Hey, awesome readers! Today, we’re talking about something super cool—Artificial Intelligence (A.I)

What Is Artificial Intelligence?

Artificial Intelligence (AI) is like an intelligent robot that learns stuff and solves problems. You know how you learn to tie your shoelaces or ride a bike? You learn from reading books or playing games, AI learns from data—lots and lots of data!

Ex: Imagine you have a magical friend who learns to do things just like you do. This magical friend can learn from looking at your picture books (data) and can solve problems for you—like finding your lost toy! That magical friend is called Artificial Intelligence, or AI.

Relationship between A.I & Other Studies

How Does AI Work?

1. Learning from Numbers 🧮 – Humans Analyze Data – (Numerical Data)

AI can look at many numbers and find patterns, kinda like solving a giant puzzle. This is done through something called Machine Learning and Deep Learning.

Ex: Just like you learn to count numbers, AI can learn from numbers too!

2. Learning from Words and Sounds 🎵 – Humans Can Listen & Speak – (Text/Audio Data)

AI can also read and listen, just like us! Imagine if your computer could understand when you’re asking for a cookie! 🍪 This magic is done by Machine Learning/DL and Natural Language Processing.

Ex: Imagine if your magical friend could talk and understand you just like your best friend! AI can do that!

3. Learning to See 📸 – Humans Can See & Recognize – (Image/Video Data)

What if I told you AI could recognize your pet hamster or your favorite toy? 🐹 AI can “see” pictures and videos and understand them, thanks to Computer Vision and deep Learning.

Ex: What if your magical friend could recognize your family from your photo album? AI can do that too!

Steps for Machines to Learn

1. Gathering Data: Collecting all kinds of information to learn from.
2. Data Preparation: Making the data ready for learning.
3. Choosing a Model: Picking the best way to learn.
4. Training: Time for AI to hit the books (or data)!
5. Evaluation: Checking to see how well AI learned.
6. Parameter Tuning: Making small changes to learn even better.
7. Prediction: Making guesses about new stuff.

Jobs You Can Get in AI 🚀

For Data Fans

• Sales Analyst
• Operations Analyst
• Customer Success Analyst … and more!

For Machine Learning Gurus

• Machine Learning Engineer
• Data Architect
• Data Scientist … and more!

For Data Science Wizards

• Analytics Manager
• Business Analyst
• Statistician … and lots more!

A Road Map to Become a Data Scientist 🎓

1. Learn Excel: It’s like the ABC of data!
2. Understand Statistics: Counting stuff, but way cooler!
3. Learn Programming: Coding in languages like Python.
4. Data Visualization: Making pretty graphs.
5. Use Numpy & Pandas: Tools for data magic.
6. Learn BI Tools: Software like Tableau and Power BI.
7. Get to Know Databases: Where all the data lives.
8. Dive into Machine Learning: Where the real magic happens.
9. Deep Learning: Even deeper magic!

Skills Needed in the Industry 🛠️

1. Data Preparation: Sorting and cleaning data.
2. Number Crunching: Doing really fast math.
3. Story Telling: Turning numbers into stories.
4. Asking Questions: Knowing what to ask.
5. Tech Skills: Being a wizard with tech tools.