Data Science Careers with Dhaval Patel - Codebasics Youtube

Dhaval Patel is a software & data engineer with more than 17 years of experience. He has been working as a data engineer for a Fintech giant Bloomberg LP (New York) as well as NVidia in the past. He teaches programming, machine learning, data science through YouTube channel CodeBasics which has 428K subscribers worldwide. 

00:00 Intro

01:34 Autoimmune disease ‘Ulcerative colitis’, Life & Death Struggle, Back to Life

03:40 Mental Health, Steroids & Immune System 

11:00 Planning Videos, Pedagogy & Smart People Problem

17:15 Working at Bloomberg, Bloomberg Trading Terminal & Exceptional Talent in Bloomberg

21:13  Career Tracks on Data Related Spectrum, Pathways for different Careers

25:16  Data Structure and Algorithms, Politics vs Equations, Eternity 

28:20  ML vs Deterministic Programming, Time & Space complexity of the ML Models

30:37 Kaggle vs Real Life, Soft Skills for Engineers, Transition from Competitions to Industrial Use-cases 

30:02 Litmus Test for Hiring Data Scientists, Continuous Engagement & Adaptability

42:35 Loss of Productivity by Lack of Communication Skills, Education System Deficiencies, How to Win Friends by Dale Carnegie 

46:50 Death by PowerPoint, Simplicity & Walk vs Talk

49:51 Negotiating Salary,  Action vs Motivation, Cellphone is a Distraction 

57:35 Growing Vegetables, Joy of Gardening, Rural Childhood & GMO Food  

01:01:40 Dhando Investor, Motel Business Monopoly by Patels, Software Engineering

01:04:04 Deep learning, C++ Back-propagation Algorithms,  Nvidia Titan RTX GPUs, Amazon Stores Experience

01:08:49 Nvidia Broadcast Noise Cancellation Demonstration, Nvidia Card Filtering, CNNs and Edge Detection 

01:16:06 BlackBox Models, ML-centric vs Data-Centric Models,  

01:19:25 Natural Language Understanding, Yann Lecaun, Low Accuracy is NLP Models

01:21:18 Github AI Pairing, Data Structures & Future of Programming Languages

01:27:01 ETL pipelines & Distributed Computing Structures 

01:30:00 FAST API, Beginner’s Tools, Pytorch vs TensorFlow, Improvements in Tensorflow 2.0

01:35:05 Programmers vs Normal People, Semantics of English vs Programming Languages, pd.read_csv 

01:38:03 Nvidia GPU vs Apple M1 GPU, Hope for non-Nvidia Deep-learning, Google Colab

01:41:30 Google Pixel,  Google Tensor Chips & Chip Shortages

01:44:00 Discord Community for Data Science, Mentorship & Abundance Mindset

01:49:00 Struggles, Battles, Hopelessness & Dysphonia