Intro: How to use this supplementary learning

Dhaval Patel

Data Entrepreneur | YouTuber | Ex - Bloomberg, Nvidia

I have 17 years of experience in Programming and Data Science working for big tech companies like NVIDIA and Bloomberg. I also run a famous YouTube channel called Codebasics where I pursue my passion for teaching. Codebasics is one of the top channels on YouTube when it comes to data science, machine learning, data structures, etc. I firmly believe that “Anyone can code” and I use analogies, simple explanations, and step-by-step storytelling to explain difficult concepts in such a way that even a high school student can understand them easily.

Hemanand Vadivel

Ex- Data Analytics Manager, 8+ Years in Europe, Microsoft Certified, Certified Supply Chain Professional

I’m a mechanical engineer who transitioned to a full time Data & Analytics manager in the UK & Germany by teaching myself Power BI, excel & anything else that was required to solve the problem. I have worked with complex data across Supply Chain, Sales, Marketing, Revenue Management, Finance and HR functions over the last 8 years to deliver effective solutions. To me, Analytics is an extra sensory organ that anyone can develop to become a superhuman at work. I have conducted several workshops and internal training to help non-technical people to become superhuman at work and now, really excited for this opportunity to share all that knowledge with you in this course.

Intro: How to use this supplementary learning

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Contents

1.1: Text Classification: Support Ticket Prioritization

1.2: Image Classification: Crop Yield Detection New

1.3: RAG-Based Gen AI: ChatGPT for Private Organizational Data

1.4: Chatbot: Food Delivery Chatbot

1.5: LLM Powered Real Estate Chatbot New

1.6: Recommendation System: Book Recommendations

2.1: Intro: How to use this supplementary learning

2.2: Statistical ML Project: Build a House Prediction System

2.3: Deep Learning Project: Build a Potato Disease Classification System

2.4: NLP Project: Build a chatbot using Dialog Flow

2.5: Gen AI Project: Build a news research tool in finance domain

Intro: How to use this supplementary learning

Lecture content Locked

Contents

1: 6 Industry Case Studies

1.1: Text Classification: Support Ticket Prioritization

1.2: Image Classification: Crop Yield Detection New

1.3: RAG-Based Gen AI: ChatGPT for Private Organizational Data

1.4: Chatbot: Food Delivery Chatbot

1.5: LLM Powered Real Estate Chatbot New

1.6: Recommendation System: Book Recommendations

2: Supplementary Learning (Industry Projects)

2.1: Intro: How to use this supplementary learning

2.2: Statistical ML Project: Build a House Prediction System

2.3: Deep Learning Project: Build a Potato Disease Classification System

2.4: NLP Project: Build a chatbot using Dialog Flow

2.5: Gen AI Project: Build a news research tool in finance domain

Intro: How to use this supplementary learning

Lecture content Locked