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Nigerian-born Isi Idemudia Of Accenture Educates Kids On Artificial Intelligence

Nigerian-born Isi Idemudia Of Accenture Educates Kids On Artificial Intelligence


With more than 459,000 people serving clients in more than 120 countries, Accenture drives innovation to improve the way the world works and lives. Accenture is passionate about technology and is committed to helping students learn and love coding. This is why they partnered with for the 2018 Hour of Code.

The Hour of Code takes place each year during Computer Science Education Week. The 2018 Computer Science Education Week took place between December 3 – 9. The goal is to have business leaders and technical leaders volunteer to inspire children across the globe on the breadth of possibilities with computer science.

From left: Isi Idemudia (PhD) (Accenture), Rep. Kim Schofield, Mr Arlando Dawson (Principal, Northcutt Elementary school), Ms Taylor Aynisha (Gifted teacher)

To support this cause, Nigerian-born Isi Idemudia of Accenture AWS Business Group (AABG), in partnership with Georgia State Rep. Kim Schofield, representing Georgia’s 60th district, held a 3-day session with children from Northcutt Elementary School who participated in the computer science education week, under the hour of code campaign.

All the kids who participated in the hour of code with Isi Idemudia, Rep Schofield, the principal and the teacher

The coding session was a 3-day event where the children were taught the steps for building an Artificial Intelligence system using the Accenture intelligent space exploration exercise, created by Accenture.

Isi Idemudia (Accenture) and 2nd and 3rd Graders of Northcutt Elementary school during the Computer Science Education week 2018.

As part of the sessions, the children learned the definition of artificial intelligence; the techniques used to create artificial intelligence and how artificial intelligence can be applied to real life issues. They were further exposed to the following techniques during the exercise:

  • Data Preparation (Level 1): The first step to creating many artificial intelligence techniques. Machine learning algorithms learn from data and the data must be ready for the machine to understand.
  • Unsupervised Learning (Level 2 & 3): Unsupervised learning is a way that computers can get smarter by analyzing and detecting patterns from a data set. When no prior pattern or structure of the dataset is known, we call this process ‘unsupervised.’
  • Reinforcement Learning (Level 4): Reinforcement learning is a type of learning where algorithms learn the optimal behaviour through trial and error, influenced by programmed risk and reward. Reinforcement learning is very like how humans learn. Reinforcement algorithms can learn the optimal way to play a game and thereby outperform human players by far.
  • Supervised Learning (Level 5 & 6): Supervised learning is a way a computer can get smarter by identifying groups within a data set based on training examples provided by a “supervisor.” Because the algorithm already knows a pattern from the training examples, the learning is steered in the right direction, hence the name ‘supervised.’
  • Optical Character Recognition (Level 7): Optical Character Recognition (OCR) is a technique that allows computers to read handwritten text from images or PDF documents.
  • Speech Recognition (Level 8): Speech recognition is the technology that records a spoken sentence and translates that into digital text. It enables us to talk to our mobile and home digital assistants, like Apple’s Siri or Amazon’s Alexa.
  • Natural Language Processing (Grammar) (Level 9): Natural Language Processing (NLP) is an area of research that teaches computers how to communicate in natural languages such as English, French or Chinese. This requires computers to understand incoming text or speech, as well as being able to form grammatical sentences in return.
  • Automation and Robotics (Level 10): Robotic automation is a type of software that replicates the actions of people controlling computer systems to run business processes. The software copies people by doing activities like logging into a system, entering data, clicking on ‘OK’, copying and pasting data between systems, etc.

Isi Idemudia is a Certified Solutions Architect with in-depth and practical knowledge of cloud architecture including hybrid frameworks for highly available solutions and fault tolerant data warehouses. She holds a Doctor of Philosophy degree in Innovation and Technology Management from the University of Pretoria/Port Harcourt and a Diploma in Innovation and Strategy from Harvard University. You may follow her on LinkedIn.

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