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

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.

The Bootcamp timetable will be released on October 20th, 2021

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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