Some trivia before we begin. Answers are at the bottom of this newsletter. 

AI stands for Artificial Intelligence, and this refers to intelligent machines that can perform tasks which typically require human intelligence. For Terminator fans, think Skynet.

You’ve probably used AI before. Yes, ChatGPT is currently the most prominent example of AI but before its launch, AI was already in our lives. From the use of weather apps and Google Maps to facial recognition software on phones and smart assistants like Amazon’s Alexa or Apple’s Siri, we’ve all interacted with AI at some point.

As technology advances, AI is becoming increasingly prevalent in our daily lives, from voice assistants on our phones to recommendation algorithms on social media platforms. With the growing demand for AI applications, the industry is expanding rapidly, making it an exciting career option for those interested in cutting-edge technology.

So how does Siri know your voice? How does Spotify recommend music based on songs you’ve already listened to? Are there people running AI?

AI entails intelligent electronic systems and bots that can perceive and interpret human prompts in their environment and take actions that result in needed success. For this to work though, human beings have to train these machines in a process called machine learning—they have to teach the machine to recognise these human behaviours and respond accordingly. And they do this by feeding the machine large amounts of data and writing code—algorithms—so that it can understand that data.

Image source: Harsh Aryan

It’s just like raising a child, except this one does exactly what you tell it to do and isn’t sticky 80% of the time—and you can work it to the bone without human rights organisations crying child abuse. Jk, jk.

The Entering Tech Shorts

This edition of Entering starts with a question on if no-code development is the same as software engineering but with cheat codes. Foluso Ayodele, in 60 seconds, tells you everything you need to know about being a no-code developer.

Watch the 1-minute YouTube Short here!

Skills needed: Mathematics, Machine Learning, Programming Skills (Backend), and Data Analysis.

1. Machine Learning Engineer: Machine learning engineers build and maintain machine learning systems that can learn and improve over time. They work on algorithms and models that can analyse data, detect patterns, and make predictions.

2. Data Scientist: Data scientists collect, process, and analyse large data sets to identify trends and insights. They use statistical and machine learning models to develop predictive models and inform business decisions.

3. Natural Language Processing (NLP) Engineer: NLP engineers develop algorithms and models that can understand and process human language. They work on applications such as voice assistants, chatbots, and sentiment analysis.

4. Computer Vision Engineer: Computer vision engineers develop algorithms and models that can analyse visual data such as images and videos. They work on applications such as facial recognition, object detection, and self-driving cars.

5. Robotics Engineer: Robotics engineers design and build robots that can perform tasks autonomously. They work on applications such as industrial automation, medical robots, and drones.

Attend the Africa Teen Tech Festival

Explore the future of tech and kickstart your career at the Africa Teen Tech Fest! Gain valuable guidance on job hunting and identify career paths aligned with your interests. Participate in Drone Soccer, e-Sports and Virtual Reality exhibits. Teens can win ₦250,000 in cash prizes!

Register for the festival now!