2021 Artificial Intelligence Bootcamp
Overview
The DSN 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 DSN (Data Scientists Network formerly known as 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.
- Intuitive and basic math understanding of Machine Learning
- Understand and build simple linear regression algorithm from scratch
- Understand and build simple clustering algorithms from scratch (Kmeans and K Nearest Neighbors)
- Understand and build Support Vector Machine algorithm from scratch
- Build supervised and unsupervised Machine Learning Algorithms using standard libraries like Scikit Learn
- Apply Machine Learning to real world problems
- Intuitive and basic math understanding of Deep Neural Networks
- Build Deep Neural Networks for with TensorFlow
- Intuitively understand and build Natural Language Processing Models
- 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:
- Intuitively build a neural network.
- Overcome overfitting and underfitting in their network via the use of regularization techniques.
- Understand the importance of the data pipeline for both language modelling and computer vision.
- Understand the concept of the key, value and query in a transformer model.
- Understand the importance of embedding layers for sequence decoding and encoding.
- Understand the limitations of recurrent networks and how LSTM was used to solve some of its limitations.
- Fully optimize their model for optimal production.
- Enlightened on the importance of mathematical principle guiding all forms of neural networks.
- Intuitively determine the type of model that best solves a problem.
- 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:
- Practical Understanding of Data Visualization with PowerBi
- Practical Understanding of Data Visualization with Tableau
- Practical Understanding of SQL
- Practical Understanding of R Programming
- Practical understanding of Geospatial Analytics
- Practical Understanding of Microsoft Excel
- Practical Understanding of Mechanism Design
Posters
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
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| Time | Session 1 | Session 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
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| Time | Session | |
|---|---|---|
| 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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| Time | Session | |
|---|---|---|
| 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
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| Time | Machine Learning | Deep Learning | Reinforcement Learning/ Mechanism Design | Specialized 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, | |
| 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
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| Time | Machine Learning | Deep Learning | Reinforcement Learning/ Mechanism Design | Specialized 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, | 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
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| Time | Machine Learning | Deep Learning | Reinforcement Learning/ Mechanism Design | Specialized 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
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| Time | Machine Learning | Deep Learning | Reinforcement Learning/ Mechanism Design | Specialized 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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