Vibe Coding vs Traditional Coding Should Kids Still Learn to Code #podcast

Abhishek Thakur · Beginner ·💻 AI-Assisted Coding ·8mo ago

Key Takeaways

Abhishek Thakur discusses the benefits of vibe coding over traditional coding for kids, sharing his personal experience of struggling to learn coding through traditional methods and how vibe coding can make learning more engaging and accessible.

Full Transcript

Yeah, I'm making sure that students learn learn vibe coding. I think my and and this is sort of biased by my own personal experience. Like I think I and I've told this story before in other places, but like I you know, I was inspired to try to create software. I sort of took the initial step of trying to make that happen, watched a bunch of YouTube videos, and this was like pre any amount of education that I had actually done in the area. Um and like failed, you know, wonderfully and was never able to make anything actually work. Like I spent many many uh you know, I was trying to build an iOS app. I would go to the library in my city because I didn't have a Mac. Um and sort of spend time watching videos and trying to do stuff, and you couldn't save files on those computers. So I had to sort of come up with some crazy way to try to save my work so that I could keep coming back to it. Um and all that stuff like never built anything that actually worked. Uh and like the code never even ran, but I was sort of like inspired and thankfully was persistent enough to like continue. Um and then ultimately studied computer science and started learning C++ and was miserable because C++ is not that fun to program in and what they have you learn in some of these intro CS classes um is just like not that exciting. And like all of that's to say I think the current way that people learn software and programming, especially kids and everything else like that, is you sort of have to um you know, you have to expend disbelief that you can actually build something interesting. Uh like kid like I think a lot of kids are like, "I want to make video games." Like that's what got me excited. Initially, it's what my little brother who studied computer science, same thing. Like he was like, "I want to make video games." Um and you're so off when you start learning to code from being able to build video games. And I feel like vibe coding is this way to like make it more visceral that like you're actually close and you're able to build this stuff. Um and like get more and more people excited about what's possible building software. Um so I I still think folks should learn how to code.

Original Description

Full video: https://youtube.com/live/5YBSypM1-u0 Please subscribe and like the video to help me keep motivated to make awesome videos like this one. :) Follow me on: Twitter: https://twitter.com/abhi1thakur LinkedIn: https://www.linkedin.com/in/abhi1thakur/ Kaggle: https://kaggle.com/abhishek
Watch on YouTube ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Playlist

Uploads from Abhishek Thakur · Abhishek Thakur · 0 of 60

← Previous Next →
1 Episode 1.1: Intro and building a machine learning framework
Episode 1.1: Intro and building a machine learning framework
Abhishek Thakur
2 Episode 1.2: Building an inference for the machine learning framework
Episode 1.2: Building an inference for the machine learning framework
Abhishek Thakur
3 Episode 2: A Cross Validation Framework
Episode 2: A Cross Validation Framework
Abhishek Thakur
4 Tips N Tricks #2: Setting up development environment for machine learning
Tips N Tricks #2: Setting up development environment for machine learning
Abhishek Thakur
5 Episode 3: Handling Categorical Features in Machine Learning Problems
Episode 3: Handling Categorical Features in Machine Learning Problems
Abhishek Thakur
6 BERT on Steroids: Fine-tuning BERT for a dataset using PyTorch and Google Cloud TPUs
BERT on Steroids: Fine-tuning BERT for a dataset using PyTorch and Google Cloud TPUs
Abhishek Thakur
7 Special Announcement: Approaching (almost) any machine learning problem
Special Announcement: Approaching (almost) any machine learning problem
Abhishek Thakur
8 Training BERT Language Model From Scratch On TPUs
Training BERT Language Model From Scratch On TPUs
Abhishek Thakur
9 Bengali.AI: Handwritten Grapheme Classification Using PyTorch (Part-1)
Bengali.AI: Handwritten Grapheme Classification Using PyTorch (Part-1)
Abhishek Thakur
10 Bengali.AI: Handwritten Grapheme Classification Using PyTorch (Part-2)
Bengali.AI: Handwritten Grapheme Classification Using PyTorch (Part-2)
Abhishek Thakur
11 Episode 4: Simple and Basic Binary Classification Metrics
Episode 4: Simple and Basic Binary Classification Metrics
Abhishek Thakur
12 Training Sentiment Model Using BERT and Serving it with Flask API
Training Sentiment Model Using BERT and Serving it with Flask API
Abhishek Thakur
13 Episode 5: Entity Embeddings for Categorical Variables
Episode 5: Entity Embeddings for Categorical Variables
Abhishek Thakur
14 Tips N Tricks #5: 3 Simple and Easy Ways to Cache Functions in Python
Tips N Tricks #5: 3 Simple and Easy Ways to Cache Functions in Python
Abhishek Thakur
15 Multi-Lingual Toxic Comment Classification using BERT and TPUs with PyTorch
Multi-Lingual Toxic Comment Classification using BERT and TPUs with PyTorch
Abhishek Thakur
16 Text Extraction From a Corpus Using BERT (AKA Question Answering)
Text Extraction From a Corpus Using BERT (AKA Question Answering)
Abhishek Thakur
17 10K Subscribers: Approaching (almost) Any Machine Learning Problem and Talk Show
10K Subscribers: Approaching (almost) Any Machine Learning Problem and Talk Show
Abhishek Thakur
18 Data Processing For Question & Answering Systems: BERT vs. RoBERTa
Data Processing For Question & Answering Systems: BERT vs. RoBERTa
Abhishek Thakur
19 Tips N Tricks #6: How to train multiple deep neural networks on TPUs simultaneously
Tips N Tricks #6: How to train multiple deep neural networks on TPUs simultaneously
Abhishek Thakur
20 Sentencepiece Tokenizer With Offsets For T5, ALBERT, XLM-RoBERTa And Many More
Sentencepiece Tokenizer With Offsets For T5, ALBERT, XLM-RoBERTa And Many More
Abhishek Thakur
21 Talks # 1:Andrey Lukyanenko - Handwritten digit recognition w/ a twist &  topic modelling over time
Talks # 1:Andrey Lukyanenko - Handwritten digit recognition w/ a twist & topic modelling over time
Abhishek Thakur
22 Episode 6: Simple and Basic Evaluation Metrics For Regression
Episode 6: Simple and Basic Evaluation Metrics For Regression
Abhishek Thakur
23 Talks # 2: Subhaditya Mukherjee - Image restoration using Deep Learning: Dehazing
Talks # 2: Subhaditya Mukherjee - Image restoration using Deep Learning: Dehazing
Abhishek Thakur
24 Basic git commands everyone should know about
Basic git commands everyone should know about
Abhishek Thakur
25 How do I start my career in Data Science?
How do I start my career in Data Science?
Abhishek Thakur
26 Talks # 3: Lorenzo Ampil - Introduction to T5 for Sentiment Span Extraction
Talks # 3: Lorenzo Ampil - Introduction to T5 for Sentiment Span Extraction
Abhishek Thakur
27 Detecting Skin Cancer (Melanoma) With Deep Learning
Detecting Skin Cancer (Melanoma) With Deep Learning
Abhishek Thakur
28 Talks # 4: Sebastien Fischman - Pytorch-TabNet: Beating XGBoost on Tabular Data Using Deep Learning
Talks # 4: Sebastien Fischman - Pytorch-TabNet: Beating XGBoost on Tabular Data Using Deep Learning
Abhishek Thakur
29 Build a web-app to serve a deep learning model for skin cancer detection
Build a web-app to serve a deep learning model for skin cancer detection
Abhishek Thakur
30 Talks # 5: Parul Pandey: Data Science, Diversity and Kaggle
Talks # 5: Parul Pandey: Data Science, Diversity and Kaggle
Abhishek Thakur
31 Implementing original U-Net from scratch using PyTorch
Implementing original U-Net from scratch using PyTorch
Abhishek Thakur
32 Tips N Tricks # 8: Using automatic mixed precision training with PyTorch 1.6
Tips N Tricks # 8: Using automatic mixed precision training with PyTorch 1.6
Abhishek Thakur
33 Talks # 6: Mani Sarkar: From backend development to machine learning
Talks # 6: Mani Sarkar: From backend development to machine learning
Abhishek Thakur
34 Dockerizing the skin cancer detection web application
Dockerizing the skin cancer detection web application
Abhishek Thakur
35 How to train a deep learning model using docker?
How to train a deep learning model using docker?
Abhishek Thakur
36 Building an entity extraction model using BERT
Building an entity extraction model using BERT
Abhishek Thakur
37 Train custom object detection model with YOLO V5
Train custom object detection model with YOLO V5
Abhishek Thakur
38 Talks # 7: Moez Ali: Machine learning with PyCaret
Talks # 7: Moez Ali: Machine learning with PyCaret
Abhishek Thakur
39 How to convert almost any PyTorch model to ONNX and serve it using flask
How to convert almost any PyTorch model to ONNX and serve it using flask
Abhishek Thakur
40 Hyperparameter Optimization: This Tutorial Is All You Need
Hyperparameter Optimization: This Tutorial Is All You Need
Abhishek Thakur
41 I finally got a copy of "Approaching (Almost) Any Machine Learning Problem"
I finally got a copy of "Approaching (Almost) Any Machine Learning Problem"
Abhishek Thakur
42 Captcha recognition using PyTorch (Convolutional-RNN + CTC Loss)
Captcha recognition using PyTorch (Convolutional-RNN + CTC Loss)
Abhishek Thakur
43 Live Q&A: Getting Started With Data Science
Live Q&A: Getting Started With Data Science
Abhishek Thakur
44 WTFML: Simple, reusable code for PyTorch models
WTFML: Simple, reusable code for PyTorch models
Abhishek Thakur
45 Talks # 8: Sebastián Ramírez; Build a machine learning API  from scratch  with FastAPI
Talks # 8: Sebastián Ramírez; Build a machine learning API from scratch with FastAPI
Abhishek Thakur
46 Data Science PC Configs: From Low Range to Super-High Range
Data Science PC Configs: From Low Range to Super-High Range
Abhishek Thakur
47 BERT Model Architectures For Semantic Similarity
BERT Model Architectures For Semantic Similarity
Abhishek Thakur
48 I just got access to GitHub's Codespaces and it's amazing!
I just got access to GitHub's Codespaces and it's amazing!
Abhishek Thakur
49 Talks # 9: Vladimir Iglovikov; Detecting Masked Faces In The Pandemic World
Talks # 9: Vladimir Iglovikov; Detecting Masked Faces In The Pandemic World
Abhishek Thakur
50 Tips To Build A Good Data Science / Machine Learning Project (For Your Portfolio)
Tips To Build A Good Data Science / Machine Learning Project (For Your Portfolio)
Abhishek Thakur
51 Docker For Data Scientists
Docker For Data Scientists
Abhishek Thakur
52 How To Become A Data Scientist In 1 Year (Learn From A Real World Example)
How To Become A Data Scientist In 1 Year (Learn From A Real World Example)
Abhishek Thakur
53 Talks # 10: Tanishq Abraham; What are CycleGANs? (a novel deep learning tool in pathology)
Talks # 10: Tanishq Abraham; What are CycleGANs? (a novel deep learning tool in pathology)
Abhishek Thakur
54 Deploy Any Machine Learning Or Deep Learning Model On Google Cloud Platform (App Engine)
Deploy Any Machine Learning Or Deep Learning Model On Google Cloud Platform (App Engine)
Abhishek Thakur
55 Pair Programming: Deep Learning Model For Drug Classification With Andrey Lukyanenko
Pair Programming: Deep Learning Model For Drug Classification With Andrey Lukyanenko
Abhishek Thakur
56 VS Code (codeserver) on Google Colab / Kaggle / Anywhere
VS Code (codeserver) on Google Colab / Kaggle / Anywhere
Abhishek Thakur
57 Talks # 11: Jean-François Puget; Did you know GPUs are not just for Deep Learning?
Talks # 11: Jean-François Puget; Did you know GPUs are not just for Deep Learning?
Abhishek Thakur
58 End-to-End: Automated Hyperparameter Tuning For Deep Neural Networks
End-to-End: Automated Hyperparameter Tuning For Deep Neural Networks
Abhishek Thakur
59 Deploy Any Machine Learning (or Deep Learning) Endpoint on Google Cloud Platform In 10 minutes
Deploy Any Machine Learning (or Deep Learning) Endpoint on Google Cloud Platform In 10 minutes
Abhishek Thakur
60 Ensembling, Blending & Stacking
Ensembling, Blending & Stacking
Abhishek Thakur

Abhishek Thakur discusses the benefits of vibe coding for kids, sharing his personal experience and highlighting the importance of making coding education more engaging and accessible. He emphasizes the need for a more visceral learning experience that allows kids to build interesting projects from the start. By learning vibe coding, kids can develop problem-solving skills, build confidence, and create interactive projects with ease.

Key Takeaways
  1. Start with vibe coding to make learning more engaging
  2. Use online resources such as YouTube videos to get started
  3. Join online communities such as Kaggle to connect with other coders
  4. Experiment with different programming languages and tools
  5. Build projects that interest you, such as video games
💡 Vibe coding can make learning to code more accessible and engaging for kids by providing a more visceral experience that allows them to build interesting projects from the start.

Related Reads

📰
Why AI-Generated GIS Code Can Run Successfully and Still Be Wrong
Learn why AI-generated GIS code can run successfully but still produce incorrect results, and how to identify and mitigate these issues
Dev.to · Muhammed Enes Duran
📰
AI chip startup Etched defies skeptics, hits $10.3B valuation from big-name investors
Etched, an AI chip startup, achieves $10.3B valuation with its innovative chips and memory components that accelerate AI inference without GPUs
TechCrunch AI
📰
Agentic Engineering with GitHub Copilot: A Practical Guide
Learn to use GitHub Copilot as a code agent for agentic engineering, transforming your coding workflow with automated tools and commands
Dev.to AI
📰
Bug Smash: Fixing 5 Critical Bugs in My Django-Groq AI Chatbot
Learn to debug and fix critical bugs in a Django-Groq AI chatbot, improving its performance and reliability
Dev.to · Hafsa Noor Muhammad
Up next
FREE WooCommerce Product Custom Fields Plugin Using Claude AI
Quick Tips - Web Desiign & Ai Tools
Watch →