What Computer Science and Artificial Intelligence really are, and how they are changing engineering, science, business and the humanities.
Engineering · Science · Business · Humanities — this room is for everyone
Your host todayComputer Science lecturer at NCUK · software engineer · co-founder & CTO
I didn't learn all this to stay in front of a screen. I learned it to build things people use.
Click a card to add one · right-click to remove
12 live demos · you will flip real bits, build an Instagram post, train an AI and land a rocket.
Spoiler: it's not about computers. Like astronomy isn't about telescopes.
Hollywood hackers, green text, hoodies.
Doctors, bankers, architects, linguists and artists all use it. Writing code is just the tool.
Break a huge problem into small ones. "Build Uber" → map, payment, matching drivers.
Exact steps to solve each piece. A recipe a machine can follow, billions of times a second.
Everything becomes numbers: photos, music, your voice, your DNA, a poem.
Hide the details. You drive a car without knowing how the engine burns fuel.
From a spark of electricity to a photo on Instagram. Lights down, sound up.
Esc to exit · M to mute
That's all a computer "sees". No letters, no photos, no music: just current flowing, or not.
A switch with no moving parts, controlled by electricity itself. Smaller than a virus: a modern phone chip has about 20 billion of them.
Each one can switch on and off billions of times every second.
Same 8 switches, three meanings. The program decides how to read them. Try making 65 (the letter A) or 255 (all on).
Click the inputs. AND: the door opens only with your card AND the right PIN. OR: the alarm rings if the door OR the window opens. Every decision a computer makes is built from these.
Click the bits of A and B. The answer is computed only with AND, OR and XOR gates, exactly like inside a chip.
A phone processor does this billions of times a second. Multiplying = adding many times. Photos, games and AI = an ocean of additions.
get the next instruction from memory
understand it: "add these two numbers"
do it with the logic gates
= 3 billion cycles every second
fast memory: what the phone is using right now
your photos and apps, kept even when it's off
10111000 00000001 00000000 00000101 00000010 00000000 11001101 00100001
MOV AX, 1 ADD AX, 2 INT 21h
int total = 1 + 2;
printf("%d", total);total = 1 + 2 print(total)
A compiler or interpreter translates the nice language down to 0s and 1s, like a translator between you and the chip.
Click the heart to zoom in and see the numbers inside every pixel.
This is real HTML + CSS, the languages of every web page. Change the text, the colour or the emoji and watch.
Algeria is connected to Europe by several undersea fibre-optic cables across the Mediterranean. Your like literally travels as light under the sea.
Instagram is not magic. It's billions of tiny switches, organised by people who learned to think in layers.
And every one of those layers was built by someone who was once a student, like you.
Notice: two of the founders of computing were women, and one was a poet's daughter (Ada was Lord Byron's daughter).
Machines that learn from examples.
Protect banks, hospitals, countries.
Web, mobile, games, the apps you use daily.
Code that moves in the real world.
How 5 billion people connect.
Making technology human.
The next frontier of computing.
Films, games, simulations, like this 3D world.
Not a robot that wants to take over the world. A very powerful pattern-finding machine.
"If the email contains 'you won a prize', mark it as spam." A human writes every rule. It breaks when spammers change words.
Show it 1 million emails labelled spam / not spam. It discovers the patterns itself, even ones no human noticed.
AI ⊃ Machine Learning ⊃ Deep Learning (neural networks) ⊃ Generative AI (ChatGPT, image generators)
Click to add red points · Shift+click (or switch) to add blue points. Then press Train and watch the AI learn the border.
A tiny neural network: 2 inputs → 8 neurons → 8 neurons → 1 output. It adjusts its 105 numbers ("weights") again and again to make fewer mistakes. That's all "learning" is.
It's trained on a huge part of the internet, books and code: trillions of words.
Given "The capital of Algeria is", it learns that "Algiers" is the most likely next word.
Humans rate its answers, so it learns to be helpful and polite (RLHF).
It doesn't "know" things like you do. It's an extremely good guesser, which is why it can sound sure and still be wrong.
This model only counts which word usually comes after another word in its training text. Click a word to add it, or let it write.
Real LLMs do the same thing, but they look at thousands of previous words, not just one, and they learned from trillions of words, not 40 sentences.
Explaining, summarising, brainstorming, translating, drafting, writing code, finding patterns in data.
Being always right. It can invent facts, sources and quotes ("hallucinations"). It can repeat biases in its data.
Use it to learn, not to cheat: your work must be your own, and you must check what AI tells you.
The best prompt formula: Role + Task + Context + Format. "You are a biology tutor. Explain osmosis to a foundation student, with one everyday example, in 5 lines."
Next: rockets, robots and engineering. Come back on time, there's a game!
Today, the most powerful tool of a mechanical, civil or electrical engineer is not a wrench. It's software.
Since December 2015, SpaceX Falcon 9 boosters fly back and land upright. Some have flown more than 20 times.
Software computes the landing path in real time, many times per second.
Optimisation algorithms (convex optimisation) find the fuel-saving path to the landing pad, while wind pushes the rocket.
In 2021 NASA's Perseverance compared camera images to maps during descent and chose a safe spot by itself: Terrain-Relative Navigation.
Hold Space (or the button) to fire the engine. ← → to steer. Land at less than 2 m/s on the pad.
The autopilot is a PD controller, 6 lines of code engineers use everywhere: drones, cruise control, robot arms, even your fridge.
Planes, F1 cars and wind turbines are tested in virtual wind tunnels: millions of tiny air cells solved by computers.
Finite element analysis simulates how bridges and towers bend in earthquakes, useful in a seismic country like Algeria.
A live virtual copy of a real factory, engine or city, fed by sensors. Test changes on the copy, not on the real thing.
Factory arms, warehouse robots, surgical robots and walking robots like Boston Dynamics' Atlas.
Jet engine makers stream sensor data from engines in flight and fix parts before they fail.
Robotaxis (e.g. Waymo) carry paying passengers with no driver in several US cities.
AI balances power grids with solar and wind, a big topic for Algeria's solar future.
Data, simulation, automation, AI. The #1 language in science and engineering.
Control systems, signals, vehicles. Used in industry and universities.
Build real robots and sensors at home for a few thousand dinars.
Weekend project idea: a plant that waters itself (soil sensor + Arduino + 15 lines of code).
Problems that took 50 years are being solved in months.
Proteins are chains that fold into 3D shapes, and the shape decides what they do in your body. Finding one shape used to take scientists years of lab work.
AlphaFold (Google DeepMind) predicted the structures of about 200 million proteins: nearly every known protein.
Demis Hassabis and John Jumper (AlphaFold), with David Baker (protein design). AI is now a Nobel-level science tool.
AI helps radiologists spot cancers in mammograms and scans, and catches things tired eyes miss.
AI screens retina photos for diabetic retinopathy, a big help where specialists are rare.
In 2020 MIT researchers used deep learning to discover halicin, a new antibiotic against resistant bacteria.
Smartwatches detect irregular heartbeats (atrial fibrillation) and alert the user to see a doctor.
AI searches millions of virtual materials for better batteries, solar cells and catalysts before anyone mixes a chemical.
Google DeepMind's GraphCast (2023) produces 10-day forecasts in under a minute, with accuracy that rivals traditional supercomputer models.
In 2019 algorithms combined data from 8 telescopes across the planet into one Earth-sized virtual telescope: about 5 petabytes of data.
Biology + computer science: read genomes, find disease genes, track viruses. During COVID-19, scientists shared and analysed virus genomes worldwide within days.
Treatments chosen for your genes. Cancer therapies are already matched to the tumour's DNA.
Science students: Python + statistics are now as important as the lab coat.
Next: money, markets and the apps that know what you want.
"Data is the new oil" — but only if you know how to refine it.
Every card payment is scored by AI in milliseconds: normal for you, or suspicious?
Pay bills and transfer money from your phone. In Algeria: BaridiMob, CIB and Edahabia cards.
Algorithms decide who gets a loan, which raises big questions about fairness.
Most trades on big stock markets are placed by computer programs.
The system compares you with 8 imaginary users and recommends what similar people liked: "collaborative filtering", the idea behind Netflix, YouTube, Amazon and TikTok.
Ads targeted to the right people, A/B tests, AI-generated visuals and slogans.
CRM tools predict which customer will buy next and when to call them.
Forecast demand, optimise delivery routes, keep stock low but never empty.
Chatbots answer simple questions 24/7; humans handle the hard ones.
Excel → SQL → Python. What sold, where, when, and why?
Next month's sales, which customers will leave, the best price.
Dashboards (Power BI, Tableau) that a CEO understands in 10 seconds.
Algerian start-ups like Yassir (ride-hailing & delivery super-app) are built on exactly this: data, algorithms and apps.
The most human questions — language, history, law, mind, art — now have powerful new tools.
The Herculaneum scrolls were carbonised by the eruption of Vesuvius in 79 AD: too fragile to open. Scientists scanned them with X-rays, and in 2023 a student used AI to read the first word inside a closed scroll: "purple" (πορφύρας).
By 2024, whole passages of an ancient philosophy text had been read.
LiDAR (laser scans from planes) plus algorithms revealed tens of thousands of hidden Maya structures under the Guatemalan jungle.
Machine translation, speech recognition, and AI for low-resource languages like Darija and Tamazight. Linguists are needed!
AI searches thousands of laws and contracts in seconds; lawyers decide what's fair.
The Panama Papers (2016): 11.5 million leaked documents, investigated with data tools by journalists in 80 countries.
Analyse language to study emotions and mental health; design apps that are good for us, not addictive.
Games, films, music and design use AI tools, but taste, story and meaning come from people.
Bias, privacy, copyright, deepfakes, jobs. Governments (e.g. the EU AI Act) need people who understand both humans and tech.
What is intelligence? Consciousness? Responsibility? These are now practical engineering questions.
Python + MATLAB, Arduino projects, CAD & simulation. Careers: robotics, aerospace, energy, automotive.
Python + statistics, bioinformatics. Careers: medical AI, drug discovery, data scientist, health tech.
Excel → SQL → Power BI → Python. Careers: data analyst, fintech, digital marketing, founder.
AI literacy, prompting, text analysis, UX. Careers: AI ethics, legaltech, UX research, digital journalism.
Free to start: CS50 (Harvard, free online) · Google's free AI courses · Kaggle Learn · freeCodeCamp · Khan Academy
A summary of a hard lesson. A spreadsheet that does your budget. A chart of your sport stats. A translation tool for your grandmother. Small is perfect.
"AI won't replace you. A person who uses AI well might." Be that person.
Hossem Eddine Kentache · Computer Science, NCUK Algeria
hossemeddinekentache@ncukalgeria.com