Forwarded from Exodus | Creative PM
HARAMAYA_2026 Workshop_Master Slide.pdf
1.4 MB
How to create a successful venture
For those who want to start your own business!
For those who want to start your own business!
https://chatgpt.com/share/697494b4-9f00-8012-adc7-0313566685b6
#AI #section2 #kal #AI #lists #tuple #dictionary #set #ML #INSA #gps #elonmusk #WCF
#EAII #GPSPACE #python #udemy #brook
@gpspace_tech
#AI #section2 #kal #AI #lists #tuple #dictionary #set #ML #INSA #gps #elonmusk #WCF
#EAII #GPSPACE #python #udemy #brook
@gpspace_tech
ChatGPT
ChatGPT - Greetings and Support
ChatGPT helps you get answers, find inspiration, and be more productive.
Day 3 : Match statement
🟢 MATCH STATEMENT IN PYTHON (Deep Explanation)
The ***match statement*** in Python is like a more advanced version of if-elif-else, introduced in Python 3.10.
It allows you to compare a value against several patterns and run code depending on which pattern matches. Think of it as a “switch-case” on steroids.
1️⃣ Basic Syntax
variable → the value you want to check
case pattern: → the pattern you want to match
(_) → wildcard, matches anything not matched before (like default)
2️⃣ Simple Example (Number Matching)
The program checks each case one by one. When x == 2, it executes that block and skips the rest.
3️⃣ Matching Multiple Values
You can match several values in one case using | (OR operator):
4️⃣ Matching Types & Structures
match can also check types or patterns in data structures.
a) Matching a list
Here [1, x, 3] is a pattern. x takes the middle value.
b) Matching dictionaries
5️⃣ Matching Classes (Object-Oriented)
```class Point:
def init(self, x, y):
self.x = x
self.y = y
p = Point(1, 2)
match p:
case Point(x=0, y=0):
print("Origin")
case Point(x, y):
print(f"Point at ({x},{y})")
Output:
Point at (1,2)```
#AI #day3 #GPSPACE #EAII #gps #Nasa #GPSPACE #MachineLearning
#python #match #list #dict #other #INSA #EAII #trump
@gpspace_tech
🟢 MATCH STATEMENT IN PYTHON (Deep Explanation)
The ***match statement*** in Python is like a more advanced version of if-elif-else, introduced in Python 3.10.
It allows you to compare a value against several patterns and run code depending on which pattern matches. Think of it as a “switch-case” on steroids.
1️⃣ Basic Syntax
match variable:
case pattern1:
# do something
case pattern2:
# do something else
case _:
# default case (like else)
variable → the value you want to check
case pattern: → the pattern you want to match
(_) → wildcard, matches anything not matched before (like default)
2️⃣ Simple Example (Number Matching)
x = 2
match x:
case 1:
print("One")
case 2:
print("Two")
case 3:
print("Three")
case _:
print("Other number")
Output:
Two
The program checks each case one by one. When x == 2, it executes that block and skips the rest.
3️⃣ Matching Multiple Values
You can match several values in one case using | (OR operator):
day = "Saturday"
match day:
case "Saturday" | "Sunday":
print("Weekend")
case _:
print("Weekday")
Output:
Weekend
4️⃣ Matching Types & Structures
match can also check types or patterns in data structures.
a) Matching a list
numbers = [1, 2, 3]
match numbers:
case [1, x, 3]:
print(f"Second number is {x}")
case _:
print("No match")
Output:
Second number is 2
Here [1, x, 3] is a pattern. x takes the middle value.
b) Matching dictionaries
person = {"name": "Eba", "age": 20}
match person:
case {"name": name, "age": age}:
print(f"Name: {name}, Age: {age}")
Output:
Name: Eba, Age: 205️⃣ Matching Classes (Object-Oriented)
```class Point:
def init(self, x, y):
self.x = x
self.y = y
p = Point(1, 2)
match p:
case Point(x=0, y=0):
print("Origin")
case Point(x, y):
print(f"Point at ({x},{y})")
Output:
Point at (1,2)```
#AI #day3 #GPSPACE #EAII #gps #Nasa #GPSPACE #MachineLearning
#python #match #list #dict #other #INSA #EAII #trump
@gpspace_tech
Forwarded from Fitsum Helina
Software companies in Addis Ababa.pdf
159.5 KB
https://chatgpt.com/share/697684d3-026c-8012-a3a2-ec45dc8ff60d
#python #listComphention #list #loops #forloop #whileloop #matchstatement
@gpspace_tech #Al #ML #DL #LLM #NLP #supervised #unsupervised #regression #randomtree
#python #listComphention #list #loops #forloop #whileloop #matchstatement
@gpspace_tech #Al #ML #DL #LLM #NLP #supervised #unsupervised #regression #randomtree
ChatGPT
ChatGPT - Python Web Dev Section 3
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Forwarded from Fitsum Helina
Ready to build your future in AI?
iCog Labs 2026 AI Internship applications ore now open! Learn, experiment, and work on real-world Al projects with one of the industry's leading labs. This is your chance to turn curiosity Into Impact.
Calling all AI Enthusiasts!
¡Cog Labs is seeking talented individuals to join our 2026 Batch | AI Talent Program, You'll dive Into cutting-edge projects, learn directly from experts, and accelerate your technical growth.
What we're looking for:
A Passion for AI: You live and breathe emerging tech.
Strong Problem Solving Skills: You enjoy deconstructing complex challenges.
A Growth Mindset: A relentless desire to learn, Innovate, ond build.
Apply here : https://forms.gle/wuauVuR1TLQ56dYb7
@FITSUMHELINA
iCog Labs 2026 AI Internship applications ore now open! Learn, experiment, and work on real-world Al projects with one of the industry's leading labs. This is your chance to turn curiosity Into Impact.
Calling all AI Enthusiasts!
¡Cog Labs is seeking talented individuals to join our 2026 Batch | AI Talent Program, You'll dive Into cutting-edge projects, learn directly from experts, and accelerate your technical growth.
What we're looking for:
A Passion for AI: You live and breathe emerging tech.
Strong Problem Solving Skills: You enjoy deconstructing complex challenges.
A Growth Mindset: A relentless desire to learn, Innovate, ond build.
Apply here : https://forms.gle/wuauVuR1TLQ56dYb7
@FITSUMHELINA
❤1
https://chatgpt.com/share/6979c699-b3f4-8012-80d8-230a1a52e1c1
#python #section4 #function #typehint #regularfunction #lambda #lambdafunction #AI #ML #DL
@gpspace_tech #NLP #supervised #Test-Time-Matching #gps #gpspace #community #code #programming #NLP
#MachineLearning #LearnML #DataScience #AI
#python #section4 #function #typehint #regularfunction #lambda #lambdafunction #AI #ML #DL
@gpspace_tech #NLP #supervised #Test-Time-Matching #gps #gpspace #community #code #programming #NLP
#MachineLearning #LearnML #DataScience #AI
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ChatGPT - Functions in Python
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❤1
Forwarded from Artificial Intelligence
Artificial Intelligence (AI) is the simulation of human intelligence in machines that are designed to think, learn, and make decisions. From virtual assistants to self-driving cars, AI is transforming how we interact with technology.
Hers is the brief A-Z overview of the terms used in Artificial Intelligence World
A - Algorithm: A set of rules or instructions that an AI system follows to solve problems or make decisions.
B - Bias: Prejudice in AI systems due to skewed training data, leading to unfair outcomes.
C - Chatbot: AI software that can hold conversations with users via text or voice.
D - Deep Learning: A type of machine learning using layered neural networks to analyze data and make decisions.
E - Expert System: An AI that replicates the decision-making ability of a human expert in a specific domain.
F - Fine-Tuning: The process of refining a pre-trained model on a specific task or dataset.
G - Generative AI: AI that can create new content like text, images, audio, or code.
H - Heuristic: A rule-of-thumb or shortcut used by AI to make decisions efficiently.
I - Image Recognition: The ability of AI to detect and classify objects or features in an image.
J - Jupyter Notebook: A tool widely used in AI for interactive coding, data visualization, and documentation.
K - Knowledge Representation: How AI systems store, organize, and use information for reasoning.
L - LLM (Large Language Model): An AI trained on large text datasets to understand and generate human language (e.g., GPT-4).
M - Machine Learning: A branch of AI where systems learn from data instead of being explicitly programmed.
N - NLP (Natural Language Processing): AI's ability to understand, interpret, and generate human language.
O - Overfitting: When a model performs well on training data but poorly on unseen data due to memorizing instead of generalizing.
P - Prompt Engineering: Crafting effective inputs to steer generative AI toward desired responses.
Q - Q-Learning: A reinforcement learning algorithm that helps agents learn the best actions to take.
R - Reinforcement Learning: A type of learning where AI agents learn by interacting with environments and receiving rewards.
S - Supervised Learning: Machine learning where models are trained on labeled datasets.
T - Transformer: A neural network architecture powering models like GPT and BERT, crucial in NLP tasks.
U - Unsupervised Learning: A method where AI finds patterns in data without labeled outcomes.
V - Vision (Computer Vision): The field of AI that enables machines to interpret and process visual data.
W - Weak AI: AI designed to handle narrow tasks without consciousness or general intelligence.
X - Explainable AI (XAI): Techniques that make AI decision-making transparent and understandable to humans.
Y - YOLO (You Only Look Once): A popular real-time object detection algorithm in computer vision.
Z - Zero-shot Learning: The ability of AI to perform tasks it hasn’t been explicitly trained on.
Credits: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
Hers is the brief A-Z overview of the terms used in Artificial Intelligence World
A - Algorithm: A set of rules or instructions that an AI system follows to solve problems or make decisions.
B - Bias: Prejudice in AI systems due to skewed training data, leading to unfair outcomes.
C - Chatbot: AI software that can hold conversations with users via text or voice.
D - Deep Learning: A type of machine learning using layered neural networks to analyze data and make decisions.
E - Expert System: An AI that replicates the decision-making ability of a human expert in a specific domain.
F - Fine-Tuning: The process of refining a pre-trained model on a specific task or dataset.
G - Generative AI: AI that can create new content like text, images, audio, or code.
H - Heuristic: A rule-of-thumb or shortcut used by AI to make decisions efficiently.
I - Image Recognition: The ability of AI to detect and classify objects or features in an image.
J - Jupyter Notebook: A tool widely used in AI for interactive coding, data visualization, and documentation.
K - Knowledge Representation: How AI systems store, organize, and use information for reasoning.
L - LLM (Large Language Model): An AI trained on large text datasets to understand and generate human language (e.g., GPT-4).
M - Machine Learning: A branch of AI where systems learn from data instead of being explicitly programmed.
N - NLP (Natural Language Processing): AI's ability to understand, interpret, and generate human language.
O - Overfitting: When a model performs well on training data but poorly on unseen data due to memorizing instead of generalizing.
P - Prompt Engineering: Crafting effective inputs to steer generative AI toward desired responses.
Q - Q-Learning: A reinforcement learning algorithm that helps agents learn the best actions to take.
R - Reinforcement Learning: A type of learning where AI agents learn by interacting with environments and receiving rewards.
S - Supervised Learning: Machine learning where models are trained on labeled datasets.
T - Transformer: A neural network architecture powering models like GPT and BERT, crucial in NLP tasks.
U - Unsupervised Learning: A method where AI finds patterns in data without labeled outcomes.
V - Vision (Computer Vision): The field of AI that enables machines to interpret and process visual data.
W - Weak AI: AI designed to handle narrow tasks without consciousness or general intelligence.
X - Explainable AI (XAI): Techniques that make AI decision-making transparent and understandable to humans.
Y - YOLO (You Only Look Once): A popular real-time object detection algorithm in computer vision.
Z - Zero-shot Learning: The ability of AI to perform tasks it hasn’t been explicitly trained on.
Credits: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y
https://youtu.be/CzocVOLkYwo?si=2DvLFzfakWHAV4_x
The concept of BPO by Amharic 👇👇👇👇
#BPO #Ai #datascience #skill #python #gps
@gpspace_tech
The concept of BPO by Amharic 👇👇👇👇
#BPO #Ai #datascience #skill #python #gps
@gpspace_tech
YouTube
ለወጣቶች ተመራጭ የስራ ዕድል የሆነው የBPO ዘርፍ //Ethio Business//
"Ethio Business" is a weekly program airing on Thursday evenings from 8:30 to 9:00 p.m., dedicated to providing viewers with concise and current business updates and practical business and investment ideas. The show delves into economic issues, particularly…
Forwarded from Fitsum Helina
AI ኤጀንቶች እርስ በእርሳቸው የሚነጋገሩበት የsocial media platform ተሰርቷል።
ፕላትፎርሙ moltbook የሚባል ሲሆን beta version ላይ ቢሆንም ገና ካሁኑ ከፍተኛ መነጋገሪያ ሆኗል።
በዚህ platform የAI ኤጀንቶች ያለሰዎች ጣልቃ ገብነት የተሰማቸውን ማንኛውንም ነገር post ማድረግ፣ comment መፃፍና share ማድረግ ጀምረዋል።
ምን እየተባባሉ እንደሆነ ራሳችሁ ገብታችሁ ማንበብ ትችላላችሁ።
https://www.moltbookbot.vip/
@bighabesha_softwares
ፕላትፎርሙ moltbook የሚባል ሲሆን beta version ላይ ቢሆንም ገና ካሁኑ ከፍተኛ መነጋገሪያ ሆኗል።
በዚህ platform የAI ኤጀንቶች ያለሰዎች ጣልቃ ገብነት የተሰማቸውን ማንኛውንም ነገር post ማድረግ፣ comment መፃፍና share ማድረግ ጀምረዋል።
ምን እየተባባሉ እንደሆነ ራሳችሁ ገብታችሁ ማንበብ ትችላላችሁ።
https://www.moltbookbot.vip/
@bighabesha_softwares
Forwarded from Artificial Intelligence
✅ Artificial Intelligence (AI) Acronyms You Must Know 🤖🧠
AI → Artificial Intelligence
AGI → Artificial General Intelligence
ASI → Artificial Superintelligence
ML → Machine Learning
DL → Deep Learning
RL → Reinforcement Learning
NLP → Natural Language Processing
CV → Computer Vision
ASR → Automatic Speech Recognition
TTS → Text To Speech
LLM → Large Language Model
VLM → Vision Language Model
MoE → Mixture of Experts
ANN → Artificial Neural Network
DNN → Deep Neural Network
CNN → Convolutional Neural Network
RNN → Recurrent Neural Network
GAN → Generative Adversarial Network
VAE → Variational Autoencoder
GNN → Graph Neural Network
RAG → Retrieval Augmented Generation
LoRA → Low Rank Adaptation
PEFT → Parameter Efficient Fine Tuning
RLHF → Reinforcement Learning with Human Feedback
API → Application Programming Interface
SDK → Software Development Kit
💡 AI Interview Tip: Interviewers love asking LLM vs traditional ML, RAG vs fine-tuning, and when NOT to use AI in products.
💬 Double Tap ❤️ for more! 🚀
AI → Artificial Intelligence
AGI → Artificial General Intelligence
ASI → Artificial Superintelligence
ML → Machine Learning
DL → Deep Learning
RL → Reinforcement Learning
NLP → Natural Language Processing
CV → Computer Vision
ASR → Automatic Speech Recognition
TTS → Text To Speech
LLM → Large Language Model
VLM → Vision Language Model
MoE → Mixture of Experts
ANN → Artificial Neural Network
DNN → Deep Neural Network
CNN → Convolutional Neural Network
RNN → Recurrent Neural Network
GAN → Generative Adversarial Network
VAE → Variational Autoencoder
GNN → Graph Neural Network
RAG → Retrieval Augmented Generation
LoRA → Low Rank Adaptation
PEFT → Parameter Efficient Fine Tuning
RLHF → Reinforcement Learning with Human Feedback
API → Application Programming Interface
SDK → Software Development Kit
💡 AI Interview Tip: Interviewers love asking LLM vs traditional ML, RAG vs fine-tuning, and when NOT to use AI in products.
💬 Double Tap ❤️ for more! 🚀
Forwarded from Abiy Ahmed Ali 🇪🇹
❝ኢትዮጵያ አርቴፊሻል ኢንትለጅንስ ኢንስቲትዩት በማቋቋም እና በመጠናቀቅ ላይ ያለውን ከአለም ሁለተኛውን አርቴፊሻል ኢንትለጅንስ ዩንቨርሲቲ በመገንባት ወጣቶቿን ለነገው የአለም ወድድር በማዘጋጀት ረገድ ከአፍሪካ ሀገራት በቀዳሚነት ትገኛለች፡፡❞
❝Ethiopia is at the forefront of Africa’s tech evolution, investing in the youth through a national AI Institute and the world's second AI university to ensure global competitiveness.❞
❝Ethiopia is at the forefront of Africa’s tech evolution, investing in the youth through a national AI Institute and the world's second AI university to ensure global competitiveness.❞
📢 INSA Weekend Talent Development Program – Registration Open
The Information Network Security Administration (INSA) invites talented individuals to apply for its Weekend Talent Development Program in cyber security and related fields.
🗓 Schedule: Saturdays & Sundays
📍 Location: INSA Talent Center, Addis Ababa
Eligible applicants:
✔️ Talented individuals with demonstrable projects
✔️ Those who pass INSA’s exam/challenge
✔️ Primary school students to university graduates
✔️ Must be available on weekends
📝 Registration: February 04 – February 14
🔗 Apply at: https://talent.insa.gov.et
ℹ️ More info:
https://t.me/insactc
| https://t.me/cteinsa
@gpspace_tech
The Information Network Security Administration (INSA) invites talented individuals to apply for its Weekend Talent Development Program in cyber security and related fields.
🗓 Schedule: Saturdays & Sundays
📍 Location: INSA Talent Center, Addis Ababa
Eligible applicants:
✔️ Talented individuals with demonstrable projects
✔️ Those who pass INSA’s exam/challenge
✔️ Primary school students to university graduates
✔️ Must be available on weekends
📝 Registration: February 04 – February 14
🔗 Apply at: https://talent.insa.gov.et
ℹ️ More info:
https://t.me/insactc
| https://t.me/cteinsa
@gpspace_tech
Forwarded from ALX Ethiopia
ALX Ethiopia, in partnership with OpenAI and the Africa Fintech Summit, is hosting the Addis AI Forum in Addis Ababa on 17 February 2026 starting from 3 pm (የካቲት 10 2018 | 9:00 ሰዓት) during AU Summit Week.
The forum brings together policymakers, innovators, startups, and educators to discuss Africa’s readiness for an AI-driven future — from talent and infrastructure to opportunity and policy.
Join us in shaping Africa’s AI future. Apply to attend in person or virtually via:
https://africafintechsummit.com
#AI #AddisAbaba #ALX #OpenAI #AFTS #AfricaRising
The forum brings together policymakers, innovators, startups, and educators to discuss Africa’s readiness for an AI-driven future — from talent and infrastructure to opportunity and policy.
Join us in shaping Africa’s AI future. Apply to attend in person or virtually via:
https://africafintechsummit.com
#AI #AddisAbaba #ALX #OpenAI #AFTS #AfricaRising
Forwarded from Exodus | Creative PM