Head to brilliant.org/TinaHuang/ to get started for free with Brilliant's interactive lessons. The first 200 people will also get 20% off an annual membership.
July 2024: Got the 20% off. Went from this video directly there and spent my first two hours on Brilliant. Great product. This is where my research on "How should I start learning python" videos ended. Thanks, Tina! - new TH fan in L.A.
Self Study AI Checklist: Beginner 1. Learn Python --- APIs (v. imp) 2. Learn LLMs 3. Learn Prompt Engineering --- Make a Project (Chatbot, Image Generator, etc) Intermediate 4. Learn Python libraries: -- Numpy -- Pandas -- Matplotlib -- Scikit-learn 5. Learn Maths: -- Calculus -- Linear Algebra -- Probability 6. Learn Statistics: -- Inferential Stats -- Descriptive Stats -- Hypothesis Testing -- Central Limit Theorem -- Distributions -- Confidence Intervals As a CSE grad, most and maybe all of these were taught but my brain was not braining. Lets see how long can I go this time. I dont know if this will be of help tbh, but good video Tina ☺
🎯 Key Takeaways for quick navigation: 00:00 🧑🎓 *Introduction to Learning AI* - The video introduces the challenge of learning AI and sets the stage for a new learning method. 00:57 🎯 *The Renon Method* - The Renon Method is introduced as a way to learn AI incrementally by starting with the basics and progressively building knowledge. - It involves creating small AI projects to maintain motivation and enthusiasm. 02:07 🤖 *Understanding Machine Learning* - An explanation of machine learning is provided, focusing on pattern recognition in data. - The example of a hot dog or not-hot-dog model is used to illustrate machine learning. 03:48 🍕 *How AI Models Learn* - Details on how AI models, such as the hot dog or not-hot-dog model and ChatGPT, learn from data. - The concept of probabilities and predictions is explained. 05:13 📚 *Learning Python and APIs* - Recommendations for learning Python basics and using APIs to interact with AI models. - Resource suggestions for Python learning are provided. 07:07 🔢 *Learning Math and Statistics* - Guidance on essential math and statistics topics for AI, including calculus, linear algebra, and probability. - Resource recommendations for learning these subjects are given. 09:00 🧠 *Deep Learning and Specializations* - Introduction to deep learning, neural networks, and specialization areas like computer vision and natural language processing. - Resource suggestions for deep learning are shared. 11:25 🛠️ *Building AI Projects* - Advice on starting to build AI projects, contributing to open-source AI models, and fine-tuning existing models. - Emphasis on practical application and not getting overwhelmed with too many resources. Made with HARPA AI
“Prime numbers are what is left when you have taken all the patterns away. I think prime numbers are like life. They are very logical but you could never work out the rules, even if you spent all your time thinking about them.” ― Mark Haddon, The Curious Incident of the Dog in the Night-Time
Some clarying points and addiontal tips, espeically for job seekers: 1. You only need basic math, you do not need to know a single thing about calc, linear alebgra, etc. if you are not going into research. Of course, the more you know about this the better, but if you just want to make AI products you don't need it. Research is a completley diffrent ball game where you will need at LEAST a master's to so much as get your foot in the door. It also doesn't pay as much as applied jobs (like Machine Learning Engier, Data Engineer, or even higher level Data Analysts). Optional: if you want to skip calc/differnation etc. that's fine but I strongly recomend learning linear algebra as it will make your life much easier. Again, you don't need it to get by but if you're looking for work in this espially it will make your life much easier. 2. The type of statistics you need are APPLIED Statstics (this includes all the types she is talking about, this is more about the rigor you are learning it). If you are going into research you might learn these from a more rigours perspective where you would need to already understand concepts from Calclus and so forth. 3. If you're looking to get a job, a realvent masters defeinely helps but so do quality Certifcations. So Micrsoft, Amazon, Google should be your starting points. ONLy get them from the websites themselves, do not get them from Cousea, Udacity etc. It's okay to learn from these sites, just dont' put them on your resume (some places are okay with this) 4. Get good at programming, espeially in Python. The following is optional: I would also take courses (online for free is fine) in Discrete Math, Data Strucures (a proper course, not just learning what Python's are) and Some kind of Algohrims Course. These will help you problem solve as you need to figure out how to implmeent things. Again, you can get away with not learning this stuff, but it will make your life easier. P.S. This is all just my opinoin from being in the job market and working. I encourge you to do your own resarch.
Thanks for the great advice. I’m a CS student/new to programming, should I learn full stack development first and then learn AI? Or, in 2024+, should I jump straight to learning AI?
@@andrewjenson_original That's a good question. It depends where you ultimately want to be, and what courses you have avaible. If I were you I would focus first on making sure you can fit all the math, so taking up to calc 3, linear algebra, and differential equations. You don't NEED this, but i recommend it, as these are harder to teach yourself. Next, I if you have an AI/ML track at your school I'd go for that. But I would make sure that you're also getting Devops, CI/CD, software devlopment etc, as IMO these are harder to teach yourself and find good stuff you'd need. If you tell me the type of job you're looking to get, I can give you even more and better info, like what certifications to go for, if a masters will help you. Generally speaking anything AI/ML related a masters is going to help you a lot even in applied sense. It's not necessary skills wise but that's what the job market wants.
Hi i am starting college i will study AI CS i am not so smart at maths but i do love it so much I don’t know from where should i start ,should i start studying maths before starting off or should i take the summer off to have fun and then start studying with beginning of the semester,ALSO i really love studying but i take it the hard way and most of the time i suck because I can’t manage my time any tips ,what should i do in college ,how many hours ,how can i be very professional at what i do
@@HabibaWael-v3p Happy to help ya! First of Math is a skill, you get better at it by practicing and doing it more. I would suggest get good at least at basic math and Linear Algebra. For the rest I need a little more info. What type of work do you want to do? If you want to do research, you will need to get very good at math, and you'll at least want a masters, ideally a PhD, so if you want to go this route, I would take the time to get good at math, including statistics and probability. If you want to work in an applied field like software engineering, Then you mostly need to be good at more basic math and Linear Algebra helps. If you tell me what you were thinking of doing I can give you better advice!
@@ceejay1353 i just want to get good grades when i enter the cs AI but i am so afraid that I won’t be good at it and after i finish i want to be a soft ware engineer as they told me that computer science studies the software part
I've seen just a few videos of yours come across my feed. I have to say they were very helpful. I have a goal to learn AI using free resources and you give a great outline for people who want to learn. Thank you and keep the videos coming!
I think the problem is a lot of us with ADHD/Autism require a top down approach. Neurotypicals tend to be fine learning in a straight lines but I think a lot of us NDs would rather learn the big picture first but no one teaches it that way. Standard Education would teach you about a car by teaching you about, the invention of the wheel, the axle, carriages, internal combustion engines, assembly line, yada yada yada. That would be so lame to learn about cars. I would start with what a car is and is used for so we have the why. The rest just shows up because of natural curiosity. How does it move? It rolls on wheels. How do the wheels spin? Engine. What's an engine? A thing that blows up fuel and spins a pole. What happens if something gets stuck? We use Oil to keep it lubed. One method is straightforward and boring but makes sure you know the topic from the ground up. The other method is rapid, exciting, and intuitive but can leave gaps. I am a firm believer gaps are easier to fill, compared to the long task of perfect foundational knowledge.
It's a very useful video, first you feel frustrated and lost, but after viewing it, you clear understand AI and get ready for a real work. Thank you and happy next machine learning year, 2024.
I am in the beginning of a career change into tech and recently decided AI is where I want to go. I have been struggling for months on what I should learn and the best path to get the right information to build my skills. This was the first video I felt confident after watching on what path I need to take to get the skills I want to learn! Amazing video Tina!
That scene where Jian Yang (not Jimmy) built a binary classifier (hot dog vs. not hot dog) but everyone else was expecting a multi-class classifier was absolutely hilarious. Don't forget he ended up selling his app for millions!
To be honest tina I learned 3d art exactly the same way and 5 years later I am far better than my competitors. Since I started experimenting with AI I was totally fascinated but didn't knew where to start self teaching while immediately applying my knowledge since em a dopamine addict. Your tutorial is life saver
Great, great video with so many actionable resources. Lots of notes taken. I also really appreciate the disclaimer at the end on not treating this vid like a to-do list of all the things we've got to learn. Soothes my perfectionist demon.
This has got to be one of the best road maps I've watched yet... thank you for this, as an networking infrastructure guy, I'm ready to pivot before they come for my job...
@@amritnalam9994 any monkey can place equipment and run cable, but not every monkey can work the command line. A.I. will thus knock the number of tech’s required to manage a network since it could configure the routing and switching much faster and more around the clock by it self.
Wow thank you so much for the resources!! Currently finishing up a DS bootcamp and was worried about how I can re-learn the stuff I didn’t fully understand with only the bootcamp material, so this is seriously perfect
I just want to say thank you so much! This is the most valuable video I have ever watched on TH-cam. Especially including Coursera courses is very thoughtful of you
Yes, please make more of these videos please! I am so interested in this stuff. I actually wanna take up a career with some type of development in AI probably business but yeah learning the basics is where it’s at. Thank you for this video.
I'm definitely going to give it a shot. I'm 60, but what the heck. You're videos are the best, because you take viewers by the hand, and guide them step-by-step on what they have to do, to get from clueless to competent.
Yes, please continue posting AI learning content. This video is great, just what I have been looking: a structured program of key areas to for self study of AI. There is a lot of content available, is very difficult to find the order that one should start. Your video covers how to star with the right foot, thank you for this.
How interesting! Many musicians also start off by playing stuff they enjoy from original creators, and then start approaching music theory and diving deeper
This was very encouraging, as I used this same method for learning quantum computing as a regular software engineer with no physics or advanced math background but love the quantum world 🥰
Already a web dev but starting the Stanford Machine Learning Specialization on Monday. Been brushing up on Python for the last couple of weeks but it came back pretty fast. Let’s go!
AWESOME details and breakdown, THANK YOU, YES some of use have ADD but are great IT engineers. learning a vast new tech is an uphill with a weights on, thanks
Will you please share what you learnt, i guess you deep dived into deep learning, genAI, LLM, langchain, stuff, pls share your experience, i wanna get my hands into it, what to do? I have basic mern experience...
To be honest, man. I have checked out sooo many videos, completed the machine learning/deep learning specializing on coursera. I am bad at math but have a basic understanding of some concepts (i am on 2nd year of a CS degree). But the thing that i really think there is missing - including on literally college courses, is putting things into practise. I think there are way, way way too much theory before you actually can get your hands dirty. I think it would be so nice to just have courses teach you how to implement these things instead of writing out endless equations. It exhausts me so much, because even though i learn some theoretical stuff then i don't even know what to remember or why. When i finally sit down to try and do something, i'm like "eh, what now?". If you just learn how to implement, say, a neural network to perform a task x amount of times so you could actually do it and see some results, then you can learn about the under the hood stuff as you go or after, so you can actually relate it to concrete situations.
that is not the purpose of a CS degree though. CS degree prepares students for the ability to do research and self-learn the applications. All those fancy models are built by equations, and you need to know that math to build the next generation of stable diffusion or large language models. If you don't understand the math, then there is not much that you can build for complex neural networks. Learning how to call APIs and apply pre-trained models can be learned on TH-cam and that is not worth the tuition.
@@richardhu3774 I think you missed the point. He has watched videos as well and having trouble finding material on practical application of the theories.
Excellent and even fast as she talks (totally necessary) the subject introductions and explanations "clear the fog" about Ai in a very effective and cohesive manner. On top of all this she offers a wealth of resources in order to GO DEEEEEPER!! Last note to anyone watching : make sure you are not distracted while watching.... FOCUS..... Many Thanks.
When you think about it all of us are LLMs. It's how we've learned to speak whatever language we speak and whatever other languages we speak. it's also how we do everything that we do by predicting what comes next based upon what we've learned in context. That's why there can be cultural similarities and differences. Because of the different models learned by different experiences. Culture and language are model sets in themselves.
Appreciate the very good video. As a long-time educator, learning by successive refinement is a well-known teaching technique. I use it to teach IT concepts, advanced AI/ML, and even guitar. Most universities' curriculums are structured this way with "course levels". Btw, LLMs do not use CNNs. They use transformers.
I'm now very interested. This is exactly the kind of video I was looking for. I will also be using your brilliant referral link to appreciate you for the great content!
Hi there, i have a even better strategy. I start always with one of the outer rings of that rinnegan ring and just read a little to see what my final goals look and feel like. Then i deal with the more inner rings and do the same. And then i deal with the outer ring (your initial one) and handle that but also another one, since the first rings are often the most boring. I did that with learning french. I started with Level C1 (C2 being the hardest) and moved downward….😅
i'm generally interested in a lot of things without being an expert in one thing. But you sold me on this. Also, your pathway is very interesting and never thought of it in that way. Your content is a gold.
your rinnegan method is basically a BFS applied to studying. I am still debating on whether i personally should follow a BFS or DFS study regime, as i normally like to get very deep into each topic but knowledge is infinite and time is limited, so there needs to be a balance
As a newcomer and a mother, I recently enrolled my child in Moonpreneur’s robotics classes, but I’m unsure if it was the right step. Many people say robotics and AI are the future of education, and I’d love to know if these classes truly offer a strong career foundation.
I appreciate the knowledge and the experience you are spreading Tina. I got confused and lost in this field, I don't know where to start there is a lot to learn and a lot to consider. It gets overwhelming sometimes. My real question is what is the real starting point? I'm spending a huge amount of time learning different things and at the end, I see myself knowing nothing and cannot relate all the things I learned together, I know Im missing something but I really cannot understand what it is.
@@jake9854 I like a challenge. If you have interest in something and want to learn, hard won't stop you. I think if the girls you are referring to think it is too hard and lose motivation and desire to study it, AI was never their cup of tea. I am sure they will enjoy another subject.
I have 20 yrs .Net, but right now its Python and Machine learning if want to make that finish line. Your advice is pretty much everything I came up with. You might need a STEM Bachelors , but knowlege of Python and tool seems to matter more. Im taking these classes at our Community college cause I dont have time or money for an Advanced degree. The market I work in requires a Comptia Security+ Certificate or similar. What similar type of Commerial ertificagjon exists for python,machine learning and data analysis?
Love your video first time watcher here, yet I have to say babies are super engaged and smart you just have to nurture them ❤ (my son was hours old and he was smiling and kept taking off his mittens which are placed on babies when they are first born to protect their tiny hands and to keep them from scratching their cute little face, he had plenty going on in his mind, he’s 2 now and is learning 3 languages) idk what were in those Covid vaccines but these post Covid babies are wild 😂❤
Hello Tina Huang. But that's not new. Before I can solve mathematical equations, I first have to know. What are the basic arithmetic operations, fractions or powers? Things are no different when it comes to AI. What you call the method is not important. Or?
Great video! It's one thing to learn ML on your own, but can someone really land a job after being self-taught? In your case is was part of your Masters education (kudos to accomplishing that with a short attention span 😜). I say for anyone who's wants to learn ML for reasons beyond just landing a job, it can be exrtremely rewarding if you have an endgame in mind (eg building your own product).
Thank you Tina! I see huuge potential in AI. So much that I feel like I should not miss this boat if I want to secure my future income! However I think this type of work would not bring me much joy. Would you still advise me to follow this path? What is your vision to the future of AI and careers? Will AI take over all high-paying jobs?
Thank you for your breakdown. I keep being asked how and what AI is all the time. It helps to hear how others explain a complex and wide topic like this. I work in the weeds in code and have a hard time explaining things in Human. I saw the vectorizing of parameters like words in an LLM and was fascinated by this idea... Someone asked how can a vector describe if something is close... So I broke it down to a small set of coordinates (the simplest vector of 1) by using latitude on a world map. Shorter distances can be evaluated with simple math, and then add another parameter (Longitude) and now the 2 parameter model of Lat/Lon is born :D... Does that resonate with your definition? My non-math/non-gis friends occasionally have a hard time with that idea still... My AI battle cry is "BreadDogPig!"
Head to brilliant.org/TinaHuang/ to get started for free with Brilliant's interactive lessons. The first 200 people will also get 20% off an annual membership.
chili sauce
what keyboard are you daily driving tho
nice job ,well done we need more of you's ,Tina is sisters name
Meanwhile people like these earing by simply selling courses
July 2024: Got the 20% off. Went from this video directly there and spent my first two hours on Brilliant. Great product. This is where my research on "How should I start learning python" videos ended. Thanks, Tina! - new TH fan in L.A.
Self Study AI Checklist:
Beginner
1. Learn Python
--- APIs (v. imp)
2. Learn LLMs
3. Learn Prompt Engineering
--- Make a Project (Chatbot, Image Generator, etc)
Intermediate
4. Learn Python libraries:
-- Numpy
-- Pandas
-- Matplotlib
-- Scikit-learn
5. Learn Maths:
-- Calculus
-- Linear Algebra
-- Probability
6. Learn Statistics:
-- Inferential Stats
-- Descriptive Stats
-- Hypothesis Testing
-- Central Limit Theorem
-- Distributions
-- Confidence Intervals
As a CSE grad, most and maybe all of these were taught but my brain was not braining. Lets see how long can I go this time.
I dont know if this will be of help tbh, but good video Tina ☺
Where I an learn llm's
@@visual_punch internet
Just 3 years real quick
Thank you
Thanks
🎯 Key Takeaways for quick navigation:
00:00 🧑🎓 *Introduction to Learning AI*
- The video introduces the challenge of learning AI and sets the stage for a new learning method.
00:57 🎯 *The Renon Method*
- The Renon Method is introduced as a way to learn AI incrementally by starting with the basics and progressively building knowledge.
- It involves creating small AI projects to maintain motivation and enthusiasm.
02:07 🤖 *Understanding Machine Learning*
- An explanation of machine learning is provided, focusing on pattern recognition in data.
- The example of a hot dog or not-hot-dog model is used to illustrate machine learning.
03:48 🍕 *How AI Models Learn*
- Details on how AI models, such as the hot dog or not-hot-dog model and ChatGPT, learn from data.
- The concept of probabilities and predictions is explained.
05:13 📚 *Learning Python and APIs*
- Recommendations for learning Python basics and using APIs to interact with AI models.
- Resource suggestions for Python learning are provided.
07:07 🔢 *Learning Math and Statistics*
- Guidance on essential math and statistics topics for AI, including calculus, linear algebra, and probability.
- Resource recommendations for learning these subjects are given.
09:00 🧠 *Deep Learning and Specializations*
- Introduction to deep learning, neural networks, and specialization areas like computer vision and natural language processing.
- Resource suggestions for deep learning are shared.
11:25 🛠️ *Building AI Projects*
- Advice on starting to build AI projects, contributing to open-source AI models, and fine-tuning existing models.
- Emphasis on practical application and not getting overwhelmed with too many resources.
Made with HARPA AI
is this your own ai work?
“Prime numbers are what is left when you have taken all the patterns away. I think prime numbers are like life. They are very logical but you could never work out the rules, even if you spent all your time thinking about them.”
― Mark Haddon, The Curious Incident of the Dog in the Night-Time
Even numbers are all patterns. Except for 2, because it is the only even prime.
What a great book. Sometimes I think about that kid to remember that even the most logical of mind couldn't even define time.
Some clarying points and addiontal tips, espeically for job seekers:
1. You only need basic math, you do not need to know a single thing about calc, linear alebgra, etc. if you are not going into research. Of course, the more you know about this the better, but if you just want to make AI products you don't need it. Research is a completley diffrent ball game where you will need at LEAST a master's to so much as get your foot in the door. It also doesn't pay as much as applied jobs (like Machine Learning Engier, Data Engineer, or even higher level Data Analysts). Optional: if you want to skip calc/differnation etc. that's fine but I strongly recomend learning linear algebra as it will make your life much easier. Again, you don't need it to get by but if you're looking for work in this espially it will make your life much easier.
2. The type of statistics you need are APPLIED Statstics (this includes all the types she is talking about, this is more about the rigor you are learning it). If you are going into research you might learn these from a more rigours perspective where you would need to already understand concepts from Calclus and so forth.
3. If you're looking to get a job, a realvent masters defeinely helps but so do quality Certifcations. So Micrsoft, Amazon, Google should be your starting points. ONLy get them from the websites themselves, do not get them from Cousea, Udacity etc. It's okay to learn from these sites, just dont' put them on your resume (some places are okay with this)
4. Get good at programming, espeially in Python. The following is optional: I would also take courses (online for free is fine) in Discrete Math, Data Strucures (a proper course, not just learning what Python's are) and Some kind of Algohrims Course. These will help you problem solve as you need to figure out how to implmeent things. Again, you can get away with not learning this stuff, but it will make your life easier.
P.S. This is all just my opinoin from being in the job market and working. I encourge you to do your own resarch.
Thanks for the great advice. I’m a CS student/new to programming, should I learn full stack development first and then learn AI? Or, in 2024+, should I jump straight to learning AI?
@@andrewjenson_original That's a good question. It depends where you ultimately want to be, and what courses you have avaible.
If I were you I would focus first on making sure you can fit all the math, so taking up to calc 3, linear algebra, and differential equations. You don't NEED this, but i recommend it, as these are harder to teach yourself.
Next, I if you have an AI/ML track at your school I'd go for that. But I would make sure that you're also getting Devops, CI/CD, software devlopment etc, as IMO these are harder to teach yourself and find good stuff you'd need.
If you tell me the type of job you're looking to get, I can give you even more and better info, like what certifications to go for, if a masters will help you. Generally speaking anything AI/ML related a masters is going to help you a lot even in applied sense. It's not necessary skills wise but that's what the job market wants.
Hi i am starting college i will study AI CS i am not so smart at maths but i do love it so much I don’t know from where should i start ,should i start studying maths before starting off or should i take the summer off to have fun and then start studying with beginning of the semester,ALSO i really love studying but i take it the hard way and most of the time i suck because I can’t manage my time any tips ,what should i do in college ,how many hours ,how can i be very professional at what i do
@@HabibaWael-v3p Happy to help ya! First of Math is a skill, you get better at it by practicing and doing it more. I would suggest get good at least at basic math and Linear Algebra.
For the rest I need a little more info. What type of work do you want to do? If you want to do research, you will need to get very good at math, and you'll at least want a masters, ideally a PhD, so if you want to go this route, I would take the time to get good at math, including statistics and probability.
If you want to work in an applied field like software engineering, Then you mostly need to be good at more basic math and Linear Algebra helps.
If you tell me what you were thinking of doing I can give you better advice!
@@ceejay1353 i just want to get good grades when i enter the cs AI but i am so afraid that I won’t be good at it and after i finish i want to be a soft ware engineer as they told me that computer science studies the software part
I've seen just a few videos of yours come across my feed. I have to say they were very helpful. I have a goal to learn AI using free resources and you give a great outline for people who want to learn. Thank you and keep the videos coming!
I think the problem is a lot of us with ADHD/Autism require a top down approach. Neurotypicals tend to be fine learning in a straight lines but I think a lot of us NDs would rather learn the big picture first but no one teaches it that way.
Standard Education would teach you about a car by teaching you about, the invention of the wheel, the axle, carriages, internal combustion engines, assembly line, yada yada yada.
That would be so lame to learn about cars.
I would start with what a car is and is used for so we have the why. The rest just shows up because of natural curiosity. How does it move? It rolls on wheels. How do the wheels spin? Engine. What's an engine? A thing that blows up fuel and spins a pole. What happens if something gets stuck? We use Oil to keep it lubed.
One method is straightforward and boring but makes sure you know the topic from the ground up. The other method is rapid, exciting, and intuitive but can leave gaps. I am a firm believer gaps are easier to fill, compared to the long task of perfect foundational knowledge.
Spot on!
argee
100%
everyone has adhd there is no typical
That's a car, here's the key, have fun.
Automate the boring stuff is an amazing book. Provides alot details while not having the reader become bored after few pages.
being able to study things that you find boring to read is a key skill for being a good student tbh
It's a very useful video, first you feel frustrated and lost, but after viewing it, you clear understand AI and get ready for a real work. Thank you and happy next machine learning year, 2024.
Hey, that's me...a distracted, short attention span learning. Thanks for this.
thats me too! oh look a squirrel!
Stop doing stuff that require short attention span .. like reels , yt short...
Trust me it works ..
that's us buddy you are not alone in this
Best video I have seen about AI so far. Your video gave me a light when I was lost in the sea of AI.
I am in the beginning of a career change into tech and recently decided AI is where I want to go. I have been struggling for months on what I should learn and the best path to get the right information to build my skills. This was the first video I felt confident after watching on what path I need to take to get the skills I want to learn! Amazing video Tina!
How is that journey going bro
That scene where Jian Yang (not Jimmy) built a binary classifier (hot dog vs. not hot dog) but everyone else was expecting a multi-class classifier was absolutely hilarious. Don't forget he ended up selling his app for millions!
To be honest tina I learned 3d art exactly the same way and 5 years later I am far better than my competitors. Since I started experimenting with AI I was totally fascinated but didn't knew where to start self teaching while immediately applying my knowledge since em a dopamine addict. Your tutorial is life saver
Great, great video with so many actionable resources. Lots of notes taken. I also really appreciate the disclaimer at the end on not treating this vid like a to-do list of all the things we've got to learn. Soothes my perfectionist demon.
Thanks!
This has got to be one of the best road maps I've watched yet... thank you for this, as an networking infrastructure guy, I'm ready to pivot before they come for my job...
How would networking infra roles be at risk due to ai?
@@amritnalam9994 any monkey can place equipment and run cable, but not every monkey can work the command line. A.I. will thus knock the number of tech’s required to manage a network since it could configure the routing and switching much faster and more around the clock by it self.
Agree, excellent AI career roadmap.
Wow thank you so much for the resources!! Currently finishing up a DS bootcamp and was worried about how I can re-learn the stuff I didn’t fully understand with only the bootcamp material, so this is seriously perfect
I just want to say thank you so much! This is the most valuable video I have ever watched on TH-cam. Especially including Coursera courses is very thoughtful of you
Are coursera courses free?
Lovely and insightful video !! Thanks for sharing out Tina☺
Yes, please make more of these videos please! I am so interested in this stuff. I actually wanna take up a career with some type of development in AI probably business but yeah learning the basics is where it’s at. Thank you for this video.
I'm definitely going to give it a shot. I'm 60, but what the heck. You're videos are the best, because you take viewers by the hand, and guide them step-by-step on what they have to do, to get from clueless to competent.
I was interested before but now thanks to you, I have a path. Thank you again.
Yes, please continue posting AI learning content. This video is great, just what I have been looking: a structured program of key areas to for self study of AI. There is a lot of content available, is very difficult to find the order that one should start. Your video covers how to star with the right foot, thank you for this.
You are brilliant and creative! Thank you so much for making this. Wishing you success in everything you do
How interesting! Many musicians also start off by playing stuff they enjoy from original creators, and then start approaching music theory and diving deeper
Hi thank you. I am 77 and find your advice about learning AI excellent.
wow 77 how far are you into your AI journey
Best video on ai so far on TH-cam...now you got me interested in self learning ai and you just earn a subscriber.🎉❤
Thank you! I'm pretty sure I'll spend some time coming back to this video.
Thanks for everything you do! and it would be great to have a refreshed version of this video!
This was very encouraging, as I used this same method for learning quantum computing as a regular software engineer with no physics or advanced math background but love the quantum world 🥰
Tina, you're a brilliant human being and DS. The best is yet to come. Happy 2024! Thanks!
Thanks for the concise explanation and direction for getting started learning AI, really appreciate it.
You're my favorite AI TH-camr. Your pedagogy is unmatched.
lol
@@GuiltyNoticerus when you die:
@@sladeTek lol you're mad lowlife.
@@sladeTek you're less than nothing.
@@GuiltyNoticer I know your baldass isn't talking about nothing 🤣
I am planning to take machine learning next semester in college and I hope this is a helpful video.
Thank you! My attention span is abysmal. Please keep the content coming. You are awesome!
Thanks!
thank you so much for supporting me 💜💜
Already a web dev but starting the Stanford Machine Learning Specialization on Monday. Been brushing up on Python for the last couple of weeks but it came back pretty fast. Let’s go!
AWESOME details and breakdown, THANK YOU, YES some of use have ADD but are great IT engineers. learning a vast new tech is an uphill with a weights on, thanks
Awesome! I have learned a good portion of the recent ai and don’t have a short attention span but still loved this video 👍😎
Will you please share what you learnt, i guess you deep dived into deep learning, genAI, LLM, langchain, stuff, pls share your experience, i wanna get my hands into it, what to do? I have basic mern experience...
To be honest, man. I have checked out sooo many videos, completed the machine learning/deep learning specializing on coursera. I am bad at math but have a basic understanding of some concepts (i am on 2nd year of a CS degree). But the thing that i really think there is missing - including on literally college courses, is putting things into practise. I think there are way, way way too much theory before you actually can get your hands dirty. I think it would be so nice to just have courses teach you how to implement these things instead of writing out endless equations. It exhausts me so much, because even though i learn some theoretical stuff then i don't even know what to remember or why. When i finally sit down to try and do something, i'm like "eh, what now?". If you just learn how to implement, say, a neural network to perform a task x amount of times so you could actually do it and see some results, then you can learn about the under the hood stuff as you go or after, so you can actually relate it to concrete situations.
that is not the purpose of a CS degree though. CS degree prepares students for the ability to do research and self-learn the applications. All those fancy models are built by equations, and you need to know that math to build the next generation of stable diffusion or large language models. If you don't understand the math, then there is not much that you can build for complex neural networks. Learning how to call APIs and apply pre-trained models can be learned on TH-cam and that is not worth the tuition.
@@richardhu3774 I think you missed the point. He has watched videos as well and having trouble finding material on practical application of the theories.
I've been looking for a video like that for so long! Thanks you Tina 👌🏻
you had me at Rinnigan :D I love taking concepts from my fav stories and applying them to IRL concepts
“We become aware of the void as we fill it.”
― Antonio Porchia
Super helpful roadmap for learning AI. Your teaching style is fun and amazing. Thanks! ❤
First time viewer. Thanks for making a great video, I'm subbed. Also you're naturally funny.
Yes definitely make more videos like this! Extremely helpful ❤️
I really loved your explanation and it's really amazing, thank you for doing this Tina Huang
I love it! That's exactly what I started doing - trying to make my first agent asap and move from there :D Thank you so much!
Great tips on how to self-study AI quickly! This video is a fantastic resource for anyone looking to dive into AI. #SelfStudy #AI #LearningAI
I like that you put difficult things much simple about learning AI .Hope you make more of them
How do you learn bro?
Excellent and even fast as she talks (totally necessary) the subject introductions and explanations "clear the fog" about Ai in a very effective and cohesive manner. On top of all this she offers a wealth of resources in order to GO DEEEEEPER!! Last note to anyone watching : make sure you are not distracted while watching.... FOCUS..... Many Thanks.
Thank you for giving us a starting point. Please do lot more videos on AI
Awesome. So helpful! Thanks Tina!
When you think about it all of us are LLMs. It's how we've learned to speak whatever language we speak and whatever other languages we speak. it's also how we do everything that we do by predicting what comes next based upon what we've learned in context. That's why there can be cultural similarities and differences. Because of the different models learned by different experiences. Culture and language are model sets in themselves.
Appreciate the very good video. As a long-time educator, learning by successive refinement is a well-known teaching technique. I use it to teach IT concepts, advanced AI/ML, and even guitar. Most universities' curriculums are structured this way with "course levels". Btw, LLMs do not use CNNs. They use transformers.
Hi Tina, thank you for sharing. Keep up! ☕🍹
Thank you!! :D
@@TinaHuang1 i will say on this video Happy New Year Tina .Love you!
Your videos are sweet. Thanks for this awesome content! It's very engaging and straight-forward.
Love this.
Would like to get into ML/AI for genomics. Thanks for sharing your thoughts on self study.
I'm now very interested. This is exactly the kind of video I was looking for. I will also be using your brilliant referral link to appreciate you for the great content!
Hi there, i have a even better strategy. I start always with one of the outer rings of that rinnegan ring and just read a little to see what my final goals look and feel like. Then i deal with the more inner rings and do the same. And then i deal with the outer ring (your initial one) and handle that but also another one, since the first rings are often the most boring. I did that with learning french. I started with Level C1 (C2 being the hardest) and moved downward….😅
i'm generally interested in a lot of things without being an expert in one thing. But you sold me on this. Also, your pathway is very interesting and never thought of it in that way. Your content is a gold.
Love your content thank for your sharing, Tina ❤
Definitely interested in more AI/ python videos 💯
New sub here. This content is perfect for what I was looking for. Thanks so much, Tina 🙂
your rinnegan method is basically a BFS applied to studying. I am still debating on whether i personally should follow a BFS or DFS study regime, as i normally like to get very deep into each topic but knowledge is infinite and time is limited, so there needs to be a balance
As a newcomer and a mother, I recently enrolled my child in Moonpreneur’s robotics classes, but I’m unsure if it was the right step. Many people say robotics and AI are the future of education, and I’d love to know if these classes truly offer a strong career foundation.
Definitely trying to learn AI thank you for your wonderful videos, please keep on making them ❤
I appreciate the knowledge and the experience you are spreading Tina.
I got confused and lost in this field, I don't know where to start there is a lot to learn and a lot to consider. It gets overwhelming sometimes.
My real question is what is the real starting point? I'm spending a huge amount of time learning different things and at the end, I see myself knowing nothing and cannot relate all the things I learned together, I know Im missing something but I really cannot understand what it is.
This method is really cool! Also the little baby model emoji! Love ittt! ❤❤❤
Your skin is so good! Can you share your skin care?? 🤩
Universal Primer GPT by Siqi Chen - 1) the math and physics LLM 2) the teacher for learning anything rapidly LLM
Thank you so much for this video! Yes, I would love to learn AI and I hope you can make more content related to AI and learning it. Thank you!
but girls think AI is very hard tho
@@jake9854 I like a challenge. If you have interest in something and want to learn, hard won't stop you. I think if the girls you are referring to think it is too hard and lose motivation and desire to study it, AI was never their cup of tea. I am sure they will enjoy another subject.
00:20 First Step is calculus.
I thought it was buying a laptop/pc that can run models locally
hmmm why locally?
I love your videos. This was extremely helpful. Thank you!
TYSM Tina, this was so well done!
“Everything you can imagine is real.”
― Pablo Picasso
Great introductory video in the world of AI with great delivery also.
You are correct, Im doing Security + Cloud+ A+ and then I will go into what you are saying, so im 1/5 of it. Im almost done!!
I have 20 yrs .Net, but right now its Python and Machine learning if want to make that finish line. Your advice is pretty much everything I came up with. You might need a STEM Bachelors , but knowlege of Python and tool seems to matter more. Im taking these classes at our Community college cause I dont have time or money for an Advanced degree.
The market I work in requires a Comptia Security+ Certificate or similar. What similar type of Commerial ertificagjon exists for python,machine learning and data analysis?
Love your video first time watcher here, yet I have to say babies are super engaged and smart you just have to nurture them ❤ (my son was hours old and he was smiling and kept taking off his mittens which are placed on babies when they are first born to protect their tiny hands and to keep them from scratching their cute little face, he had plenty going on in his mind, he’s 2 now and is learning 3 languages) idk what were in those Covid vaccines but these post Covid babies are wild 😂❤
Hello Tina Huang.
But that's not new. Before I can solve mathematical equations, I first have to know. What are the basic arithmetic operations, fractions or powers?
Things are no different when it comes to AI. What you call the method is not important. Or?
I tutor that in math all the time
i lost it with the rinnegan method 😂😂😂 god, i love how you mix anime stuff with more serious content. thanks for doing it
Great video! It's one thing to learn ML on your own, but can someone really land a job after being self-taught? In your case is was part of your Masters education (kudos to accomplishing that with a short attention span 😜). I say for anyone who's wants to learn ML for reasons beyond just landing a job, it can be exrtremely rewarding if you have an endgame in mind (eg building your own product).
omg I love you! thanks for this!!!!
You just described how I learn.. but I've always referred to it as the jump in head first method, lol. Thanks for putting a name to it!
Thank You! You're great and I love your video!!!😊
Thank you Tina! I see huuge potential in AI. So much that I feel like I should not miss this boat if I want to secure my future income! However I think this type of work would not bring me much joy. Would you still advise me to follow this path? What is your vision to the future of AI and careers? Will AI take over all high-paying jobs?
You're great! Much appreciated 🙏
Thank you for your breakdown. I keep being asked how and what AI is all the time. It helps to hear how others explain a complex and wide topic like this. I work in the weeds in code and have a hard time explaining things in Human.
I saw the vectorizing of parameters like words in an LLM and was fascinated by this idea... Someone asked how can a vector describe if something is close... So I broke it down to a small set of coordinates (the simplest vector of 1) by using latitude on a world map. Shorter distances can be evaluated with simple math, and then add another parameter (Longitude) and now the 2 parameter model of Lat/Lon is born :D... Does that resonate with your definition? My non-math/non-gis friends occasionally have a hard time with that idea still...
My AI battle cry is "BreadDogPig!"
I see why you have 624K subscribers. You are really great.
Great content Tina thank you for all your hard work and involvement to provide us such a clear vision of AI & DS 🎉🎉
Thank you, great video 🎉
0:16 where did you all these animated icons?
Thank you, this is such a fantastic video, full of great resources and really well presented 😊
WoW the road map i create and do it myself is just like you. Except that i comment out some math that learn in U. Great tips!
7:47 Maths is boring?
THANK YOUU👌 you literally carry me 😊
Great content! Please do more in-depth on your learning path 🎉
hey! at 6:27 you said you'll put api links, but they're not in the description.
they are :) it's a little lower in the descriptions
I'm extremely sorry but where is the api to dalle-3 and text to video api you said? i only see the courses and project in the description@@TinaHuang1