor at African Institute for Mathematical Sciences/Machine Intelligence
Chris Emezue,
AfricaNLP Researcher at Masakhane
Gbètondji Jean-Sébastien Alexandre Dovonon,
Machine Learning Researcher
Tunde Ajayi,
AfricaNLP Researcher at Masakhane

Thursday 28th October – Bootcamp Finalists

Swipe right to view full table

TimeMachine LearningDeep LearningReinforcement Learning/ Mechanism DesignSpecialized Skills
9:00 - 10:00 am AI Bootcamp Onboarding for Finalists
Data Science Nigeria
10:00 – 10:30 am Break
10:30 – 12:30 pm Machine Learning with Microsoft Azure
Dr. Nnanna Orieke, Microsoft
Mathematics for Artificial Intelligence
Samuel Edet,
World Bank Group
Mechanism Design
Dr. Eric Sodomka,
Facebook
2:00 – 2:30 pm Break
2:30 - 4:30pm Understanding Machine Learning Algorithms
Kris Sankaran,
University of Wisconsin-Madison
Computational Game Theory
Prof. Hau Chan,
University of Nebraska-Lincoln
4:30 – 5:00 pm Break
5:00 – 6:30 pm Big Picture Session
What's now and next for Artificial Intelligence & Intelligent Automation
Prof. Kirk Borne

Friday 29th October – Bootcamp Finalists

Swipe right to view full table

TimeMachine LearningDeep LearningReinforcement Learning/ Mechanism DesignSpecialized Skills
9:00 - 11:00 am Soft Skills for Tech Talents
Daniel Emenahor,
Senior Learning Development Associate, Jobberman
11:00 – 11:30 am Competition
Mr & Mrs Algorithm
11:30 – 12:00 pm Break
12:00 – 2:00 pm Mechanism Design
Dr. Eric Sodomka,
Facebook
Geospatial Analytics
GRID3 Team
Asmau Bugaje,
Sophie Delaporte
2:00 – 2:30 pm Break
2:30 - 4:30pm Deep Learning Masterclass with Retina.ai
Dr. Stephen Odaibo & Retina.ai team
Geospatial Analytics
GRID3 Team
Romain Goldenberg
Ollie Pannell
4:30 – 5:00 pm Break
5:00 – 6:30 pm Big Picture Session
AI Start-up Building & Funding
Osayi Igharo,
Rippple VC

Monday 1st November – Bootcamp Finalists

Swipe right to view full table

TimeMachine LearningDeep LearningReinforcement Learning/ Mechanism DesignSpecialized Skills
9:00 - 11:00 am Understanding Knowledge Graph Engineering
Emeka Okoye,
Cymantiks
Building Data Science Solutions for the Industry
Dr. Dumebi Okwechime,
Kobo360
11:00 – 12:00 pm Break
12:00 – 2:00 pm Data Story Telling
Humphrey Obie,
Monash University
2:00 – 2:30 pm Break
2:30 - 4:30pm Process Mining and Semantic-based Modelling
Kingsley Okoye (PhD),
Tecnológico de Monterrey
Introduction to Multi-agent Systems
Dr Long Tran-Thanh,
University of Warwick
Reinforcement Learning
Dr. Remy Sekou,
IBM
4:30 – 5:00 pm Break
5:00 – 6:30 pm Big Picture Session
Data Governance for Ethical AI
Prof. Neil Lawrence,
University of Cambridge

Tuesday 2nd November – Bootcamp Finalists

Swipe right to view full table

TimeMachine LearningDeep LearningReinforcement Learning/ Mechanism DesignSpecialized Skills
10:00 - 11:00 am Quiz Time
11:00 – 12:00 pm Break
12:00 – 2:00 pm Data warehouse 101
Damilola Ojo,
Delta Partners, Dubai
2:00 – 2:30 pm Break
2:30 - 4:30pm Spatial Analysis
John Quinn,
Google Research, Sunbird AI,
Quantum AI Computing
Wale Akinfaderin,
Amazon Web Services (AWS)
Quantitative Analytics for Business
Elias Kruger,
Wells Fargo
4:30 – 5:30 pm Opportunity Desk
Career Fair with Industry Partners
6:00 – 7:00 pm Awards & Recognition

AI Bootcamp Awards & Opportunities

  • Internships from top companies
  • Scholarships
  • Mr. & Miss Algorithm for Community value Award
  • Best Poster Award
  • AI School of the Year Award
  • Industry Recognition Award

Frequently Asked Questions

The pre-study program is open to everyone.

This class is entirely for newbies, intermediates, and experts who want to cover topics in Machine Learning, Deep Learning and Specialized skills.

By registering, you will get access to all the learning contents, daily assessments and support.

Participation in the Pre-Study program is not an automatic ticket to the 2021 AI Bootcamp but will prepare you to have foundational skills in all the topics that will be discussed at the Bootcamp.

You will be required to participate in the Qualification Hackathon and Validation/Assessment quiz to qualify for the Bootcamp.

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