4 answers
Ryan
Student
Shawano, Wisconsin
1
Question
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I am a high schooler looking to enter a path into AI. What is the best first step to take as I am only a junior in high school?
I have background knowledge in python. I am junior in high school. I am looking to progress my knowledge. I am learning on coursera and have coursera plus so I can get any course there.
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4 answers
BEYZA KOMİŞ
I am a student currently enrolled in a accredited program
2
Answers
Sakarya, Turkey
Updated
BEYZA’s Answer
As a second year Software Engineer I would like to provide you an answer from a student point of view which you can relate to.With the face paced tech industry there can be a lot to catch up.If you want to dive in the Ai path , I suggest you take baby steps to grasp the concepts that fall under the Ai category.Because as a student there is just so much information dumped on to you.You have to complete tasks and projects without even knowing what tools you're using or why.I strongly believe that if you want to start strong you first have to understand and master the fundamentals of your desired field.Then after you've grasped the concepts, you won't find yourself lost in between assignments like I have.Good luck I wish you the best!!
I really appreciate the response, it is great to hear something from an enrolled student.
Ryan
Ashutosh Raina
Software Developer
7
Answers
Campbell, California
Updated
Ashutosh’s Answer
The key to succeeding in school is to focus on the basics while also thinking about what will help you get a job. For long-term success, having a strong understanding of Math, Calculus, and core Computer Science concepts like data structures and algorithms is crucial. These skills take time to master, so practice and repetition are important. As you advance through your education, you'll start to see how everything builds on the foundations you learn in high school and college.
When it comes to courses, they can teach you how to do things now, but it's important to understand the difference between details and fundamentals. Online courses, like those from Coursera or MIT on Deep Learning, are valuable resources. However, I suggest starting with math courses and then moving on to statistics to build a solid foundation. Keep going, and you'll see your hard work pay off!
When it comes to courses, they can teach you how to do things now, but it's important to understand the difference between details and fundamentals. Online courses, like those from Coursera or MIT on Deep Learning, are valuable resources. However, I suggest starting with math courses and then moving on to statistics to build a solid foundation. Keep going, and you'll see your hard work pay off!
Sneha Deb
Tech Consultant
52
Answers
Edison, New Jersey
Updated
Sneha’s Answer
Hi Ryan! That’s awesome! Since you already know Python, the best next step is to build a strong foundation in math (especially linear algebra, calculus, and probability) since AI relies heavily on it. On Coursera Plus, I’d recommend courses like Andrew Ng’s "Machine Learning" or DeepLearning.AI’s "AI for Everyone" to get hands-on experience. Try working on small AI projects (e.g., image recognition, chatbots) and exploring frameworks like TensorFlow or PyTorch. Good luck!
Thank you! I appreciate your response and am excited to take action.
Ryan
William Phelps
Computer solutions consulting
16
Answers
Danville, Virginia
Updated
William’s Answer
In 1985, everybody wanted to learn COBOL/RPG. In the 1990's it was Java and C. In the 2000's it was HTML/CSS/JavaScript. The common thread was that each of the was "THE thing to know". How has that worked out in general?
What I'm trying to say is that while "learning the flavor of the day" is exciting... learning the basics to endure is boring, but ultimately pays better in the long term.
Once you have the building blocks, the actual technology stacks become less important. (Personally, I think the AI craze in general has a short runway and will flame out in general as more of the most interesting tidbits get acquired -- as usual --by a handful of companies ... so I'm really more curious about what's next.)
Unless you have that one killer idea that no one else has considered, I'd focus on the core parts, and be flexible - let your interests take you in a direction rather than forcing yourself into an area you might not even like.
What I'm trying to say is that while "learning the flavor of the day" is exciting... learning the basics to endure is boring, but ultimately pays better in the long term.
Once you have the building blocks, the actual technology stacks become less important. (Personally, I think the AI craze in general has a short runway and will flame out in general as more of the most interesting tidbits get acquired -- as usual --by a handful of companies ... so I'm really more curious about what's next.)
Unless you have that one killer idea that no one else has considered, I'd focus on the core parts, and be flexible - let your interests take you in a direction rather than forcing yourself into an area you might not even like.
Thanks for the advice.
Ryan